Christophe Debruyne
email: debruync@scss.tcd.ie

Atul Nautiyal
email: nautiyaa@scss.tcd.ie

Declan O'sullivan
email: declan.osullivan@scss.tcd.ie

Publishing and Consuming Irish Administrative Boundaries as Linked Data

Keywords: Linked Data, Geospatial Information, GeoSPARQL

We report on the Linked Data platform developed for the administrative boundaries governed by the Ordnance Survey Ireland (OSi), as they wished to serve this data as an authoritative Linked Open Data dataset on the Web. To implement this platform, we have adopted best practices and guidelines from the industry and academia. We demonstrate how this dataset can be combined with other datasets to add a spatial component to information. We believe that the publication of this dataset not only provides opportunities for third parties (including scholars) in their activities, but that this outcome of this initiative is of importance, as the OSi made the authoritative dataset available. With the current platform deployed, future work will include the inclusion of other (closed) datasets and the investigation of access mechanisms.

Introduction

Linked Data [START_REF] Bizer | Linked Data -The Story So Far[END_REF] refers to both an initiative and a set of best practices and guidelines to publish and interlink data on the Web using standardized Web technologies such as HTTP URIs, RDF and SPARQL. Important is the availability of authoritative datasets published as Linked Data that allows one to interlink information, create novel applications or support third parties in their activities such as scholars analyzing datasets. An example of the inclusion of an authoritative dataset as RDF into the Linked Data Web is Linked Logainm [START_REF] Ryan | Linked data authority records for Irish place names[END_REF], where a set of Irish place names were related with their geographic counterpart in GeoNames1 and DBpedia2 using the SILK Link Discovery Network [START_REF] Isele | Silk Server -Adding missing Links while consuming Linked Data[END_REF]. The Ordnance Survey Ireland, Ireland's National Mapping Agency, embarked on an initiative to serve an authoritative boundaries dataset they govern as Linked Data. In this paper, we elaborate on OSi's Linked Data platform and demonstrate how this dataset can be used with other datasets for scholarly activities.

OSi's Linked Data Platform

The platform is available at http://data.geohive.ie. An important distinction has to be made between geographic features and their geometries [START_REF] Battle | Enabling the geospatial semantic web with parliament and geosparql[END_REF]. The first denotes things such as building, counties, forests, and the latter their geometric representation. For the first, we have developed an ontology3 for the administrative boundaries that have been made available as open data through Ireland's New National Mapping Agreement4 . Features such as Barony and County were introduced as subclasses of GeoSPARQL 5 's concept of Feature.

Since we argue that a geometry is "merely" an attribute of a feature in the same way a name is an attribute of a person, we have, for the time being, chosen not to provide geometries with a URI. The geometries of a feature have thus to be accessed via a feature with geo:hasGeometry. Geometries are available in three levels of detail: generalized up to 100, 50 and 20 meters. The level of detail has an impact on bandwidth and rendering, amongst others. An example of how descriptions of features are presented in HTML is shown in Fig. 1. We have also decided to separate non-information resources from information resources, the first being things and the latter being documents describing these things, by giving them different HTTP URIs. For instance, the County Dublin is identified with the URI x, described by the HTML document with URI y and described by an RDF document with URI z. Obtaining the representation that one needs is done with a technique called content negotiation.

To avoid an excessive load on the server, we have chosen to limit access to the SPARQL endpoint and set up a Triple Pattern Fragments (TPF) server [START_REF] Verborgh | Triple pattern fragments: A lowcost knowledge graph interface for the web[END_REF] instead. A TPF server basically returns a result set for simple triple patterns and it is up to a TPF client to compute the result of a SPARQL query. The platform furthermore hosts the boundary datasets as dumps and hosts simple ontologies for Irish administrative boundaries according to Linked Data principles.

Consuming Ireland's Boundary Data

The administrative boundaries that are currently available as Linked Data are: City and County Council, City Council, Civil Parish, County Council, Electoral Division, Local Electoral Area, Municipal District, Rural Area, Barony, County, and Townland. We note that City, County, and City and County Councils are indeed three separate entities.

To demonstrate how the boundary data can be used, we will combine it with the 2011 Census data.6 . We will look at the number of people in private households by size in "CTY areas in Ireland"7 . This concept corresponds with the union of City, County, and City and County Councils in the OSi dataset. There are 34 CTYs in the census data. The OSi data has 26 County Councils, 3 City Councils and 2 City and County Councils. These numbers seem not to add up, but it is important to note that the data was collected in 2011 and the counties of Tipperary North and Tipperary South were merged into County Tipperary in 2014. The census has also split the city and county of the 2 City and County Councils considered as administrative boundaries by the OSi.

The CSO dataset contains observations for each area. One type of observation collected is the number of people living in households of different sizes. By retrieving those with the query below and asserting owl:sameAs statements between the correspondences, one can formulate, for instance a query to retrieve the total numbers of people living households of 8 people or more. These can then be plotted on a map using OSi's boundary data, as shown in Fig. 2.

prefix qb: <http://purl.org/linked-data/cube#> DESCRIBE ?x WHERE { ?x a qb:Observation . ?x qb:dataSet <http://data.cso.ie/census-2011/dataset/persons-in-houses-by-size/cty>. } This demonstrates that OSi's authoritative boundary data can be easily combined with other datasets and add a spatial component for scholars to explore. While not demonstrated in this paper, the geospatial infrastructure allows one also to retrieve information via the geometries (e.g., "retrieve all civil parishes in this square").

Conclusions and Future Work

In this paper, we reported on the development of a Linked Data Platform for Ireland's Administrative Boundaries for and provided by the Ordnance Survey Ireland, who are the custodians of that data. As they are the custodians, the dataset that has been published is regarded as authoritative. We have demonstrated how this data can be combined with other datasets to This demonstrates that OSi's authoritative boundary data can be easily combined with other datasets, which can facilitate data exploration for, amongst others, scholars.

Current limitations are the absence of "versions" of administrative boundaries and the limited availability to the SPARQL endpoint. Data about boundary evolution, though addressed from a conceptual point of view and simulated, cannot be served as they are not (yet) stored in OSi's technology stack. TPFs do not provide support for all SPARQL queries and GeoSPARQL's spatial predicates. Access mechanisms to the SPARQL endpoint will be investigated.

Fig. 1 .

 1 Fig. 1. Description in HTML of County Dublin on the left and its three geometrieswith the one generalized up to 100 meters drawn on a map -on the right.

Fig. 2 .

