Milena Angelova
email: mangelova@tu-plovdiv.bg

Vishnu Manasa Devagiri

Veselka Boeva
email: veselka.boeva@bth.se

Peter Linde
email: peter.linde@bth.se

Niklas Lavesson
email: niklas.lavesson@bth.se

Manasa Vishnu
email: vishnu.manasa26@gmail.com

Devagiri

An Expertise Recommender System Based on Data from an Institutional Repository (DiVA)

Keywords: data mining, DiVA, expertise retrieval, knowledge management, natural language processing

Introduction 1

Finding experts in academics is an important practical problem, e.g. recruiting reviewers for reviewing conference, journal or project submissions, partner matching for research proposals, finding relevant M. Sc. or Ph. D. supervisors etc. In this work, we discuss an expertise recommender system that is built on data extracted from the Blekinge Institute of Technology (BTH) instance of the institutional repository system DiVA (Digital Scientific Archive). DiVA is a publication and archiving platform for research publications and student essays used by 46 publicly funded universities and authorities in Sweden and the rest of the Nordic countries (www.diva-portal.org). The DiVA classification system is based on the Swedish Higher Education Authority (UKÄ) and the Statistic Sweden's (SCB) three levels classification system. Using the classification terms associated with student M. Sc. and B. Sc. theses published in the DiVA platform, we have developed a prototype system which can be used to identify and recommend subject thesis supervisors in academy.

Related Work 2

The discovery of expertise is crucial in supporting a number of tasks. For example, finding an appropriate expert when one needs guidance on a subject matter, or needs to fill a vacancy based on relevant expertise, or needs to find research collaborators working in similar areas etc. The methods used for developing systems that facilitate mining of expertise can be classified into two main categories: methods based on mining unstructured information and methods based on social networking sites.

Unstructured information includes emails, Web pages, wiki, reports, etc. Text mining tools are used to index technical terms from unstructured documents, which can be queried to identify subject experts. Some of the important tools using this information include email expertise extraction (e3) system [START_REF] Krulwich | The ContactFinder agent: answering bulletin board questions with referrals[END_REF], ContactFinder [START_REF] Campbell | Expertise identification using email communications[END_REF], MIT Expert Finder [START_REF] Vivacqua | Agents for expertise location[END_REF], etc. A major limitation of these methods is the authentication of information.

Today there are many social networking sites, some specifically for the scientific community, such as Research Gate, Nature Network etc. Experts have to feed in information about their subject expertise, domains, publications, credentials, etc. A major limitation of these methods is in the adding and updating of information.

A common drawback to both approaches is that they are based on non-peer-reviewed information provided by the user, i.e. they can be biased.

In the recent years research on identifying experts from online data sources, such as the DBLP library, Microsoft Academic Search, Google Scholar Citation, LinkedIn, PubMed etc., has been gradually gaining interest [START_REF] Abramowicz | Semantically Enabled Experts Finding System-Ontologies, Reasoning Approach and Web Interface Design[END_REF][START_REF] Balog | Finding similar experts[END_REF][START_REF] Bozzon | Choosing the Right Crowd: Expert Finding in Social Networks[END_REF][START_REF] Boeva | Semantic-aware Expert Partitioning[END_REF][START_REF] Boeva | Identifying a Group of Subject Experts Using Formal Concept Analysis[END_REF][START_REF] Hristoskova | A Graph-based Disambiguation Approach for Construction of an Expert Repository from Public Online Sources[END_REF][START_REF] Jung | Finding topic-centric identified experts based on full text analysis[END_REF][START_REF] Singh | Developing a Biomedical Expert Finding System Using Medical Subject Headings[END_REF][START_REF] Stankovic | Linked Data Metrics for Flexible Expert Search on the Open Web[END_REF][START_REF] Tsiporkova | Tool support for technology scouting using online sources[END_REF][START_REF] Zhang | Expert Finding in a Social Network[END_REF]). An example is a Web-based biomedical expert finding system, proposed in [START_REF] Singh | Developing a Biomedical Expert Finding System Using Medical Subject Headings[END_REF], which can be applied to identify subject experts and subjects associated with an expert. The system builds and maintains a big repository of biomedical experts by extracting the information about experts' peer-reviewed articles that are published and indexed in PubMed. Two other interesting approaches using semantic matching and developing trust algorithms are [START_REF] Charlin | The Toronto Paper Matching System: An automated paperreviewer assignement system[END_REF] and [START_REF] Osman | Trust and Matching Algorithms for Selecting Suitable Agents[END_REF]. [START_REF] Charlin | The Toronto Paper Matching System: An automated paperreviewer assignement system[END_REF] have developed an automated reviewer assignment system that can be used to find suitable reviewers for conference papers. The assessment of reviewers' expertise is based on their previously published papers and self-assessed expertise about the submissions. [START_REF] Osman | Trust and Matching Algorithms for Selecting Suitable Agents[END_REF] propose a trust model that calculates the expectation about an agent's future performance in a given context by assessing both the agent's willingness and capability through the semantic comparison of the current context in question with the agent's performance in past similar experiences. А comprehensive survey on the state-of-the-art methods in expert finding and summary of these methods into different categories based on their underlying algorithms and models is presented in [START_REF] Lin | A Survey on Expert Finding Techniques[END_REF].

Institutional repositories have been around for at least 20 years, but it is only recently you find some discussions on how to create new services using text analysis or data mining in institutional repositories or library catalogues [START_REF] Kerdprasop | Knowledge Mining in Higher Education[END_REF], Lawrence 2016[START_REF] Okamoto | Text Analysis of Academic Papers Archived in Institutional Repositories[END_REF][START_REF] Tonon | Data Mining as a Tool for Information Retrieval in Digital Institutional Repositories[END_REF] and even more rare are any evidence on actual resources based on these ideas.

The use of university repositories is not so common, in spite of their wealth of bibliographic metadata of both local scientific records and student theses records. There are papers describing mining the contents of scientific papers for more effective information discovery and selection [START_REF] Saggion | Scholarly Data Mining: Making Sense of Scientific Literature[END_REF][START_REF] Tonon | Data Mining as a Tool for Information Retrieval in Digital Institutional Repositories[END_REF][START_REF] Okamoto | Text Analysis of Academic Papers Archived in Institutional Repositories[END_REF]. Other areas that are reported in the literature is personalized services for library user using data mining technology or book recommendation systems for library user based on user profiling [START_REF] Ding | Research on Personalized Service of Library in Colleges and Universities Based on Data Mining Technology[END_REF][START_REF] Jomsri | Book Recommendation System for Digital Library Based on User Profiles by Using Association Rule[END_REF], Ciu et al. 2014). These are the main uses of data mining in university institutional repositories that we can find being reported in the literature so far. One of the reasons for not exploiting institutional repositories on a greater scale could well be that they are often created, administered and run by librarians who generally are not research oriented and especially not towards computer science. Another reason might be that the data in the repositories often is entered by researchers and students themselves and therefore, in many cases, are not quality controlled. An elaborated discussion of this issue can be found in the section "Data".

Identifying Experts from Institutional Data Sources 9

Many scientists who work on the expertise retrieval problem distinguish two information retrieval tasks: expert finding and expert profiling, where expert finding is the task of finding experts given a topic describing the required expertise [START_REF] Craswell | Overview of the TREC-2005 Enterprise Track[END_REF], and expert profiling is the task of returning a list of topics that a person is knowledgeable about [START_REF] Balog | Broad Expertise Retrieval in Sparse Data Environments[END_REF]). In the considered context we need to deal with both expertise retrieval tasks.

Profiling of Expertise

10 An expert profile may be quite complex and can, for example, be associated with information that includes: email address, affiliation, a list of publications, co-authors, but it may also include or be associated with: educational and (or) employment history. This information can be separated into two parts: expert's personal data and information that describes the expert area of competence. Personal data is used to resolve the problem with ambiguity. This problem refers to the fact that multiple profiles may represent one and the same person and therefore must be merged into a single generalized expert profile. Namely, the process of merging expert profiles is driven by the calculation of the similarity scores between different entities composing the profile, e.g., expert name, affiliation, email address, etc. [START_REF] Boeva | Measuring Expertise Similarity in Expert Networks[END_REF].

11 The data needed for constructing the expert profiles could be extracted from various Web sources, e.g., LinkedIn, the DBLP library, Microsoft Academic Search, Google Scholar Citation, PubMed etc. In our work, we have used data extracted from DiVA repository to construct the tutor profiles and ontology model. Initially, the extracted data was divided into personal data and a list of subject terms. Personal data has entities, e.g., first and last name of each thesis supervisor, affiliation containing information about university, faculty and department, and also the academic role of the supervisor. Each B. Sc. or M. Sc. thesis presented in DiVA is associated with a list of keywords that are selected and entered by the author in order to describe her/his thesis subject. We have used these keywords and the built ontology to describe the supervisors' area of competence. The built ontology is a conceptual model of the domain of interest and it is used to attain accurate and topic relevant expert profiles. When a conceptual model is missing then, e.g. the Stanford part-of-speech tagger [START_REF] Toutanova | Enriching the knowledge sources used in a maximum entropy part-of-speech tagger[END_REF] can be used to annotate the different words in the text collected for each expert (supervisor) with their specific part of speech. The tagger also defines whether a noun is a plural, whether a verb is conjugated, etc. The annotated text can further be reduced to a set of keywords (tags) by removing all the words tagged as articles, prepositions, verbs, and adverbs.