 2 Fig. 2. Plotting the results of the query on a map.

http://geonames.org/

http://dbpedia.org/

http://ontologies.geohive.ie/osi

http://www.osi.ie/news/new-mapping-agreement/, last accessed April

5, 2016. 5 http://www.opengis.net/ont/geosparql

Available as Linked Data on http://data.cso.ie/

See http://data.cso.ie/census-2011/page/classification/areas/CTY

Acknowledgments. The ADAPT Centre for Digital Content Technology is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is cofunded under the European Regional Development Fund. We thank the Ordnance Survey Ireland (OSi) for permitting us to use their boundaries dataset for the purposes of this study. Within OSi, we are especially grateful for the input and domain expertise provided by Lorraine McNerney and Éamonn Clinton.


Giovanni Colavizza

Epidemics in Venice: on the Small or Large Nature of the pre-Modern World

Keywords: Epidemics, Venice, Small-world networks

recently argued that the pre-modern contact world was physically and, by set inclusion, socially not small-world. Since the Black Death and similar plagues used to spread in well-defined waves, the argument goes, the underlying contact network could not have been small-world. I counter here that small-world contact networks were likely to exist in pre-modern times in a setting of the greatest importance for the outbreak of epidemics: urban environments. I show this by running epidemic diffusion simulations on the transportation network of Venice, verifying how such network becomes small-world when we account for naval transportation. Large epidemic outbreaks might not have been even possible without the catalyst of urban small-worlds.

Introduction

Pre-modern epidemics still foster interest, especially around their etiology, dynamics and impact [START_REF] Alfani | Il ritorno della peste? Un'introduzione alla storiografia recente[END_REF]. A key topic in this respect is understanding the mechanics of different kinds of epidemics. For example, the Black Death might have been an exceptional, if not completely different phenomenon from the bubonic plague [START_REF] Christakos | Recent results on the spatiotemporal modelling and comparative analysis of Black Death and bubonic plague epidemics[END_REF]. Pre-modern plague outbreaks are generally considered to have been more impactful in cities than in the countryside, where the population density was lower and the means of transportation not as effective [START_REF] Alfani | Il Grand Tour dei Cavalieri dell'Apocalisse[END_REF]. Evidence suggesting a strong link between trade routes and sequences of plague outbreaks, as well as their seasonality, has been suggested [START_REF] Bossak | Did medieval trade activity and a viral etiology control the spatial extent and seasonal distribution of Black Death mortality?[END_REF]. As a consequence, the interaction of different kinds of epidemics and the spatio-temporal dynamics of an outbreak in a urban environment might have been more complex than expected [START_REF] Ell | Three days in October of 1630: detailed examination of mortality during an early modern plague epidemic in Venice[END_REF]. In view of the lack of extensive data sources on pre-modern epidemics, modeling efforts are of great importance in order to help bounding the limits of the possible.

A small-world effect is an observation of a low average shortest path length between any two nodes in a network, irrespective of the number of nodes in such a network and their average clustering coefficient [START_REF] Newman | Networks: an introduction[END_REF]. In practice, usually a few edges connecting far-away nodes suffice to make the whole network small-world: an example are modern transportation networks, where flight routes among cities connect far-away urban ground networks. Despite small-world contact networks being intuitively linked with fast spreading epidemics, in practice spreading often slows down due to structural and temporal effects [START_REF] Holme | Network reachability of real-world contact sequences[END_REF]. As an example, [START_REF] Karsai | Small but slow world: How network topology and burstiness slow down spreading[END_REF] found that small-world networks can present slow spreading due to topological effectsdense intra-cluster and sparse inter-cluster connectivity-and bursty activity patterns of individuals.

Marvel et al. [START_REF] Marvel | The smallworld effect is a modern phenomenon[END_REF] recently claimed that the contact network of the premodern world was not small-world-not physically nor socially. Their evidence is the wave-like representation of epidemic diffusion at a continental scale in premodern Europe, examples of which are to be found in most historical atlases. I contend here that it is likely that the pre-modern world was small-world, at least in urban centers. This is shown by running epidemic spread simulations on the transportation network of the city of Venice iterating over two steps: local SIR processes on fully mixed groups of persons interacting by random travelers. As soon as naval transportation is accounted for, the network becomes effectively small-world. This paper is organized as follows: methods are presented in Section 2, namely the transportation network of Venice and the epidemic model; Section 3 describes the simulations and Section 4 concludes.

Method

A simulation is proposed in order to assess to what extent the small-world of physical contacts could be a pre-modern phenomenon in a urban setting. Taking the transportation network of the city of Venice as a case study, a realistic-size population is distributed in the city, according to the urban density of different areas. The population is split in small groups, corresponding to the nodes of the network, where full mixing is assumed and SIR processes are run independently. This small groups interact with each other via travelers, who can move by land or water.

Venice Transportation Network

The transportation network of Venice was manually constructed from the modern topography of Venice, from which land and sea routes have been exported as geographical referenced segments. Nodes are created at crossing vertices, or crossroads, mirroring the urban density of any given area of the city. Edges are classified as being on land ("calle" is Venetian, green in Fig. 1) or water ("canal", blue), while nodes are classified as connecting only water edges (cyan), only land edges (grey) or connecting at least one of each typology (red). The resulting network possess 7384 nodes, 8861 edges and a low average degree of 2.4, typical of transportation networks. If we consider our proxy of urban density to be a good approximation for the density of population in a given area of the city, and if we reasonably assume that the topography of Venice did not substantially change from the XVI century to the present day, then our network can be used to simulate epidemic outbreaks in the city.

Evidently, Venice is circled by water and mixed nodes are just a lower-bound approximation of all possible landings in the city. Venice is also known for its exceptional condition of a "floating city", yet the availability of water routes was a common feat of many pre-modern urban settlements. On a larger scale, even Europe is almost circled by water, and possesses several river basin areas. Nevertheless the extent to which Venice can be taken to be representative of premodern urban environments in this respect remains to be clarified. In order to account for Venice's alleged specificity, the simulations will be rather conservative with respect to the likelihood of naval travels.

If we reasonably assume Venice to have had a maximum of circa 150'000 inhabitants during the XV to XVIII centuries1 , and assign it to all land nodes uniformly, we total 23 persons per node. The outbreak and spread of an epidemic can then be simulated by a discrete model which iterates between two selfconclusive phases (i.e. each phase is computed for all nodes independently before moving to the next phase):

-Step 1: the population of each node is considered to be fully-mixed and the time evolution of the infected fraction of the population within each node is modeled using standard approaches, here we adopt the SIR model. -Step 2: a fraction of the population moves according to different functions (power law, exponential or geometrical progression).

Epidemic Model

The epidemic model is composed of three elements: a model for the development of the infection within each node, a traveling process and its associated travel probability function. The susceptible s, infected i, recovered r (or anyway removed) model (=SIR) prescribes to divide the population into three classes. Infected individuals have contact with susceptible individuals at an average rate of β (contact rate), and infected individuals recover at an average rate of γ (infection period). This model is thus governed by the following system of differential equations:

ds dt = -β • s t • i t ; di dt = β • s t • i t -γ • i t ; dr dt = γ • i t
with s t + i t + r t = 1 at all times. Default values of β = 0.05 and γ = 0.1 were used in all experiments. Note that in our setting these values need not be above the critical threshold for a transition to an epidemic regime, which is β ≥ γ with a fully mixed population [START_REF] Newman | The spread of epidemic disease on networks[END_REF].

After the population has been updated according to the SIR model, travel occurs. For each node independently:

1. An amount of traveling population is selected uniformly at random. 2. Each traveler randomly selects a neighboring land node with probability p or, if it is in a red node, it randomly jumps to another red node with probability 1 -p. Naturally, p = 1 if the traveler is in a grey node, and backwards movements are possible. The proposed model is an approximation and does not account for several aspects of the real-world phenomenon. One sensible limitation is the absence of real movement patterns which account for the relative importance of specific destinations, which could be integrated for example using a gravity model [START_REF] Simini | A universal model for mobility and migration patterns[END_REF].

Simulation

The simplest way to simulate an epidemic outbreak is to infect a certain amount of persons in a random land node, where this amount needs to be sufficient for some traveler to survive and move. A starting condition of one node with three infected individuals was enough to generate an epidemic outbreak. For the purpose of this paper the origin of the epidemics does not matter, provided the randomly selected node is connected to the principal component of the transportation network. For what follows a node in the "San Polo" parish has been selected as the starting point (red circled in Figure 1).

In order to follow the spread of the epidemic, we use two measures calculated at any time step t. First, the standard Infection Rate IR(t), the proportion of infected persons at any give time t over all nodes, defined as:

IR(t) = n v=1 i(v t ) n v=1 i(v t ) + s(v t )
Secondly, a customized version of the Basic Reproduction Number, called transmissibility, largely inspired by [START_REF] Witten | Simulations of infectious diseases on networks[END_REF]. This transmissibility T R(t) is an approximated lower-bound to the average probability of a previously uninfected node to receive an infected traveler at time t. Define V to be the set of nodes in the transportation network, N (v) to be the distance-1 neighborhood of node v and T i(v t ) the number of infected travelers of node v at time t, then:

T R(t) ≈ 1 |V | v∈V :i(v)=0 u∈N (v) 1 -|N (u)-1| |N (u)| T i(ut) |N (v)|
Transmissibility is approximated because it only considers adjacent nodes i.e. travels of distance 1, and a lower-bound to the real measure given the division by the total number of nodes in the network. The resulting measure is a trend of the infection, strictly correlated with the Infection Rate and anticipating it.

The results of simulations are summarized in Figures 2(a) and 3(a) for the scenario where p = 1 (thus naval travel probability is 0). Figures 2(b) and 3(b) show the scenario with p = 0.85 and thus naval travel probability is 0.15. All simulations were run multiple times (blue lines) and averaged (red lines), over 200 time ticks. Note that the two settings correspond to using two different transportation networks: one where red nodes are not connected to other red nodes, and only land routes are open; another where red nodes are connected with all other red nodes in the network. The former network has an average path length of 34 and a diameter of 91, the latter has an average path length of 8.6 and a diameter of 35. Simulations have been run with a power law travel function: both exponential and geometrical progression do not change the outcomes of the two simulations, only their timings (an exponential functions lags the spread, a geometrical progression accelerates it).

If we disallow for naval travels, we clearly see the wave-like epidemic spreading process taken by Marvel et al. [START_REF] Marvel | The smallworld effect is a modern phenomenon[END_REF] as evidence for the lack of a small-world contact network in the population. In particular, the outcome is a low-infection process, shown in Figure 2(a), which behaves according to the topology of the network as the front of the epidemics progresses, Figure 3(a). This model is clearly sensible to the topology of the network. For example the rise in transmissibility from ticks 40 to 50 is due to the spread reaching the dense area before the "Rialto" bridge, and the second major peak after tick 100 is mainly due to the spread moving after the bottleneck of the "Rialto" bridge. Running the same process on a regular square lattice of comparable size-details are omitted for brevity-produces a similarly steady process of wave-like diffusion with a monotonic increase of the Infection Rate until a global maximum is reached, followed by a steady decrease. The reason for this behavior is of course the regularity of the underlying topological network of the regular lattice, as results are consistent with previous literature on the topic [START_REF] Keeling | Networks and epidemic models[END_REF].

Conversely, even a low probability of naval travel makes the process behave as in a small-world setting, with little to no effect of the underlying network topology, as shown in Figures 2(b) and 3(b). It is therefore likely that urban centers and water routes acted respectively as catalysts and fast carriers of epidemics in pre-modern times as they do now, in a sort of jump and burst pattern. The wave-like representation of pre-modern epidemic spreads across Europe might therefore be just an artifact of data aggregation. I thus suggest that an alternative model, with cities or urban conglomerates as supernodes in a network of land and water transportation, might better explain pre-modern epidemic outbreaks at the continental level. Each supernode, a city, should contain a fully-connected population of potential hosts (rats, humans, etc.). Eventually, according to seasonal patterns, cities communicate, mainly via water transport (either by sea or by rivers). The proposed approach bears strong resemblance to the super-networks of family households initially proposed in [START_REF] Ball | Epidemics with two levels of mixing[END_REF], and further expanded in [START_REF] Ball | Network epidemic models with two levels of mixing[END_REF], where every node in the supernetwork is a different network in itself-in our case small-world cities.

Conclusions

I investigated via epidemic spread simulation how the pre-modern world was likely to have been small-world at the urban scale, taking the transportation network of Venice as a case study. Without naval travel, the epidemic expands in waves, closely tied with the topology of the network. On the contrary, even with a low probability of naval travel accounted for, the process becomes qualitatively small-world. I thus argue that the interaction of small-world epidemics in cities, especially ports, and the jumps permitted by naval travels might account for the spread of large-scale epidemics in pre-modern times more than a generalized wave-like process induced by an exponentially decaying contact kernel. Several research questions remain open, specifically:

1. to what extend the case study of Venice can be taken to be representative of pre-modern urban environments in general? 2. Will the proposed model account for epidemic spread at a European scale? 3. Will evidence from historical records back the proposed model?