In view of the above, an expert profile is defined as a list of keywords (domain-specific topics), extracted from the available information, describing her/his expert area. The problem with ambiguity has been resolved using the extracted personal data. The expert profiles with the same names are candidates to be merged into a single expert profile. For instance, if the supervisors' names and affiliations are identical then their expert profiles are merged into a single one. Most supervisors who are affiliated with BTH have not entered their email addresses in the DiVA repository. Therefore, we have not used the email address as an entity to resolve the problem with ambiguity.

Expertise Similarity

An important issue in an expertise retrieval context is to establish a way to quantify how well the area of expertise of an individual expert conforms to a certain subject or to estimate the expertise similarity between two experts. The calculation of expertise similarity is a complicated task, since the supervisor expertise profiles usually consist of domain-specific keywords that describe their area of competence without any information for the best correspondence between the different keywords of two compared profiles. One possibility to measure the expertise similarity between two expert profiles (or between a supervisor profile and a subject profile) is by taking into account the semantic similarities between any pair of keywords that are contained in the two profiles. Several semantic distance and similarity algorithms can be applied within structured terminological resources [START_REF] Leacock | Combining Local Context and WordNet Similarity for Word Sense Identification[END_REF][START_REF] Rada | Development and application of a metric on semantic nets[END_REF][START_REF] Wu | Verb semantics and lexical selection[END_REF]. In this case, the algorithms count the number of edges (links) between the two keywords (classification terms) in order to compute the relatedness of these terms.

In the current study, we use a modified Wu and Palmer measure, proposed in (Manjula [START_REF] Shenoy | A new Similarity Measure for Taxonomy Based on Edge Counting[END_REF], to calculate similarity between two ontological elements. In considered context all expert profiles are described by a list of domain specific terms, where he/she is an expert. Assume that each expert profile i is described by a list of P i keywords. In our experiments, we use the modified where L is the shortest distance between two given concepts, D is the depth of the ontology, N is the distance from the least common ancestor to the root, N1 and N2 are respectively, the distances from the two considered concepts to the root, and λ is a coefficient that is 0 when the concepts are in the same hierarchy and 1 when they are neighborhood concepts. Namely, the authors consider how far the two considered concepts are semantically and where they are located in the ontology. The modified Wu and Palmer measure (noted by s herein), finds the shortest path between two concepts in the ontology tree and the depth of the whole ontology. Then the expertise similarity S ij between two expert profiles i and j (i ≠ j), can be defined by the arithmetic mean of semantic similarities between the corresponding keywords, i.e.

Where s(k il ,k jm ) is the semantic similarity between keywords k il and k jm calculated accordingly to the definition given above (Manjula [START_REF] Shenoy | A new Similarity Measure for Taxonomy Based on Edge Counting[END_REF].

Expert Finding

The experts finding task can be viewed as a list completion task, i.e. the user is supposed to provide a small number of example experts who have been used to work on similar problems in the past, and the system has to return experts with similar area of competence. In our context, the user can be a university student, a director of a study programme or other administrative staff and the returned experts are recommended subject thesis supervisors.

Another possibility is to present the domain of interest by several preliminary specified subject categories and then the available experts can be grouped with respect to these categories into a number of disjoint expert areas (clusters) by using some clustering algorithm, as e.g. ones developed in [START_REF] Boeva | Semantic-aware Expert Partitioning[END_REF][START_REF] Boeva | Identifying a Group of Subject Experts Using Formal Concept Analysis[END_REF]). In the considered context each cluster of experts can itself be thought as the expertise area of any expert (supervisor) assigned to the cluster. In this case, in order to select the right individuals (thesis supervisors) for а specified task the user may restrict her/his considerations only to those experts who are within the cluster that is identical with (or at least most similar to) the task's subject. The specified subject and the expert area can themselves be described by lists of keywords, i.e. they can be compared by way of similarity measurement.

Description of the Prototype System and Results

The developed prototype system has been evaluated and validated on information extracted from the BTH DiVA installation, concerning thesis supervision of researchers affiliated with BTH. The extracted DiVA classification terms are used to build an ontology that conceptualizes the thesis domain supported by the university. The supervisor profiles of the tutors affiliated with the BTH are constructed based on the extracted DiVA data. Each supervisor profile is defined by a list of keywords (classification terms) used in the DiVA theses that have been supervised by the researcher in question to describe her/ his area of expertise.

Data

The data set consists of 2216 records of student theses published between 2010 and 2017. One issue with data entered during a long interval like this is that the quality of the records varies. In the case of our sample data this certainly is true. In 2015 the BTH repository joined the national Swedish consortia DiVA-system. At around the same time the library started supplying records to a national portal "SwePuB" intended to become a national tool and a resource for the collection of publication data for bibliometric analyzes and data processing (SwePub). The DiVA migration and having SwePub harvesting our records meant that the library needed to focus much more attention on the quality of the records. The amount of meta data attached to every record increased.

Records entered by students or staff themselves usually have quality issues. In our case we have quality issues with records entered before the second half of 2015. Beginning in the fall of 2015 records are always quality checked by staff from the library or the university departments.

Another data issue is knowing what expert in the used data set still is affiliated with BTH.

In a data set covering eight years many supervisors have come and gone. In our case we needed a big data set to create and validate a prototype system so the issues discussed above are not really a problem. But if you want to put an Expertise Recommender System into everyday use issues like these must be paid close attention to.

Ontology Description

We have defined our ontology as a formalization of concepts and relations between them. The domain concepts are described by classes and the relations between them is defined as "isSubclassOf". Main focus in our ontology are classes and their sub-classes. The model in this study is created using National Subject Categories in DiVA (Linköping University Library, 2011) that is standard for the Swedish listing of research subjects 2011 and classification terms from extracted data. National Subject Categories in DiVA are separated into three levels. Namely, the main categories (the highest level) are Agricultural Sciences, Engineering and Technology, Humanities, Medical and Health Sciences, Natural Sciences, and Social Science. These main categories are located at the first level of the ontology. The others two levels are described by the sub-subject areas that belong to the each of main categories. The second level has 26 subject categories and the third level consists of 257 categories, respectively. From the extracted data we have taken the subject terms (specific domain keywords) and added them to the structure of ontology model as classes. In that way, the created ontology tree has a four level depth.

Metrics

Silhouette Index [START_REF] Rousseeuw | Silhouettes: A graphical aid to the interpretation and validation of cluster analysis[END_REF]) is a cluster validity index that is used to judge the quality of any clustering solution C = {C 1 , C 2 ,…, C k }. Suppose that the considered data set contains the attribute vectors of m objects. Then the SI is defined as , where a i represents the average distance of object i to the other objects of the cluster to which the object is assigned, and b i represents the minimum of the average distances of object i to object of the other clusters. The values of Silhouette Index vary from -1 to 1.

Results

26 As it was mentioned above the test data is downloaded from BTH DiVA installation, concerning thesis supervision of researchers affiliated with BTH. The extracted data has been used to construct the supervisor profiles and ontology model. Each supervisor profile is defined by a list of keywords (domain-specific terms). After resolving the problem with ambiguity, the set of supervisors has been reduced to 375 expert profiles.

27 We have studied two different experiment scenarios. In the first scenario, the user is supposed to provide an example supervisor and the developed recommender system will return a list of experts (supervisors) with close (similar) expertise. In this scenario, initially the system calculates the expertise similarity scores between the given supervisor and the all other supervisors presented in the system by using the expertise similarity formula described in section "Expertise Similarity". Then the system returns a ranked list of similar experts who are recommended subject thesis supervisors. For instance, we have tested the system by using an example supervisor whose expertise can be described by the following subject terms: database, performance, usability, web server, cloud computing and Amazon web services. The system has returned a list of the supervisors ranked with respect to the similarity of their expert profiles to the profile of the example supervisor. In Table 1, we list the ten top ranked supervisors who have been recommended by the system. The calculated expertise similarity scores between the example supervisor and the all other supervisors presented in the system are in the range between 0.046 and 0.77. The expertise of each top recommended supervisor is described by the keywords found in her/his expert profile (the second column in Table 1). As one can notice the all top ranked supervisors have expertise that is overlapped to different extend with the competence of the given example supervisor. For example, the expertise of supervisor 1 covers usability subject from the example expert profile while supervisor 8 has competence overlap in two subjects: database and performance. k and evaluating the obtained solutions by the Silhouette Index (SI). We have applied kmeans for k between 2 and 257 (the maximum domain-specific classes in ontology). The selected optimal value for k is 16 and the corresponding average SI score given on the clustering solution generated for k = 16 is 0.38. In this scenario, in order to select the right individuals for а specified thesis subject the user may restrict her/his considerations only to those supervisors who are within the cluster that is identical with (or at least most similar to) the given subject. The experts in the selected cluster can be ranked with respect to the similarity of their expert profiles to the specified subject. For example, if we need a supervisor with expertise in database and parallel computing we will use cluster 0 (see Table 2), in which all experts have competence either in one or in both fields. We have checked how the 10 top ranked supervisors returned by the system in the first experiment scenario has been distributed between the generated clusters. The obtained grouping is presented in Table 2. As we can see the supervisors who have been grouped together have a similar area of competence. For instance, supervisors 3, 4, 7 and 8 are distributed in one and the same cluster (cluster 0). The main expertise of supervisors 3 and 4 is in cloud computing while supervisors 7 and 8 both have competence in database.

The supervisors 2, 5, 6 and 10 are grouped in the cluster 3. For example, the supervisors 5 and 6 have expertise in performance and the others are in cloud computing and video streaming. However, supervisors 1 and 9 are in a different cluster (cluster 15 in Table 2), because as we can see in Table 1 they have very unique expertise in comparison with the others.

It is interesting to notice that the generated clustering solution partitions the supervisors into 16 disjoint clusters (subject categories), i.e. each supervisor belongs to only one cluster. However, as it can be seen in Table 2 there are subject terms that participate in the description of more than one subject category, e.g., parallel computing is used for clusters 0 and 3 (the third column in Table 2), i.e. the obtained subject categories can have an overlap on some topics.

Conclusion and Future Work

The main contributions of this work are:

i. a prototype system for ranking potential thesis supervisor candidates based on their previous supervision experience and expertise retrieval approaches; and

ii. an evaluation of the prototype with real-world data extracted from the BTH instance of the institutional repository system DiVA. The proposed system is based on online information, can be updated regularly, and uses standardized subject vocabulary, i.e., DiVA classification terms associated with each thesis. It can be implemented by any university that uses an institutional repository with a controlled vocabulary including keyword fields in the records, i.e. it is general.

For future work, we aim to pursue further evaluation and validation of the developed expert recommended system on bigger datasets and also on data extracted from other DiVA university repositores. Our future plans also involve using additional information about the supervisors' expertise, e.g., extracting information about the supervisors' research publications, in order to build richer expert profiles and ontology model.

BIBLIOGRAPHY

  Wu and Palmer measure to calculate the semantic similarity between two keywords. Manjula Shenoy et al. propose an improved version of the standard Wu and Palmer measure (Manjula Shenoy et al., 2012). The modified Wu and Palmer semantic similarity measure s is defined as follows:

Table 1

 1 The 10 top ranked subject thesis supervisors recommended by the system in the first experiment scenario. In the second scenario, the set of supervisors is clustered into groups of experts with similar expertise by applying k-means partitioning algorithm. The optimal number of clusters is determined by clustering the set of supervisors applying k-means for different

			Expertise
	Expert Keywords	similarity
			score
	1	user experience, usability	0.770
	2	privacy, security, cloud computing	0.763
	3	cloud computing, security metrics, security threats, security measurement frameworks	0.760
	4	procedural city generation, perlin noise, performance, game content 0.760
	5	machine learning, parallel computing, multiprocessor, performance	0.760
	6	mobile, power, consumption, android, native, web, enterprise service bus, performance, framework	0.754

Table 2

 2 Grouping of the 10 top ranked supervisors recommended by the system in the first experiment scenario (ones listed in Table1).

	Experts Cluster Description of clusters
			usability; tessellation; android; security threats; main-memory database;
	3, 4, 7, 8 0	database; distributed databases; parallel computing; security; data mining
			and etc.
	2, 5, 6, 10	3	usability; data mining; performance monitoring; systematic review; video streaming; parallel computing; mpeg-2 standard; mpeg-2 standard; nosql database; machine learning; cloud computing and etc.
	1, 9	15	usability; quality of experience; urban design; systematic literature review and etc.

analytics" funded by the Knowledge Foundation (grant: 20140032) in Sweden.

ABSTRACTS

Finding experts in academics is an important practical problem, e.g. recruiting reviewers for reviewing conference, journal or project submissions, partner matching for research proposals, finding relevant M. Sc. or Ph. D. supervisors etc. In this work, we discuss an expertise recommender system that is built on data extracted from the Blekinge Institute of Technology (BTH) instance of the institutional repository system DiVA. The developed prototype system is evaluated and validated on information extracted from the BTH DiVA installation, concerning thesis supervision of researchers affiliated with BTH. The extracted DiVA classification terms are used to build an ontology that conceptualizes the thesis domain supported by the university. The supervisor profiles of the tutors affiliated with the BTH are constructed based on the extracted DiVA data. These profiles can further be used to identify and recommend relevant subject thesis supervisors.


Elisabeth Heinemann

Michael Kaiser

Judith Schulte

Fabian Cremer

The Value of Network Sustainability: Why We Join Research Infrastructures

Introduction

In the social sciences and humanities, scholarly communication is at the heart of researchers' activities. Scholarly communication practices differ greatly from those in other disciplines. An example of this is the format of the monograph, which reveals other particularities such as the workflow, the way researchers collaborate, the correlation between fieldwork and theory, and the way arguments are elaborated and constructed (OPERAS Consortium, 2017). The publication can thus not be considered the last step of the research process or merely as the output produced, but it is indissolubly linked to the whole research process (OPERAS Consortium, 2017).

The research landscape in the social sciences and humanities, however, is diverted and fragmented into an environment of many small players who are highly specialized. This is mainly due to multiple disciplines and sub-disciplines, as well as different languages [START_REF] Mounier | The structure of research in social sciences and humanities[END_REF]. This specificity in the social sciences and humanities should not be considered a flaw but rather an adaption to the reality of the research landscape. Nonetheless, the fragmented scientific community becomes disintegrated if the different players act in isolation and negatively impact one another [START_REF] Mounier | The structure of research in social sciences and humanities[END_REF].

To tackle the situation, the European Commission works on setting up the European Open Science Cloud, an infrastructure to support open science in Europe (European Commission, 2016). At the same time, a research-driven approach to the The Value of Network Sustainability: Why We Join Research Infrastructures ELPUB 2018 internationalization of scholarly communication in the social sciences and humanities is needed. This approach can bring together researchers from multiple disciplines and various infrastructures using different tools and languages and integrate their research into the European Open Science Cloud. This paper explores how OPERAS (open access in the european research area through scholarly communication), a research infrastructure that addresses these particular challenges in the social sciences and humanities, implements network sustainability and how such a sustainable network benefits and at the same time arises from its partners. The Max Weber Foundation, an OPERAS core group member, is used as an example. The paper provides an overview of the Max Weber Foundation and the OPERAS research infrastructure and uses a network analytical approach to OPERAS as a community network. It then investigates the concept of network sustainability and presents concrete examples of how this is implemented within the research infrastructure.

Max Weber Foundation

The Max Weber Foundation is a legal entity, funded by the German Ministry of Education and Research, but nonetheless independent in its activities as a research organization. The foundation is comprised of ten humanities research institutes abroad. Its goal is to promote research focusing on history, culture, economy and on the social sciences, and to foster a mutual understanding between Germany and the guest countries. The electronic publication platform perspectivia.net is the international, cross-epochal and interdisciplinary portal of the foundation (Max Weber Foundation, 2018).

The Max Weber Foundation closely works with national infrastructure partners, especially DARIAH-DE, to develop services at a national level. DARIAH-DE is a consortium developing and providing digital infrastructure and services to support research in the humanities and social sciences with digital methods and procedures (DARIAH-DE Consortium, 2018). With joint research projects and cooperation partners, such as the "Forum Transregionale Studien," the Max Weber Foundation takes part in the internationalization of research in the social sciences and humanities. The forum is a national German organization with partners from different research centers. It seeks the internationalization of research by enabling scholars from abroad to work on transnational research topics as invited fellows or at conferences (Forum Transregionale Studien, 2018).

Without having any significant service provider for an information infrastructure in their own organization, the Max Weber Foundation relies on direct partnerships and national or international initiatives including libraries, computing centers, digital humanities centers and joint infrastructure projects. As a core group member of OPERAS, the Max Weber Foundation has a vital interest in shaping a sustainable research infrastructure and integrating research in the social sciences and humanities internationally.

OPERAS-distributed research infrastructure

OPERAS was born from a clear understanding that the specific challenges in scholarly communication in the social sciences and humanities have to be addressed in a common effort. The research infrastructure presently gathers 35 organizations from thirteen European countries as well as one international partner and is coordinated by a ninemember core group. It is led from France by OpenEdition, an infrastructure dedicated to electronic resources in the humanities and open sciences. OPERAS members' backgrounds are very diverse: publishers and publication platforms, infrastructure providers and libraries, universities and research organizations. OPERAS is supported by OPERAS-D (design) and HIRMEOS (High Integration of Research Monographs in the European Open Science Infrastructure), two projects funded under Horizon 2020, the biggest research and innovation program of the European Union. The projects' results are the backbone for the future services that the OPERAS research infrastructure will deploy. Not all OPERAS partners are actively involved in both of the projects and some partners only participate in one of them. The Max Weber Foundation is a project partner in both, OPERAS-D and HIRMEOS, and a core group member of OPERAS.

Img. 1: The OPERAS network © Laetitia Martin 9

As key objective, the OPERAS-D project has prepared a design study that defines governance models, scientific and technical concepts for future services that the infrastructure will provide, and has established a roadmap to achieve these goals according to the requirements for long-term sustainability. The study's main findings are 1. the need to consider scholarly communication as the heart of scientific research and not as one of its outputs, particularly in the social sciences and humanities;

2. the fragmentation of the field; and 3. the need and the conditions for integration at European level (OPERAS Consortium, 2017).