The purpose of this paper is two-fold. First, to caution in the use of aggregated evidence, as multiple interpretations can usually coexist with quite different mathematical models which account for the same measurable outcomes. Secondly, to suggest that the historical process of the reduction of distances across the globe, mainly thanks to transportation and communication technologies, has been gradual albeit increasingly accelerating. Small-world mechanics now proper to large-scale global networks might be found during pre-modern times in smaller-scale networks, such as urban environments. The quest then becomes to understand the pre-modern world as potentially being one where small and large-world mechanics coexisted at different times and scales.

Fig. 1 .

 1 Fig. 1. The transportation network of Venice. Green edges are land routes and blue edges water routes; grey nodes connect only land edges, cyan nodes connect only water edges, and red nodes connect at least one edge per typology. The red circle indicates the starting point of epidemic simulations.

3 .

 3 The number of movements done by each traveler is given by different travel probability functions. Given p(d) the probability of traveling d steps and k a kernel factor, three functions have been tested: (i) the power law p(k; d) = e -k•d , (ii) the exponential p(k; d) = d -k and (iii) a geometrical progression p(d) = p(d -1)/2. A default kernel parameter of k = 2.0 has been used.

  (a) No naval travel. (b) Naval travel.

Fig. 2 .

 2 Fig. 2. SIR processes over the whole population, averaged over all simulation runs.

Fig. 3 .

 3 Fig. 3. Infection Rate and Transmissibility over time. The outcomes of several runs of the simulation (in blue) are averaged (in red) to show an estimation of empirical variance.

This is an approximation of Venetian population before the major plagues of the years 1576 and 1630-31. Estimates can be found e.g. in[START_REF] Beltrami | Storia della popolazione di Venezia dalla fine del secolo XVI alla caduta della Repubblica[END_REF], p. 54. Historical analyses of the two plagues can be found in[START_REF] Preto | Peste e società a Venezia[END_REF] and[START_REF] Ulvioni | Il gran castigo di Dio: carestia ed epidemie a Venezia e nella Terraferma[END_REF], respectively.

Acknowledgments

I thank colleagues Isabella Di Lenardo and Olivier Delang for sharing the transportation network of Venice, and their students for making it. I also acknowledge EPFL students Joachim De Jonghe, Nicolas Duthilleul and Théo Lamaire for their preliminary efforts in the project.


Janneke M Van Der Zwaan

Maarten Van Meersbergen

Antske Fokkens

Serge Ter Braake

Inger Leemans

Erika Kuijpers

Piek Vossen

Isa Maks

Storyteller: Visualizing Perspectives in Digital Humanities Projects

Keywords: Visualizations, Heterogeneous data, NLP, History, Storylines

Humanities scholars agree that the visualization of their data should bring order and insight, reveal patterns and provide leads for new research questions. However, simple two-dimensional visualizations are often too static and too generic to meet these needs. Visualization tools for the humanities should be able to deal with the observer dependency, heterogeneity, uncertainty and provenance of data and the complexity of humanities research questions. They should furthermore offer scholars the opportunity to interactively manipulate their data sets and queries. In this paper, we introduce Storyteller, an open source visualization tool designed to interactively explore complex data sets for the humanities. We present the tool, and demonstrate its applicability in three very different humanities projects.

Introduction

Visualizations in digital humanities often represent the results of complex algorithms running on 'big data' from the humanities domain. Humanities scholars agree that the visualization of their data is an essential instrument to communicate their research results and to evoke scholarly debates as well as public interest [START_REF] Novak | HistoGraph-A Visualization Tool for Collaborative Analysis of Networks from Historical Social Multimedia Collections[END_REF] [10] [START_REF] Jessop | Digital visualization as a scholarly activity[END_REF]. The disciplinary characteristics of both scholarly practices and data in the humanities, however, offer a challenge for visualization techniques. In terms of practice, the humanities have stringent requirements concerning the representation of data and their provenance as their data are usually not generated under controlled circumstances. Humanities scholars like to have direct access to their data, queries and results in order to manipulate them and discuss their interpretation and also provide this to other users. Because of the heterogeneity of humanities data, and the exploratory character of humanities research questions, a limited corpus of texts can already generate an extensive amount of complex data [START_REF] Bod | Who's afraid of Patterns? The Particular versus the Universal and the Meaning of Humanities 3.0[END_REF].

In this paper, we address these challenges and present Storyteller, a visualization tool that helps to analyze complex, multilayered data. The tool allows users to interactively explore the data by adjusting the queries. In addition, Storyteller takes provenance into account by allowing users to view the data in the original context of their source. We have used Storyteller to visualize data from three different digital humanities projects. The first project is 'NewsReader' 4 which automatically detects events in news in terms of what happened, who is involved, and where and when it happened. In addition, events are aggregated into storylines to provide explanatory structures. The second project is 'BiographyNet'. 5This project involves the representation of biographies of prominent figures in Dutch history. The third project is Embodied Emotions. 6 The goal of this project is to track changes over time in the relationship between emotions and the parts of the body that are involved in emotional experience and expression. While the data of these three projects are very different, we demonstrate that Storyteller provides a new visualization technique that offers enhanced insights for each of these projects.

This paper is organized as follows. Section 2 provides a general introduction to the specific challenges humanities research sets for visualization of digital research. In Section 3, we present the Storyteller tool. The three different use cases are discussed in Section 4. Section 5 presents our concluding remarks.

Humanities data and visualizations

Over the last decade, various scholars have stressed the necessity for digital humanities to develop its own visualizations that specifically cater for the needs of humanities projects. In a seminal article from 2011, Johanna Drucker stated that adaptations of visualization techniques from the natural and social sciences do not meet the needs of humanities scholars, because they simplify research data and inherently assume knowledge to be observer-independent, certain and factual. Drucker stresses that, as opposed to most scientific research where data is regarded as given, most humanities data should in fact be read as 'capta': selected and constructed [START_REF] Drucker | Humanities approaches to graphical display[END_REF]. This implies that data visualizations should always provide contextualization through several layers of information. Humanities scholars therefore face problems with current data visualization techniques on various levels:

Multiple entities over multiple dimensions

Phenomena in the world of humanities research "do not lend themselves to representation within bounded, carefully delimited parameters" [4, p.247]. Single value systems are often too reductive to fit humanities requirements. Humanities research typically aims to interrelate multiple entities. Scholars will try, for instance, to map multiple events, investigate locations, and participants to these events, and plot them over time. Humanities visualizations should be able to interrelate these entities and plot them over third (space) and fourth (time) dimensions.