10 The design study serves as a basis on which the future of OPERAS is built. The Max Weber Foundation's formal role in OPERAS-D is to ensure a clear and efficient communication and dissemination of the project's results. platforms and referencing and indexing service providers, five sets of data and metadata are implemented on participating platforms: identification metadata, named entities data, certification metadata, annotation data and metrics metadata (HIRMEOS Consortium, 2018). The Max Weber Foundation, while not being one of the implementing platforms, formally participates in the communication and dissemination of HIRMEOS' project results.

Using the two projects' results, the research infrastructure OPERAS will deploy services at three levels. At a first level, shared services between partners will offer communication and publication services to their communities.

OPERAS as a community network

Social networks have increasingly been studied since the early 20th century. With the rise of social network analysis, an interdisciplinary approach that works on the premise that all social life is formed by relations and on the patterns that these create, scholars of all disciplines have started to systemically study social networks [START_REF] Marin | Social Network Analysis: An Introduction[END_REF]. Within social network theory, a network is often defined as "a set of nodes (or network members) that are tied by one or more types of relations" [START_REF] Wasserman | Social Network Analysis: Methods and Applications[END_REF].

In principle, everyone and everything can be a network member; including organizations, companies, web pages, countries, or positions [START_REF] Marin | Social Network Analysis: An Introduction[END_REF].

In the case of OPERAS, the partners that have signed a letter of support to the research infrastructure and have been accepted as members can be seen as the nodes of the social network. Even though the term social network is commonly synonymously used for social media networks such as Twitter and Facebook, a social network is not necessarily an online network. To avoid confusion, however, I will in the following use the term community network for the network of OPERAS partners rather than social network. partners according to their function in OPERAS, which does not include the national differences between stakeholders nor does it differentiate between the types of organizations. Lastly, a grouping according to members' types of organizations creates the problem of multiple group memberships. The Max Weber Foundation, for instance, is comprised of ten humanities research institutes abroad. Yet, the foundation also operates a publication platform. It is thus not only a member of the group of universities and research organizations but at the same time also a quasi-publisher. Another example is Georg-August-University Göttingen, which is a public German university but is participating in OPERAS through their university library. Therefore, in chapter 6, which introduces the implementation of network sustainability within OPERAS, I will not group the research infrastructure's members but rather look at all partners as interdependent but individual nodes.

What then are the benefits to a network analytical approach to the sustainability of a research infrastructure? I could find little literature that explicitly deals with the centrality of community networks for the sustainability of research infrastructures.

There is, however, research on the role of social networks for project stakeholder management. Provan and Kenis show that the form of governance has a huge impact on the effectiveness of a network [START_REF] Provan | Modes of Network Governance: Structure, Management, and Effectiveness[END_REF] and Chung and Crawford, for example, propose to use social network theory to identify stakeholders and improve project management [START_REF] Chung | The role of social networks theory and methodology for project stakeholder management[END_REF]. In the field of technology clusters and companies, there is research that shows that social network formation is crucial to the sustainability of technology clusters and economic activities in some regions [START_REF] Casper | How do technology clusters emerge and become sustainable? Social network formation and inter-firm mobility within the San Diego biotechnology cluster[END_REF] and an influential paper has shown that the success of Silicon Valley can largely be understood through network analysis [START_REF] Saxenian | Inside-Out: Regional Networks and Industrial Adaptation in Silicon Valley and Route 128[END_REF]. For research infrastructures, a network analytical approach takes the attention away from the "static" expertise and formally defined tasks of a single member and draws it towards the "mobile" connections that this member has with other partners and to the work that is done "informally". It thus recognizes the value of sharing expertise and knowledge and of the informal connections within research infrastructures [START_REF] Marin | Social Network Analysis: An Introduction[END_REF]. I argue in the following that these are crucial aspects to the sustainability of a distributed research infrastructure such as OPERAS.

Network sustainability

Concepts for sustainable research infrastructures in the social sciences and humanities have only recently entered the international agenda.

The Brundtland Report of 1987 triggered a worldwide discussion on sustainability and environmental concerns. The report defines sustainable development as "development that meets the needs of the present without compromising the ability of future generations to meet their own needs" (United Nations, 1987). It furthermore outlines three areas of sustainability: economic, social, and environmental sustainability. This widely used definition of sustainability, even if not clearly inclusive of research infrastructures, can be adapted to them. Research infrastructures also need to satisfy present requirements while staying flexible and resilient to meet future needs-needs which are not at all self-evident. Sustainable research infrastructures must therefore constantly evaluate how the requirements they serve are developing and adjust to them. The 2030 Agenda has enhanced the Brundtland definition in 2015 with 17 Sustainable Development Goals (SDGs) and 169 targets -none of which include the social sciences and humanities or target research infrastructures (United Nations, 2015). Goal no. 17, however, which asks for a revitalization of global partnerships for sustainable development, defines "multi-stakeholder partnerships that mobilize and share knowledge, expertise, technology and financial resources" as an important systemic issue (United Nations, 2018).

Adapting the Brundtland definition and the SDGs to research infrastructures, three areas of sustainability arise:

1. economic sustainability which guarantees the research infrastructure's funding and the efficiency of its governance;

2. technical sustainability that includes data storage and the resiliency of dynamic software; and 3. network sustainability which includes gaining access to other networks and interest groups, sharing knowledge and increasing each other's visibility, and staying current and state-ofthe-art.

When is a network sustainable? Granovetter, who in 1973 introduced the now famous idea of the strength of weak ties, argues that while it is obvious that strong ties are beneficial to a network-they share information readily and communicate frequentlyweak ties enable the network to gain information and access to nodes that are more distant and therefore to information that is original [START_REF] Granovetter | The Strength of Weak Ties[END_REF]. Applying this to a distributed research infrastructure means that the network needs a strong core as well as diverse and distributed partners. More recently, Krebs and Holley have identified five general patterns that can be observed in effective networks: nodes share common attributes and goals, they are diverse, there are several paths between nodes, the average path length is short, and some nodes are more important than others [START_REF] Krebs | Building Adaptive Communities through Network Weaving[END_REF]. They furthermore argue that because networks are often left unmanaged, nodes sharing similar attributes connect and close by, resulting in a lack of diversity and effective paths of communication within the network [START_REF] Krebs | Building Adaptive Communities through Network Weaving[END_REF]. Effective community networks, they argue, arise with an active leader taking responsibility and forming a hub. The leader then usually connects to outside potential partners, making them part of the network and thereby extending it. In an efficient and sustainable network, the leader needs to encourage connections between the nodes according to the individual needs. Some interactions might lie dormant, but the paths need to be created [START_REF] Krebs | Building Adaptive Communities through Network Weaving[END_REF]. This "hub-and-spoke" model, however, should only be a temporary structure as it places too much power and liability in the hub. The network becomes more resilient the fewer nodes include the hub for their connections. The transition of the leader from the weaver of the network to a facilitator of network weaving is crucial for a sustainable network [START_REF] Krebs | Building Adaptive Communities through Network Weaving[END_REF]. While Krebs and Holley exemplify their research on economic networks, it is an important insight that is also useful when looking at distributed research infrastructures. Thus, a sustainable network in the context of a distributed research infrastructure does not merely imply forming connections to exchange information during professional and scientific conferences in the short run-although the importance of this should not be underestimated-but to achieve long-term and large-scale integration and unification as a basic service for researchers.

Network sustainability for research infrastructures is, although phrased differently, included in the report on long-term sustainability of research infrastructures published by the ESFRI Long-Term Sustainability Working Group. They argue that "a robust longterm vision is the most important prerequisite in order to successfully and sustainably build and operate" a research infrastructure (ESFRI, 2017). This vision goes well beyond financing mechanisms and business models for research infrastructures. The report suggests, among others, to launch continued and practically-oriented initiatives to improve the management of research infrastructures "through the exchange of best practices and lessons learnt, and contribute to strategic planning, evaluation, and training" (ESFRI, 2017).

Taking into account the research that has been done on the sustainability of networks and bearing in mind the specificities of a distributed research infrastructure, I will show in the following chapter that a sustainable network enables a distributed research infrastructure to understand future needs, to then address those needs, and finally to also shape them. This is not only beneficial for the research infrastructure but also for the partners individually, as shown on the example of the Max Weber Foundation.

Network sustainability: practical implementation

The projects OPERAS-D and HIRMEOS have substantially increased the sustainability of the research infrastructure OPERAS. OPERAS-D has developed a concept for economic sustainability, which includes a governance model and a future roadmap for the research infrastructure in the OPERAS Design Study. The HIRMEOS project addresses the technical sustainability of the services developed within OPERAS. While both, economic and technical sustainability, are closely interlinked with network sustainability, the following seeks to isolate how network sustainability is achieved and why this is not only beneficial for OPERAS but also for its partners.

Understanding future needs

A clear benefit for the Max Weber Foundation and other partners arises from gaining access to other networks and interest groups that they can rely on when organizing workshops or conferences or are in need of specific information or expertise. The community network connects the foundation with other interest groups, for instance national infrastructures but also European initiatives as e.g. CESSDA-a consortium promoting international research cooperation and results, CLARIN-a European research infrastructure for language resources and technology, DARIAH-EU-a pan-European infrastructure supporting digital research and methods in the social sciences and humanities, and OpenAIRE-a project promoting open scholarship. While some of these are formal partners of the OPERAS infrastructure (DARIAH-EU, e.g., is a partner of the HIRMEOS project) the connection to other networks and interest groups takes place through other members. In most cases, more than one partner in OPERAS can connect other members to these networks and interest groups.