Valuation -interrelation

Entities and events may vary in value or weight and these in turn may differ depending on the research question. Visualizations should be able to reflect these differences. This can be done on various levels, for instance, by assessing the sentiment events generate, the number of mentions they get or by observing co-reference: is a single event mentioned in multiple sources? 3. Provenance Humanities scholars have high standards for the accountability of the provenance of data: much of this data consist of original (textual) material that needs critical consideration, weighing and positioning, in order to validate the relevance of the presented results [START_REF] Ockeloen | BiographyNet: Managing provenance at multiple levels and from different perspectives[END_REF]. Visualizations should therefore represent data provenance. Often, this entails presenting text in visualizations, instead of just quantitative data. 4. User dependency and perspectives Humanities scholars stress the fact that visualizations are not endpoints in the research cycle (a static, graphic presentation of the results), but one of the many steps in the hermeneutic cycle that can help to interpret the data, leading up to a next phase of research [START_REF] Jessop | Digital visualization as a scholarly activity[END_REF]. Furthermore, in humanities research "facts" are often contested. Visualizations should therefore be able to map multiple perspectives on the same topic or the same event. Instead of pretending to present final results, humanities visualizations should account for the uncertain and interpretative elements inherent in the data representation. Visualizations must offer researchers the possibility of manipulating the selection of data or the queries that address them in order to try and analyze different perspectives [3, p.20:51 ].

Visualizations for humanities research should be able to display the inherent ambiguity and complexity of 'capta', while building the co-dependent relation between observer and research data into an interactive, interpretative visualization model. Storyteller takes all these facets into account in an attempt to provide a visualization that brings new insights in humanities data.

Storyteller

Storyteller visualizes events in humanities data sets as structured stories, as defined in [START_REF] Vossen | Storylines for structuring massive streams of news[END_REF]. Following van den Akker et al., the tool shows interlinked actorcentric and event-centric stories that are extracted from text [START_REF] Van Den Akker | Digital hermeneutics: Agora and the online understanding of cultural heritage[END_REF]. The properties of the data determine what are actors (participants) and events. In this section, we explain the visualizations in general terms. Section 4 discusses the data setspecific uses.

Figure 1 shows a mock-up of Storyteller. 7 The tool visualizes connections between events that happen over time and participants in these events. Events are divided into groups, based on data set-specific properties. Each event is associated with a date and a climax score that indicates the importance of the event. The visualization consists of three linked views.

The first view consists of a horizontal bar chart and a co-participation graph. The bar chart lists all participants in the data. The length of the bars correspond to the number of times a participant is mentioned in the source text(s). The co-participation graph shows events as nodes on a timeline. Participants are represented by lines. If multiple participants participate in the same event, their lines intersect at the node representing this event. Hovering the mouse cursor over an event shows further details. The second view consists of a horizontal bar chart and two time-based plots. The horizontal bar chart lists the groups that occur in the data set. The length of the bars indicate the number of events in the group. For each group, the top most plot displays a sequence of time-ordered events (approximating a storyline). The size and color of the bubble representing an event is based on the importance of the event which is represented by its climax score. Again, hovering the mouse cursor over an event shows more information. The second time-based plot is a scatter plot that displays the climax score of individual events. Events from the same group are represented by the same icon. In this graph, the user can select events by dragging the mouse cursor over them.

Storyteller Demo

The third view addresses the provenance of the data visualized in the other two views. It displays a table that contains the "raw" data, allowing the user to cross-reference events, participants, and groups with the original sources.

To facilitate visual exploration of the data, graphs in Storyteller are dynamic and interactive. The user can filter or select data by clicking components of the graphs or by dragging the mouse cursor. Filters activated in one view are dynamically applied to the other views. Filters in one view are applied in succession, each time reducing the amount of data on the screen. This allows the user to drill-down into the data set, gaining knowledge of its composition in the process. Every filter that is applied to the data can be removed independently from the other filters.

Storyteller is open source software, built to be as generic and reusable as possible. 8 It displays data in a JSON format, specified in the documentation. This open outfit allows anyone to visualize their data, and to modify the application to their needs.

Visualizing the Data

Storyteller was used to visualize data sets from three different projects. In this section, we discuss the projects, the data sets, the data set-specific mappings to Storyteller concepts (i.e., events, participants, groups, climax score), and how the visualization contributes to stimulating insight into the data. The three projects are NewsReader (4.1), BiographyNet (4.2), and Embodied Emotions (4.3). In Section 4.4, we summarize the differences between the three data sets.

Newsreader

NewsReader aims to identify what happened to whom, when and where in large amounts of news [START_REF] Vossen | Newsreader: How semantic web helps natural language processing helps semantic web[END_REF]. NewsReader developed NLP pipelines that identify events, their participants, time expressions and relations between them in English, Spanish, Italian and Dutch text. Using this extracted information, documents which mention the same event can be identified and a single representation of this event can be provided. This leads to deduplication of redundant information and aggregation of information in cases where documents provide complementary information on the event. Each event representation is linked to the places where it was mentioned in text. This link allows comparing the different perspectives various sources provided on a specific event.

The data is represented in RDF, using the Simple Event Model ( [START_REF] Van Hage | Design and use of the simple event model (sem)[END_REF], SEM) to model events, their participants, location and time. The extracted events form so-called Event-Centric Knowledge Graphs [START_REF] Rospocher | Building event-centric knowledge graphs from news[END_REF]. These graphs provide the means to investigate, for instance, who was involved in a specific event, what else did this person or company do, and who does this person interact with, etc. These are exactly the kinds of stories Storyteller was designed to visualize, using both actor-centric and event-centric representations.