At the same time, OPERAS benefits from the Max Weber Foundation's knowledge of and connections within Germany and the host countries of its institutes. An example of this is the OPERAS-D final conference, to take place in summer 2018, that brings together different stakeholders from and outside of OPERAS. Regardless of the conference's topic, the selection of relevant speakers was only possible because of the OPERAS community network. In addition, the conference will grant access to a larger international

The Value of Network Sustainability: Why We Join Research Infrastructures ELPUB 2018 community to all OPERAS partners. The same holds true for the HIRMEOS project, where partners conduct webinars and workshops together.

This reciprocal network sustainability ultimately ensures that OPERAS stays and becomes aware of future needs which can only then be addressed. Gaining access to other networks and interest groups is only possible with a network of diverse partners, the strong "weak ties." It can also only be robust if there are several partners that can connect others to outside networks and interest groups.

Addressing future needs

The strongest benefits from research infrastructures with a sustainable network arise from sharing knowledge, information, and experience. OPERAS has set up working groups which develop white papers on the topics of advocacy for open access, tools (research and development), standards, business models, best practices, multilingualism, and platforms and services. The working groups represent groups of partners sharing the same goals but who have diverse backgrounds. While in the beginning OPERAS' coordinator OpenEdition has acted as a hub for the research infrastructure, the working groups are a first step to facilitate network weaving for the core group members of OPERAS who act as contact points for the working groups (see img. 1). The Max Weber Foundation is the contact point of the advocacy working group and thus unites the expertise of various OPERAS members in this area. The working groups enable the Max Weber Foundation to actively pass on its expertise while at the same time acquiring knowledge from other partners. The working group papers are a result of this process where sharing information with a network benefits all partners. This especially holds true for the identification of future projects that OPERAS partners can work on together, which is an essential part of the working groups.

Another example from the HIRMEOS project is the metrics collection tool. Javier Arias from Open Book Publishers describes this and the benefits for organizations with fewer resources in "Collecting inclusive usage metrics for Open Access publications: the HIRMEOS project" [START_REF] Arias | Collecting inclusive usage metrics for Open Access publications: the HIRMEOS project[END_REF].

Sharing knowledge, information and expertise aids OPERAS in becoming sustainable as it prepares the infrastructure in solving challenges that it has previously identified and addressing future needs. To sustainably share knowledge, information and expertise, however, communication needs to happen via short paths but be organized through partners that are especially committed to the research infrastructure.

Another aspect that supports OPERAS in addressing future needs is that the research infrastructure increases the visibility of the Max Weber Foundation as a research organization internationally and contributes to the reputation of its researchers. This is important as a main obstacle to publishing open access for researchers is the perceived lower reputation (OPERAS "Advocacy Working Group", 2018). Increasing one's own visibility and reputation outside the national context can thus help to meet this challenge. At the same time, OPERAS can more effectively address future requirements if it is visible, which becomes possible with more widely known partners. Another example stems from the HIRMEOS project, which enables the platforms that directly benefit from its services to develop and provide their own services within OPERAS and to integrate into the European Open Science Cloud. The Max Weber Foundation is a project partner of HIRMEOS without being one of the implementing platforms. The network value for the foundation arises from actively participating in the shaping of future services and the processes of standardization. The latter is urgently needed for the foundation as it specializes in transnational and transregional research projects.

Staying current and state-of-the-art is a prerequisite for partners of a distributed research infrastructure to actively shape future needs. This only becomes possible if partners of a research infrastructure share some common attributes and goals but are diverse enough to influence the landscape from different angles.

Obstacles to network sustainability

Implementation of network sustainability does not always work smoothly. Some of the aspects described in the previous chapter can be achieved through the management of the research infrastructure and the business model. This includes, for instance, creating a core group to facilitate the network weaving of strategic partners, implementing regular video conferences to assist a continuous communication, and forming working groups to connect partners with similar goals. Also the formal requirements of funded projects supporting a research infrastructure contribute to a sustainable network.

Yet, the intrinsic commitment of partners involved is crucial. It stems on the one hand from the benefits of network sustainability for themselves and on the other hand on the sustainability and thus effectiveness of the infrastructure it creates. This causes a virtuous circle where partners' commitments stem from the direct benefits of network sustainability, which increases the network sustainability, which in turn intensifies the advantages mentioned before. However, while the benefits are huge, they often do not show immediately. This can lead to a lower level of dedication than desired. Reasons for this include time constraints, a lack of labor force, money constraints, and a misjudgment of the overall work that participation in a distributed research infrastructure requires.

While this lowers the overall effectiveness of a distributed research infrastructure, it does not necessarily impede a sustainable network that can understand, address and shape future needs. The level of commitment does not have to be equally high for all partners at all times because a sustainable network has several paths between the nodes. One can lie dormant and others can be used in its place. Yet, oftentimes research infrastructures do not have several paths between the nodes. OPERAS has, for instance, only one partner in some geographical regions (see img. 2) and within the core group there is only one partner each who is the responsible contact point for a working group (see img. 1). If the level of commitment of one of these partners is low, the research infrastructure's network sustainability risks impairment.

Another problem is the length of the average path between nodes, which should be as short as possible in a sustainable network. In the case of OPERAS, OpenEdition, which has in the beginning acted as the hub of the research infrastructure, began to enable the core group members to act as network weavers themselves. Yet, this does not shorten the communication paths of all members of the network equally, especially if they are only involved in one of the working groups. A network with long communication channels quickly becomes inflexible and unable to perform its function of understanding, addressing and shaping future needs.

Not all these obstacles will necessarily impede network sustainability. Yet, every research infrastructure is well advised to take these possible risks into account.

Conclusion

In order to become and stay sustainable, distributed research infrastructures must satisfy present requirements while staying flexible and resilient to meet future needs. This means that it is not enough to only consider their economic model and technical viability.

Research infrastructures with a sustainable network can understand, address and shape future requirements through granting their partners access to other networks and interest groups, through sharing knowledge, information and experience and increasing each other's visibility, and by enabling their partners to stay current and state-of-the-art. They can only do so if partners share common attributes and goals but are diverse at the same time. Communication between members of a research network has to follow short paths while some partners (a core group) are more important to the communication within the research infrastructure than others. Finally, there needs to be more than one path between partners to make a research network sustainable.

While some of these aspects can be achieved through the management of the research infrastructure and the business model, most derive to a large extend from an intrinsic commitment of the partners involved. The level of commitment does not have to be high at all times if the research infrastructure has more than one path of communication between its partners. However, this is not yet the case with many partners in OPERAS, making the research infrastructure vulnerable. In addition, the length of the average path of communication between partners should be as short as possible in a sustainable network. OPERAS has shortened the lengths of the communication channels by establishing working groups but they are still long for members of only one communication group. This risks inflexibility and therefore the sustainability of the network.

Network sustainability deserves permanent efforts. While funded research projects are clearing the path for a sustainable community network, stakeholders of a research infrastructure need to actively engage. Shared services, such as conferences, trainings, and advocacy for open science require constant exchange of information. Projects may serve as development sprints and content providers, yet keeping track of new developments and evaluating techniques is a permanent task for all partners and goes beyond every project's lifetime. While the project OPERAS-D has identified current challenges for scholarly communication in the social sciences and humanities, a sustainable research infrastructure needs to constantly reevaluate the status quo. The solutions, particularly for unified services such as certification, discovery, and research for society, require continuous adaption to future needs. To be able to also shape those future needs, a sustainable research infrastructure must actively participate in a discourse in the respective field. Solutions to the challenges distributed research infrastructures face can for that reason only be sustainable if addressed by an international consortium.

BIBLIOGRAPHY

  More than merely addressing future needs, a sustainable community network supports partners of a research infrastructure in shaping the future landscape. The community network of OPERAS has for example supported the Max Weber Foundation in participating in an active discourse on open access and legal issues in Europe. It thus supports partners in staying current and state-of-the-art. More concretely, OPERAS has signed the Scholarly Publishing and Academic Resources Coalition's (SPARC) open letter protesting against the planned reform of the European Union's copyright directive and has led the Max Weber Foundation to sign the Jussieu Call for open science and bibliodiversity, thus supporting a flourishing and diverse academic publishing landscape.

	The Value of Network Sustainability: Why We Join Research Infrastructures
	Shaping future needs
	ELPUB 2018

  The Value of Network Sustainability: Why We Join Research Infrastructures ELPUB 2018

The Value of Network Sustainability: Why We Join Research Infrastructures ELPUB 2018

for their precious insights and suggestions. This paper is largely based upon the findings of the OPERAS Design Study, a deliverable of the OPERAS-D project funded by the European Commission in Horizon 2020.

APPENDIXES

List of figures

Img. 1: "The OPERAS network." January 2018. © Laetitia Martin.

Img. 2: "OPERAS partners." April 2018. CC By.