The visualization we implemented displays the outcome of this pipeline. The events in the NewsReader Storyteller are event instances plotted on the lines of the participants involved. Participants are entities, e.g., a person such as Steve Jobs, or a company like Apple Inc. If two participants took part in the same event, their lines cross at the event intersection. Figure 2 shows that, according to news articles from 2003 to 2009, Apple Inc. participated in events together with, for example, the EU, Steve Jobs, and Wallmart. In this context, the coparticipation graph allows the user to discover patterns in interaction: who is interacting with whom? Who else are they interacting with? Figure 3 shows the second view of the NewsReader visualization. It displays events that are connected in storylines: each event that is part of the same story is represented in the same row. Events that are mentioned in a topical relation and involve the same participants are considered to be part of a story. In Storyteller concepts, a group is a story. The groups are ordered based on the highest occurring climax score in the story. This score is based on the number of times an event is mentioned and the place in the article where it is mentioned. As defined in [START_REF] Vossen | Storylines for structuring massive streams of news[END_REF], events with the highest climax score represent critical turning points around which stories unfold. Preceding events lead up to the climax and following events resolve it. In Vossen et al. [START_REF] Vossen | Storylines for structuring massive streams of news[END_REF], stories are constructed by connecting events to climax events using bridging relations. The view below the storyline view places all events on the Y-axis based on their climax score. The color and shape of the events indicate the story the event belongs to. This visualization provides insight into how stories work up to their climax.

When taking the different levels of visualization together, users can detect patterns in the behavior of certain participants by looking at interactions, the individual events and stories over longer stretches of time. For instance, does a specific company tend to have long-term interactions with business partners or do their dealings tend to remain limited to few events in a short period of time? What happens to companies when a specific CEO joins the company? Do they recover from a crisis?

BiographyNet

The BiographyNet project enriches the metadata from the Biography Portal of the Netherlands,9 by running the full texts of circa 140,000 short biographies through an NLP pipeline. Previously missing structured data on topics like parents and education are automatically mined from the text, providing new leads and computerized analyses. A visualization tailored to BiographyNet's specific needs is now under development, but the BiographyNet data also serves as a good use case here to see if Storyteller can cope with this data as well.

For BiographyNet, the participant in Storyteller is a person, usually the biographee, about whom information is provided. The event is a particular thing that happened to this individual at a certain point (or period) in time. So if BiographyNet states that the Humanist philosopher Erasmus was born in 1469, the participant is Erasmus and the event is 'born in 1469'. The group this event belongs to is 'dates of birth'. The climax score is the overall number of mentions of a certain event. For this data, that boils down to the number of people from a group that were involved in the same kind of event in the same year. If in one group of people the event 'born in The Hague' occurs frequently, it will get a high climax score because it is the event that binds most people. This will allow for an easy recognition of patterns: if in a group of 300 women from the period 1950-2000 the events 'born in Amsterdam' and 'studied in Leiden' get high climax scores, than we have singled out a potentially important pattern, a distinguishing feature, for this group, which we can easily compare to the climax scores for any other groups.

The data set currently visualized in the BiographyNet Storyteller consists of important events in the lives of 25 women, 24 of whom died between 1940 and 1945, and one who died in 1949. 10 In addition to dates of birth, death and marriage, we visualize events that can tell us something about their 'claim to fame': 'publish', 'organize', 'found', 'paint', 'study', etc. Figure 4 shows the co-participation graph of this data set. In accordance with how the data was selected, the event(s) most co-participated in is 'death'. Figure 5 shows the second view. The large green circles in the scatter plot show again that 'death' is the most important event. The current visualization only maps events to participants and time, but other aspects such as location can easily be added. For future work it will be a challenge to visualize uncertainty when the year in which an event happened is not known or uncertain. For example, Eramsus was born circa 1469, but the exact year is unknown. For other cases, a date or year could be missing completely and sometimes there is a period in which something happened -e.g., a person studies Law for several years; a person had a daughter at the end of the eighteenth century (see also [START_REF] Stokes | The Problem of Digital Dating: A Model for Uncertainty in Medieval Documents[END_REF] [START_REF] Stokes | The Problem of Digital Dating: A Model for Uncertainty in Medieval Documents[END_REF]).

Embodied Emotions

The goal of the Embodied Emotions project was to investigate the relationship between emotional expressions and body parts in Early Modern Dutch theater texts [START_REF] Van Der Zwaan | HEEM, a Complex Model for Mining Emotions in Historical Text[END_REF][START_REF] Leemans | Mining Embodied Emotions: a Comparative Analysis of Sentiment and Emotion in Dutch Texts[END_REF]. The main focus was on tracking changes in the embodiment of emotional expressions over time. To this end, a Historical Embodied Emotions Model (HEEM), was developed. The model consists of two layers: concept types and emotion labels. The concept types, i.e., Emotion, Body part, and Bodily response, refer to the embodiment of emotions. In addition, there are 38 historically accurate emotion labels. A representative set of 29 Dutch theater texts from 1600-1830 was manually annotated with HEEM labels. The manual annotations were used to train text classifiers [START_REF] Van Der Zwaan | HEEM, a Complex Model for Mining Emotions in Historical Text[END_REF], which were subsequently applied to a bigger set of 279 theater texts [START_REF] Van Der Zwaan | Historic Embodied Emotions Model (HEEM) dataset[END_REF]. Body parts were further specified in an additional data processing step. First, all words marked with HEEM label 'Body part' were manually assigned a more specific body part label, e.g., Heart, or Head. The resulting mapping was applied to the bigger corpus; for each sentence that was assigned HEEM label 'Body part' and that contained words from the body part mapping, the corresponding body part label was assigned to the sentence as well.

A data set for Storyteller was generated from the manual annotations. This data consists of various, interrelated levels that could be visualized:

1. The expression of emotions in a singular theater text 2. The expression of emotions over time over a group of texts (e.g., divided by genre: comedy, tragedy, farce) 3. The bodily location of emotions in a singular theater text 4. The bodily location of emotions over time over a group of texts 5. The emotional qualities of body parts over time 6. Provenance of all the projections For the demo, we decided to focus on visualizing the relationship between emotions and body parts over time. In Storyteller concepts, events are used to refer to an emotion expressed in a single theater text (e.g., Love in Vondel's Lucifer ). A participant is a body part label (e.g., Heart). The groups are abstracted emotions (i.e., HEEM labels). The climax score was calculated by dividing the number of times an emotion occurs in a text by the number of sentences in the text. The date of a text is its year of publication.

The resulting visualization provides an environment where researchers can switch between events (emotions) and participants (body parts), and represent their interrelations over time. The co-participation graph enables researchers to explore what emotions are felt in which body parts, and what body parts are used to express specific emotions. Figure 6 shows the co-participation graph of Heart, which is the body part occurs most frequently in the data set. Another result that was found by interacting with the visualization is that anger can be expressed through the eyes, the tongue, the hands and the nerves. The timebased graphs in the second view of the visualization enables researchers to gather evidence for statements such as "the heart has become the most important seat for the expression of love since 1750", and "body parts like finger nails and hair were very emotional around 1600, but are 'neutralized' after 1700". Figure 7 shows the second view with the Embodied Emotions data set filtered on Heart. The column-like distribution of points in the graph indicate that the data set contains texts from certain years only. By filtering the data researchers can take into account domain knowledge about general developments over time, e.g., the fact that theater texts in general become less explicitly emotional around 1800. Filtering also allows researchers to focus on a "basic" set of emotions, by removing more "moral reflective" emotions, such as honor, shame, and feelings of guilt.

Summary

The three projects we described all have different data and use cases: direct interaction of participants through modeling specific events and their stories (NewsReader), similarities between people by representing the kind of events they are involved in and when (BiographyNet), and the historic development of how people related emotions and bodyparts (Embodied Emotions).

Table 1 lists the data set-specific mapping to events, participants, groups and climax score in each of the three data sets. 1. Events, participants, groups, and the climax score in the three projects.

Conclusions

Digital Humanities projects often aim at bringing order to large amounts of (semi-)structured texts, or heterogeneous data. In this context, visualizations are essential to provide humanities scholars with insight and to inspire future research. This paper presented Storyteller, a visualization tool that does just that. The applicability of the tool was demonstrated by discussing preliminary results from visualizing data from three different projects. One of the strengths of Storyteller is that participants, events, groups and climax scores can be used to refer to different things in different data sets, depending on the needs of the scholars who will use it. Access to the original data is provided to enable the user to check the findings and closely read the original sources whenever necessary. Storyteller's first two views reveal patterns that are hard to detect by close reading. The tool visualizes complex and heterogeneous data, which is by nature hard to understand. Using Storyteller also requires a proper understanding of how the tool works. We therefore aim to develop tutorials that help scholars to understand an use the tool. Generally, the humanities scholars that explored data using Storyteller were positive about its usability. For future work, a more formal usability study is required.

The third view provides insight into where information comes from by presenting the source text, but there are many more aspects to uncertainty and perspectives that are not yet addressed. The main focus of our future work will be on visualization of uncertainty, to cope with different perspectives, uncertain time periods and contested data.

FilterFig. 1 .

 1 Fig. 1. Mock-up of Storyteller.

Fig. 2 .

 2 Fig. 2. Apple Inc.'s co-participants in news articles from 2003 to 2009.

Fig. 3 .

 3 Fig. 3. Storylines containing participant Apple Inc.

Fig. 4 .

 4 Fig. 4. The co-participation graph of the BiographyNet Storyteller data set.

Fig. 5 .

 5 Fig. 5. The BiographyNet Storyteller data set in the second view.

Fig. 6 .

 6 Fig. 6. Co-participation graph of the Embodied Emotions data filtered on Heart.

Fig. 7 .

 7 Fig. 7. The second view of the Embodied Emotions data filtered on Heart.

Table

	Concept	NewsReader	BiographyNet	Embodied Emotions
	Event	Event (something happen-	Event type occurring in a	Emotion expressed in a sin-
		ing in the real or an as-	specific year (e.g. marriage	gle theater text (e.g., Love
		sumed world)	in 1910, death in 1943)	in Vondel's Lucifer )
	Participant	Entity (e.g., Apple Inc.,	A person	Body part (e.g., Heart)
		Steve Jobs)
	Group	Story linking events and	Event type (e.g. marriage,	Abstracted emotion (e.g.,
		participants	death)	Love)
	Climax score Prominence of event men-	Number of people involved	Number of times an emo-
		tions (number and location	in this type of event in a	tion is expressed divided by
		in articles)	given year	the number of sentences in
				the text

http://www.newsreader-project.eu/

http://www.biographynet.nl

https://www.esciencecenter.nl/project/from-sentiment-mining-to-miningembodied-emotions

For a better understanding of the Storyteller visualizations, the online demos can be found at http://nlesc.github.io/UncertaintyVisualization/ (News-Reader), http://nlesc.github.io/BiographyNet/ (BiographyNet), and http:// nlesc.github.io/EmbodiedEmotions/ (Embodied Emotions).

https://github.com/NLeSC/UncertaintyVisualization

http://www.biografischportaal.nl/en

This last woman was added for reasons of visibility: Storyteller's timeline ends at the last event and those of 1945 were hard to see without anything occurring afterwards.


Simon Donig
email: simon.donig@uni-passau.de

Maria Christoforaki

Siegfried Handschuh

Neoclassica -A Multilingual Domain Ontology

Keywords: Ontology, Neoclassica, Material Culture, Visual Culture, Multimodality, Furniture, Architecture, Classicism, Cultural Object Documentation, History, History of Art, Cultural Sociology, Digital Humanities

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Antiquarianism played an important role in the shaping of European modernity. As a "Pan-European movement" it helped to embed "the idea held by Europeans that Europe itself epitomised the highest level of culture and civilization", concludes for instance Allison Palmer. Yet, the outreach of this "highly complex movement [...] remarkably unified under the banner of classicism" [START_REF] Palmer | Historical Dictionary of Neoclassical Art and Architecture[END_REF]: 1, spanned the globe. The Neoclassic period from 1760 to 1860 engraved antiquity in such diverse fields as architecture, gardening, the visual and the applied arts, literature and even composition, creating a wealth of artefacts from the Russian Empire's Urals to newly independent Brazil and impacting on urbanity from New York to Athens. It experienced an exchange of highly specialized craftsmen across the boundaries of territories and languages, a spread of new techniques and technologies and last but not least the emergence of almost global markets for consumer goods such as furniture and bronzes.

The Neoclassica ontology as part of the broader Neoclassica research framework provides an innovative tool to address several aspects crucial to researching the global impact of an aesthetic movement.

Albeit having been conceived less than a year ago, and being developed in full-time since March 2016, the ontology has made considerable progress. Currently with a focus on furniture and architecture, accommodating already more than 760 concepts represented in at least three languages (currently chiefly English, German and French). More than 300 of these concepts represent artefacts from the realm of material culture, particularly a broad range of furniture and furnishings, while an almost equal number of concepts describes the components that make up such artefacts.

In section 2 we give a rough image of the Neoclassica research framework and how the ontology is situated within the framework. We will then go on to give an outline of the basic objectives and current state of development of the Neoclassica ontology in section 3. The structure of the ontology so far is described in section 4 and two examples covering multilinguality and the descriptive capabilities of the ontology are given in section 5. Finally, we give an outlook on the future directions of the whole system.