ABSTRACTS

This paper develops the concept of network sustainability. To become and stay sustainable, distributed research infrastructures must satisfy present needs while at the same time be flexible and resilient to meet future requirements. For this it is not enough to merely build a resilient economic model and be technically viable. Research infrastructures that can understand, address and shape future needs have a sustainable community network. Clear characteristics of a research infrastructure with a sustainable network are that partners gain access to other networks and interest groups, that knowledge, information and expertise is shared freely among partners, that the infrastructure increases partners' visibilities and vice versa, and that partners are enabled to stay current and state-of-the-art. This is shown on OPERAS (open access in the


Game not Over: End-User Programming and Game System Modding as Models for Extending Community Engagement

Matthew Wells 1

In December of 2016, Microsoft Studios-the game publishing arm of the tech giantreleased a software package entitled "Age of Empires II-Rise of the Rajas". This was supplementary content-typically termed an "expansion pack"-for the renowned realtime strategy game Age of Empires II. Releasing additional content in this manner is common in modern commercial gaming as a means to extend a product's shelf life, but Rise of the Rajas was strikingly unusual because the original Age of Empires II had been released all the way back in 1999 (Whitaker, 2016). Expansions are typically released at most a year or two after a game's publication date. But in this case, 17 years had come and gone prior to Rajas' release.

2

What motivated Microsoft to release Rise of the Rajas? It was, in fact, a commercial response to the work of the original game's vital DIY hobbyist game programming community, which had sustained the original Age of Empires II game in part by creating new features for it-that is, new artwork, new scenarios, and even new rules and mechanics, which in gaming circles are collectively called "mods", short for "modifications". Such mods serve to sustain digital games-and, by extension, the digital platforms upon which such games are made-that are considered by their creators to be no longer commercially viable. "Modders" study their chosen platforms intensely, and learn to modify and expand upon them. As well as extending the amount of playtime that such games offer, such practices also serve to foster emergent communities, as modders share their creations with others, and trade tricks and techniques with like-minded creators. As such, these groups serve to disseminate and add to knowledge bases that otherwise would have likely been lost. They also use modding as a means to challenge and subvert the dominant discourses espoused by their games, and to create more inclusive artefacts that foster closer connections to chosen games and gaming communities. These amateur publishing communities are at the heart of what makes modding culture so vibrant.

It is for these reasons that I will advocate in this paper for the study and adoption of these techniques within academic scholarship, and in particular design research, in order to promote sustained engagement with published research findings and designed artefacts. As a recent article on the topic has noted, " 'modifications' have become the creative bridge that's combined developers and fans into one talent-infused organism. Through a set of dedicated amateur programmers and designers, a game can live on when its creators move on to pastures new, or be reborn in a wildly different tangent" (Reseigh-Linconln, 2017). The advantages of bringing such vitality to academic publishing channels are clear-research projects that have technically "ended", due to changes in funding or focus, can be kept going by those that they impact the most. Design projects that address open-ended "wicked" problems can continue to remain relevant through the efforts of those who are directly present to witness and respond to contextual changes that occur over time. Moreover, fostering playful cultures around such problems can engender creative practices that go beyond what is possible via traditional academic research methodologies. And all of this would be centered around sites of digital publicationmodding culture is what it is because it is a culture centered around publishing communities. This article will proceed in several stages. First, previous research on modding will be discussed, as well as efforts in the digital humanities to foster online digital cultures. Second, design research will be examined in more detail. Following that, mods and modding practices will be discussed, including the history of modding. Finally, modding as a publishing culture will be explored at length, and connections with academic research and publication will be made. Special attention will be paid to the open source software movement, which offers similar advantages to modding, but fosters different sorts of communities. Open source software is a valuable contribution to design research, but modding offers certain benefits with respect to informality and inclusivity that will be discussed in detail.

Previous Research

With respect to existing research on game modding, the work of Hector Postigo and Olli Sotamaa is arguably the most prominent. Building on the work of Henry Jenkins and others on "participatory culture," Postigo takes the position that modders are motivated in large part by a desire to personalize the games they play, stating that they "make games 'their own' by designing unique elements of game play or importing elements from popular or national culture that had some meaning to them personally" (Postigo, 2007, p. 309; see also [START_REF] Jenkins | Fans, bloggers, and gamers: exploring participatory culture[END_REF]. Sotamaa builds on this by noting that "further motivations can range from hacking and researching to self-expression and community building" (Sotamaa, 2010, p. 252). Others have linked modding to the emergence of the "prosumer" within neoliberal economies, noting that modders themselves receive little to no compensation for their efforts [START_REF] Hong | Game modding, prosumerism and neoliberal labor practices[END_REF]. With respect to end-user development more generally, there are many researchers in the field taking a variety of approaches (see Lieberman, Paternò, and Wulf, 2006). For the purposes of my paper, I will focus in particular on the work of Gerhard Fischer, whose concept of "meta-design" within "open systems"-that is, the enabling of the user to change the shape and structure of a given piece of software-resonates strongly (see [START_REF] Fischer | Meta-design: a manifesto for end-user development[END_REF]. Fischer has used the example of the SimCity game series as a "closed system" that restrict its potential capacity to be used as a tool for experimentation and adaptation by the user [START_REF] Fischer | Meta-design: design for designers[END_REF].

Within academia, there have also been serious and considered moves towards experimentation within digital spaces, meaning that there is a pre-existing context for the acceptance and application of game modes. Scholars in the digital humanities, for example, have been experimenting with online academic projects for some time. Among the most ambitious sites for such work in the Speculative Computing Laboratory (SpecLab), founded by Joanna Drucker and Jerome McGann at the University of Chicago. One of the primary goals of SpecLab has been to expose the rigidity of digital knowledge forms, but also to pair that rigidity with the subjectivity of humanities-based academic research in a way that emphasized the interpretive qualities of both elements. As Drucker notes, "the single most important challenge we gave ourselves in SpecLab was to design representations that modeled subjectivity within knowledge production," adding that "making visible these subjective acts of interpretation, and the role of imaginative play, served to challenge the authority claims of formal logical systems" (Drucker, 2009, p. xiv).

Among the most prominent of SpecLab's projects was the collaborative game Ivanhoe, which operated by taking existing literary works and encouraging players to play with them via in-character amendments to the existing texts. Ivanhoe operates by players making moves, each of which adds new information to a chosen work. As Sansing explains it, "you can make a move by writing what happens before the story begins, or by writing what happens after the story ends, or by writing about something that happens during the story out of sight of its readers, or completely outside the scope of the book" (Sansing, 2003, p. 45). As such, "you can add to the story by writing a new passage or chapter about characters or actions that the original author did not include in the book, or you can add to the work's historical context by playing outside its covers" (Sansing, 2003, p. 45). Drucker explains the reasoning behind this design as follows:

Ivanhoe was meant as an imaginative, provocative space that would move beyond instrumental management and statistical processing of text-based materials. It was designed in response to the question of how the future of literary and humanities scholarship might be provoked by electronic instruments, and on what foundations adequate tools could be established (Drucker, 2009, p. 66).

Despite its unorthodox approach to textual interpretation-or perhaps because of it-Ivanhoe offered a model that could have appealed to game players outside of its original focus on those with knowledge of canonical literary texts. The game's scope could have been expanded to the point that it became its own discursive framework, as Rockwell observes:

Ivanhoe could become not one game, but a framework for the implementation and playing of a class of text based games of deformance. A framework or toy with which we can play games of learning and collaboration. A framework that would provide another starting point for games of criticism (Rockwell, 2003, p. 93).

Despite its promise, however, Ivanhoe has since been shut down, and is no longer available online. Its impermanence is, arguably, a symptom of a larger problem with respect to online academic publishing that will be discussed in more detail later in this article.

Design Research

The work outlined here is grounded in longstanding efforts to promote an increased focus on design as a research tool, and to connect with "users" of such research via collaborative design efforts. As noted by Margolin, design research emerged in the 1960s and 1970s in the United Kingdom and the United States, through the efforts of scholars within the disciplines of engineering and architecture such as Bruce Archer, John Chris Jones, and Horst Rittel, with Christopher Alexander also emerging as a prominent figure [START_REF] Margolin | Design research: towards a history[END_REF]. But with the advent of interactive digital computing technologies-and wide consumer application of such technologies, beginning (arguably) in the 1980s and 1990s-it assumed a new prominence within business and academia. It should be noted that interactive computing had emerged long before concerns over the aesthetics and efficacy of interfaces were raised. When the first systems were conceived of and developed in the mid-1960s-first at Cambridge, Massachusetts tech firm Bolt, Beranek, and Newman, and soon after that at MIT-the once-familiar command prompt was the only feasible way to facilitate user interactivity via print-based teletype machines [START_REF] Wells | Cold war games: operational gaming and interactive programming in historical and contemporary contexts[END_REF]. In the 1970s, researchers at Xerox's Palo Alto Research Centre (PARC) launched the first major efforts towards graphical user interfaces within operating systems and related applications, though it was not until Apple adopted PARC's ideas for the operating system of their Macintosh line of personal computers in the 1980s that GUIs entered the consumer market in a major way, and it was not until the 1990s, with the rise of Microsoft Windows, that the command prompt began to lose its prominence [START_REF] Wells | Cold war games: operational gaming and interactive programming in historical and contemporary contexts[END_REF]. As such, even the most concerted and longstanding research efforts in human-computer interaction (HCI) have a relatively short pedigree.

The arguments, however, for focusing such efforts on design are strong. As scholars in the area have noted, "when researchers actually construct something, they find problems and discover things that would otherwise go unnoticed. These observations unleash wisdom, countering a typical academic tendency to value thinking and discourse over doing" (Koskinen et al., 2011, p. 2). Yet it has also been recognized that the benefits of design research increase when such efforts are taken outside the academy. As Gerald Fischer and Elisa Giaccardi, two of the more active computer scientists in this area, have argued, "the diverse and collective stock of scientific content and artistic or stylistic ideas that individuals and communities share, reinterpret, and use as a basis for new ideas and visions constitutes the vital source of invention and creativity" (Fischer and Giaccardi, 2007, p. 28). Beyond tapping outside talent, Fischer has also discussed how design problems are not static, and that public engagement is necessary in order to sustain successful design efforts, noting that "design projects and designed artifacts, given the nature of their context (wicked problems, change, unique characteristics, and multiple stakeholders) often evolve over long periods of time" (Fischer, 2001, p. 1). He is speaking here about design more generally-his background in computer science lends itself to an approach that focuses on software engineering, which has a strong corporate focus-but Fischer has participated in more scholarly design research project within the context of enabling creative problem-solving within communitarian contexts [START_REF] Fischer | Communities of interest: Learning through the interaction of multiple knowledge systems[END_REF]; see also [START_REF] Fischer | Domain-oriented design environments[END_REF], for work more singularly focused on software engineering).

Modding also resonates with the "cultural probes" approach to research in the field of human-computer interaction (HCI), and in fact may serve as an effective approach to probe-based research in HCI. Cultural probes have their roots in research at the Royal College of Art in London, specifically in their program of Computer-Related Design [START_REF] Koskinen | Design research through practice: from the lab, field, and showroom[END_REF]. Researchers Bill Gaver, Tony Dunne, and Elena Pacenti launched the Presence Project in the 1990s with the aim of deepening the engagement of elderly populations with their local communities [START_REF] Gaver | Design: cultural probes[END_REF]. But it was their unique approach to their work that is relevant here. As they explained, "We used other techniques from groups such as Dada, the Surrealists, and more contemporary artists in the probes as well," including, crucially, the situationists (Gaver, Dunne, and Pacenti, 1999, p. 26). As noted elsewhere (in relation to the Presence Project), "the situationists tried to create situations that lead people to places and thoughts that they do not visit habitually through dérive (roughly, drift) and détournement (roughly, turnabout)" (Koskinen et al., 2011, p. 91). The probes approach was subsequently adopted in HCI research; as scholars in the area have noted, "since the initial publication of cultural probes in interactions, the use of probes has proliferated widely in the HCI community" [START_REF] Boehner | How HCI interprets the probes[END_REF](Boehner et al., , p. 1078)). Such practices are playful in nature, in the sense that they are meant to present novel ideas and artifacts to audiences in unexpected, and at times seemingly nonsensical, ways and means. The "messageProbe" project, for example, which was meant to facilitate communication amongst family members, also unintentionally introduced a novel space for family play:

Another conclusion that became clear after the deployment…is that families want to have fun together, even at a distance. With the messageProbe, we saw tic-tac-toe boards, connect-the-dots games, and family member caricatures, all bringing family members from different households into shared, playful activities [START_REF] Hutchinson | Technology probes: inspiring design for and with families[END_REF].

Mods and Modding

14 A mod, quite broadly, is any modification made to an existing digital game, no matter how slight. More specifically, mods are generally recognized only if they are made by game players and other users, as opposed to professional developers, though developers occasionally elect to adopt modding practices as well, as described in the introduction. Mods generally are free to use, and in fact attempts to commercialize them have been met with fierce resistance-the popular online game portal Steam had to abandon plans to create a retail modding storefront in the wake of such opposition [START_REF] Mcwhertor | Valve kills paid mods on Steam, will refund Skyrim mod buyers[END_REF].

Modding has its roots in the game "cracking" subculture of the 1980s, in which users of games for such "home" computers as the Commodore 64 and Sinclair ZX Spectrum would hack into the source code of popular games, in part to remove their internal copyright infrastructures so they could be freely distributed (Reseigh-Linconln, 2017). Cracking was largely legitimized with the 1993 release of Doom, a landmark title which popularized the "first-person shooter" genre which is dominant in the industry today. Apart from its graphics and gameplay, what made Doom unique was the fact that its developers released to the public the tools which they used to design the game itself, including graphics editors and level editors. Such inclusions transformed many crackers into modders, as "rather than having to crack a game open…modders were given everything they could possibly need to slightly adjust or completely overhaul their new favorite shooter" (Reseigh-Linconln, 2017).

The popularity of modding has surged over the past decade or so, and developers have responded by releasing even more powerful gaming tools. A key element of such tools is the Lua scripting language. Developed in 1993 by computer scientists in Rio de Janeiro, Lua, has seen widespread adoption as a clear, concise medium with which to code game infrastructures and mechanics. As the author of a Lua reference book puts it, "Lua is easy to learn; the syntax is simple and clear. One can read and understand small Lua scripts without knowing anything about the language," and as such "it is possible to use Lua as a [scripting] language for configuration files that can be edited by people who don't know anything about programming" (Emmerich, 2009, p. 1). While a knowledge of programming certainly helps when it comes to working with Lua, it can also serve as an effective teaching language, and as such has helped many modders become proficient in more sophisticated techniques by which to modify and extend their games.

Just as important as the mods themselves are the online communities that have grown up around the more popular modded games. One of the most vibrant of these communities, particularly with respect to the age of the games it focuses on, is the website Simtropolis. The Network Addon Mod is all about giving you options-tons of options-on how to thoughtfully and efficiently design your city's transportation system. Some of the elements it adds are major, like massive highway systems, high speed rail, and working canals, and some are small, like turning lanes, nicer curved roads, and elevated pedestrian walkways [START_REF] Livingston | Mod of the week: Network Addon Mod, for SimCity 4[END_REF].

Simtropolis and websites like it are vital elements in terms of sustaining modding communities and ecosystems, a point that will be revisited soon.

Modding is an ideal template for collaborative design research precisely because it encourages continued reflection on a design artifact, and enables all parties invested in a design artifact to continue the design process using an approach that is simultaneously personal and public. Mods are personal in the sense that they typically reflect individual interpretations of a given artifact but are also made to generate reactions from other players. The creation of a new asset based on a character from another, favoured media source, for example, indicates a personal preference for that media source, but it typically also meant to generate a positive reaction from other players who are also fans. These interpersonal practices can feed back into the design research process, creating a mutually beneficial shared space:

When designers work as facilitators rather than detached observers, the last remnants of the idea that researchers ought to be detached, impartial observers-"flies on the wall"disappear. What comes about is the idea that design is supposed to be an exploration people do together, and the design process should reflect that (Koskinen et al., 2011, p. 83).

The subjective and personal nature of modding will be discussed in more detail in the next section.

Publication: Modeling Informality and Inclusivity

Design research projects have been published and presented via familiar outlets such as academic journals and conferences, but other, possibly more effective channels have been suggested and promoted. This is particularly true (arguably) with digital design projects, where online platforms can readily offer functionality that goes beyond the display of text and images. Arguably the most ambitious move in this direction comes in the form of "webtexts", advocated primarily by scholars Cheryl Ball and Douglas Eyman. Webtexts move beyond the scholarly preference for text and simple by images by embracing a wider range of the affordances on offer within digital spaces:

Webtexts are multimedia-rich, digital, screen-based texts designed to enact an author's scholarly argument. Webtexts, in which authors design their argument using linked webpages or database-driven platforms, animations, images, audio, video, scripts, programming languages, and written text, can be equivalent in intellectual scope to an article or a book [START_REF] Ball | Editorial workflows for multimedia-rich scholarship[END_REF].

As DeVoss, Cushman, and Grabill (whom Ball and Eyman cite) explain from a pedagogical perspective, contextual discourses can lock in certain expectations with respect to the composition of digital artefacts, but that does not mean we should be constrained by such expectations:

Writing within digital spaces occurs within a matrix of local and more global policies, standards, and practices. These variables often emerge as visible and at times invisible statements about what types of work are possible and valuable… If students are to be effective and critical new-media composers, they should be equipped with ways in which they can consider and push at practices and standards in strategic ways (DeVoss, Cushman, and Grabill, 2005, p. 16).

Though webtexts need not relate specifically to design research, design is a primary focus in their design-that is, "webtext authors embrace design so that the conceptual model they use is relevant to the text's purpose and media"-so this aspect emerges implicitly, if not explicitly (Eyman and Ball, 2014, p. 115).

Webtexts show some promise, but there are issues with the paradigm. Perhaps the primary problem is usability. While venues such as Kairos encourage a diversity of approaches to webtext publication, issues arise when the platforms designed for such texts are difficult to parse, and, more problematically, when they degrade over time. This latter issue is particularly true with older works, which have tended to "shrink" in size as the resolutions of computer screens have increased. The emergence of mobile "smartphones" and tablet computers as popular means to access online media has also rendered certain webtexts inoperable to many potential users, as technologies such as Flash are not supported on most devices. Without a solid grounding in HCI, moreover, many webtexts are difficult to penetrate without a good deal of experimentation. While that might be an end goal in and of itself with respect to the author's intentions, the fact remains that, with such a vast amount of online content available (academic or otherwise), inscrutable webtexts may simply be passed over. It is beyond the scope of this article to examine each point in detail, but commonalities may be summarized. Essentially, the problems Hurley identifies come down to managing a disaparte group of individuals contribuing to a single project. Concerns over project cohesiveness, shared standards and beliefs, and distributed motivation inevitably arise. When conflicts arise, as blogger Chris Hoffman has observed, the end result is that "internal drama begets forks, forks, and more forks," meaning that the central project is splintered into multiple associated projects, thereby destroying the centrality that makes open-source so attractive in the first place [START_REF] Hoffman | The downsides of open source software[END_REF]. Moreover, the more popular an open-source project becomes, the more acute these problems become, with the typicaly result being that organizations with little to no interest in full community involved take charge.

Game modding works much differently from this model, the key difference being its inherent decentralized structure. Modding is not about developing a central project because that central project is already completed, or at least its continued development is not controlled by modders. This appears to be an imbalanced situation, but that is only assessing the situation from one perspective. From the perspective of the project publisher, agency is distributed, in the sense that a published artefact is produced, but is also inherently extensible and modifiable. Removed from the need of having to develop this artefact themselves, modders can and do play with the artefact in unique and interesting ways. Its content and/or aestheitc are often subverted, a playful response that is difficult to establish in open source contexts. Alternative and antithetical visions flourish in modding cultures, often in unexpected ways-the strictly single player game

Half-Life, released by Valve in 1998, was quickly modded into Counter-Strike, which was eventually released commercially and is now one of the most successful multiplayer game series in existence.

In terms of publishing platforms, modding cultures rely largely on older web technologies such as message boards-while seeminly a questionable approach to imitate, there are advantages that will be discussed shortly. However, the website Simtropolis, which has already been discussed briefly, is worth revisiting here to analyze its structure and format in more detail. Simtropolis is organized around several categories, each with its own "tab" that is displayed near the top of each page. Each tab links to a specific category of fan-created content-the first, and perhaps most important, lesson for academic publishers is that almost all of the content on the site is created by the users themselves. Yet this content is organized around several information "hubs"-specifically, the citybuilding games that the site caters to-providing the necessary constraints for creative output [START_REF] Stokes | Creativity from constraints: the psychology of breakthrough[END_REF]. Among the categories of content are "fan art" creations such as city "journals"-replete with images and descriptive text-and custom-made maps. Such media are important elements of fan culture, though they differ from mods in the sense that they reflect interactions with games as they exist in their initial commercial state. As practices, they resemble in character the comments that may be appended to certain types of online articles (academic or otherwise), in the sense that they result from engagements with pre-existing media texts.

The tab "ST Exchange" leads to the content page for game mods, and is thus of primary concern here. The Exchange provides links to all of the mods available on the site. As there are over 19,000 such mods for SimCity 4 alone, however, such access must be managed. As such, the front page of the Exchange displays only a grid of featured mods, which rotate in and out on a regular basis. Each row of the grid encompasses a different category of content. The first displays "featured" mods, including the NAM mod discussed above; this is the only permanent fixture on the main page. The next row, labeled "What's New", shows new mods that have been uploaded to the Simtropolis database. The next row, "Highest Rated", is an important one, in that it reflects a means by which the modding community itself can feed back into the system. Using a typical five-star rating system, users are able to score the mods they download and use based on their opinions of them; these scores are then averaged to create the overall ratings. Popular mods (in terms of downloads) are then listed, and mods are subsequently subdivided in other ways below. All of this fosters a culture in which featured content in fluid, and useful and effective mods are given the most attention.

None of this technology is particularly cutting-edge of course, but it also reflects the informality of modding cultures. The most important aspect of such community sites is the ease with which they may be constructed. Message board software is generally free, and simple to set up. While version control software such as Git, which is used to control open-source projects, is generally also free, its setup and administration is much more complicated. Message board are not only easier to operate, they can be freely hosted on a number of specialty websites such as ProBoards (https://www.proboards.com/). Sites such as Simtropolis often begin on such free hosting sites before migrating to their own web servers and URLs. This DIY approach to community building is an important hallmark of modding culture. While modding hubs do not have the sophistication of sites such as Github, they foster levels of individual agency over communication and distribution infrastructures that often gets lost in larger open-source projects.

This DIY informality also fosters what is perhaps modding's most important quality-its potential to subvert, challenge, and supplement dominant social, cultural, and political discourses. In Bethesda Softworks' 2015 release Fallout 4, the game begins with the player cast as a husband in a typical heterosexual relationship in a nuclear family. Soon after the release, however, a fan modded the game so that the opening dialogue implied that the player was in a same-sex relationship with his spouse, provoking a backlash that served to highlight the challenge to dominant Western domestic discourses that the mod offered [START_REF] Gohl | Fallout 4's 'LGBT Family' mod sparks death threats[END_REF]. In 2013, game designer Mike Mika famously modded the Nintendo Entertainment System version of Donkey Kong for his daughter to make Pauline, the female character in the game, the hero, as opposed to the object of rescue [START_REF] Mika | Why I hacked Donkey Kong for my daughter[END_REF].

Modding cultures are full of examples of such endeavours to swap and subvert traditional gaming (and societal) roles, and to make games more reflective of the diverse audiences that play them. Such efforts at inclusivity allow modders to more closely connect with their games, and to larger gaming communities.

32 How does this all translate to the academic realm? One could imagine a similar content hub serving as an academic publishing site. Despite the benefits of collaborative design research as described in the previous section, there is as of yet little to no discussion as to how the efforts of users could be published in a manner that puts their work in equal standing with the original design research. Instead, users are stripped of their agency within traditional academic publishing outlets, as the researchers themselves describe projects on their own terms in articles and associated media. A modding forum, on the other hand, has the potential to turn user contributions into "first-order" content, created by the users themselves and standing equally with the scholarly materials they support and extend. In addition to the mods themselves, users of websites such as Simtropolis are given space to describe their creations, provide screenshots of their work in action, and link to dependent files, creating complete and robust contributions to the overall project of extending a given game. Sites such as Simtropolis also carry the advantage that they are built out of pre-existing, and often free and open-source, components. This carries an important advantage over webtexts, which tend to be usercreated, and thus difficult to modify and extend when necessary. Both platform and content thus work in tandem, serving to nurture a community and expand the reach and power of the works it focuses on.

Conclusion: Coded Communities

33 While the benefits of modding and modding communities to academic research have been outlined here, issues surrounding the fostering of new digital publishing practices should not be ignored. In particular, it is necessary to be mindful of the fact that digital platforms are created from code, and as such the affordances of these platforms are predetermined, or "baked in", by developers. As Kitchin and Dodge have noted, "the freedom to participate and do certain kinds of work only exists if an application's underlying calculative algorithms and communicative protocols are encoded to support such actions" (Kitchin and Dodge, 2011, p. 133). Platforms with built-in limitations would in theory limit what modding communities are able to do. As already noted, however, leading platforms are generally built out of familiar components, such as pre-existing message board software, and thus have been tested and extended over time. Yet this is still not a concern to take lightly, particularly as academic research projects would likely have requirements that would be unfamiliar to game modders. In a sense, platform development would, or should, be as open as research modding itself, inviting feedback from the communities they serve. It is this focus on community that should never waver, moreover. Publication can often be thought of as a closed process, in the sense that it may be understood to be the creation of finished products. The digital realm, however, opens up new possibilities for open-ended and extensible publishing practices. Research

Game not Over: End-User Programming and Game System Modding as Models for Ext...

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modding should thus be seen as a natural outcome of changing publishing practices, as opposed to an awkward outsider, as it leans towards the goals many researchers currently share with respect to the possibilities inherent in digital publication spaces.

ABSTRACTS

In certain digital gaming subcultures, specific games are extended and enhanced by players who create "mods", or modifications, that add new artwork, new scenarios, and even new rules. "Modders" meet in online communities that foster engagement through the discussion and selfpublication of mods, and these can keep interest in a given game going years after it is released.

Most importantly, modding allows players to challenge and subvert dominant discourses, and to foster cultures of inclusivity. These DIY efforts could be adapted by academic publishers, particularly those focused on design research, to encourage sustained engagement with scholarly materials. This article discusses the history of modding, provides examples, and sketches one online modding community in detail. It then makes the argument that modding is a form of enduser engagement of the sort advocated by scholars such as Gerald Fischer, and compares modding to other online academic publishing efforts, such as webtexts.

INDEX

Keywords: games, modding, mods, programming

A

  potential alternative model for design research is the open-source software development model, in which users work as a (typically distributed) team to develop and refine a given software artifact. Open-source also centralized platforms such as Github, and formal mechanisms to connect contributors and their code to larger projects. Yet the open-source model is far from perfect, and advocate David Hurley has identified the following major "challenges" with the paradigm(Hurley,

BIBLIOGRAPHY

  Whitaker, R. (2016, December). "Age of Empires II HD is getting a new expansion titled Rise of the Rajas." The Escapist. Retrieved from http://www.escapistmagazine.com/news/view/169041-Ageof-Empires-II-HD-Getting-A-New-Expansion-Rise-of-the-Rajas

This is all important with respect to modding because some of the most successful mods are those that introduce absurdities into normally restrained game spaces, as will be discussed below.

AUTHOR

MATTHEW WELLS

Ryerson University, Toronto, Canada matthew.wells@ryerson.ca (corresponding author)

Game not Over: End-User Programming and Game System Modding as Models for Ext... ELPUB 2018