Neoclassica Framework

Epistemological considerations

For historians of art, historians, or cultural sociologists dealing with material culture (for an introduction to the research-concept: [START_REF] Colloredo-Mansfeld | Introduction -Matter Unbound[END_REF], [START_REF] Hicks | The Material-Cultural Turn: Event And Effect[END_REF]) has always been a troublesome issue for methodological reasons. Arguably the discipline best fitted with the farthest reaching tool-set to address aspects of material and visual culture has always been the history of art. (For reflections on the interrelations of history and the history of art with visuals see recently [START_REF] Schober | Verführung durch visuelle Kultur. Zur aktuellen Selbstbefragung von Geschichte und Kunstgeschichte[END_REF].)

Over the last 200 years historians of art have developed the concept of style to represent a set of features shaped according to a particular aesthetic order. Stylistic analysis together with that of iconography (the symbolic dimension inherent to visual representations) and combined with the technique of building corpora of artefacts and features for a long time have been driving forces of the discipline.

Style, however, is both, one of art history's most impressive heuristic tools for classification and the expression of particular historic conditions, cultural grammars and discursive conjunctions [START_REF] Hoppe | Stil als Dünne oder Dichte Beschreibung. Eine konstruktivistische Perspektive auf kunstbezogene Stilbeobachtungen unter Berücksichtigung der Bedeutungsdimension[END_REF]. Any process of classification will inadvertently be faced with selection and, as every scholar of the Humanities is well aware, selecting is a concious or unconscious process of meaning-making, e.g. by giving weight and value to a chosen trait or object over another. The select body can be considered as a canon, endowed with scholarly authority. The shape of such bodies, and the attributions made to them, can essentially be understood as time-bound efforts of meaning-making [START_REF] Assmann | Speichern oder Erinnern? Das kulturelle Gedächtnis zwischen Archiv und Kanon[END_REF].

Any scholarly effort dealing for instance with aesthetic programs has to be well aware of this duality, particularly when transferring traditional knowledge representations from the realm of culture to the Semantic Web [START_REF] Veltman | Towards a Semantic Web for Culture[END_REF]. A research framework based on these premises should in our eyes be aware of traditional orders of knowledge representation and deliver both, tools to analyse, question and understand them and provision new, more transparent tools of knowledge discovery.

The Proposed Framework

We propose a framework called Neoclassica which explores this duality by accommodating traditional knowledge representation as a formal ontology (top-down approach) and data-driven knowledge discovery (bottom-up approach), where cultural patterns will be identified by means of algorithms in statistical analysis and machine learning, having in particular the potential to uncover hitherto unknown patterns in the source data. The outcomes of both approaches will be united in a consistent, unified formal knowledge representation.

Partners from the GLAM will provide us with multimodal artefacts to be processed by the different framework components while in the end we hope to provide a research platform allowing different institutions and researchers to upload content that will be classified both automatically and with human assistance.

The Neoclassica-framework aims to be a useful tool for researchers to uncover and clarify among other things the spread of cultural patterns, better our understanding of cultural exchange processes, trace the emergence of new or hybridized aesthetic forms, or to deconstruct and analyse visual canons, to name but a few.

3 Why a New Domain Ontology?

Basic Objective

The Neoclassica-ontology offers a formalized encoding of domain-expert knowledge in order to make it accessible to complex research questions with the use of a computer. Thus it offers venues to make the domain knowledge commensurable with the bottom-up module. [START_REF] Doerr | Ontologies for Cultural Heritage[END_REF]: 464 argues that specialized terminology in cultural heritage research is chiefly used as an intellectual tool for hypothesis building. Our aspiration is that the Neoclassica ontology will eventually be used as such a tool, establishing a controlled vocabulary that not only is researchoriented and multilingual but also reflects the different shape of the represented concepts in different languages. So far we are not aware of any broadly accepted ontologies in this specific area. However a seizable amount of concepts we are interested in, is represented by various well established thesauri such as Getty's Arts and Architectural Thesaurus (AAT),2 the German Möbeltypologie,3 see also [START_REF] Böth | Möbel -eine Typologie für Museen und Sammlungen[END_REF]), the French architectural thesaurus Thésaurus de la désignation des oeuvres architecturales et des espaces aménagés, 4 and the furniture thesaurus Thesaurus des Objets Mobiliers [START_REF] Verdier | Thesaurus des objets mobiliers[END_REF], see aso [START_REF] Verdier | Système descriptif des objets mobiliers. Sous-direction des études, de la documentation et de l'inventaire[END_REF], or the Spanish Diccionario de Mobiliario,5 all of them essentially developed for the purposes of documenting cultural objects in the realm of museums and cultural conservation in general.

Under-and overspecification is an issue in this context because most established thesauri are conceived with a more general focus in mind. They hence lack a lot of domain-specific concepts or concepts of regional origin that we require, while on the other hand providing a lot of modern concepts that eventually might even taint the semantics of a concept if compared with a period example.

To give an example of the last case, the historic term pantry describes a dedicated space connected to the kitchen or dining room used to store both food and cooking utensils;6 nowadays pantry usually refers to a piece of cabinetry serving a similar function. While in the period in question a pantry might have been equipped with specialized pieces of furniture, no dedicated concept for these existed. As the term pantry slowly migrated from denoting a dedicated space to a broader type of case furniture, the ontology accommodates the term only to denote said space. Period furniture that nowadays often are referred to as pantries are in turn accommodated by other period terms such as credenza, sideboard or buffet bas.

To illustrate the effects of culturally induced underspecification let us provide another example. The ontology was to accommodate a type of artefact common on the continent, yet almost unknown to Great Britain: a piece of furniture with two distinct and visually separated units (for an illustration see figure 2 below) consisting of a small, recessed bookcase with a double door, like a dwarf bookcase, placed on top of a side-cabinet with a double door.

The AAT for instance does not accommodate such a concept but has other concepts that represent constructionally similar types of furniture such as secretary bookcases or chests-on-chests. The French language, however, offers the concept of a meuble à deux corps (literally: furniture with two bodies) to describe such artefacts (cf. étagère-bibliotheque in [START_REF] Verdier | Thesaurus des objets mobiliers[END_REF]: 158). The German Möbeltypologie, in turn, does also not offer a dedicated concept for this type of artefact, coming closest by defining an Aufsatzschrank or Armoire à deux corps as consisting of a cabinet unit often placed on top of another type of furniture like a chest of drawers, buffet or table.

We wanted the term to be more generic and have thus decided to accommodate a type of case furniture, called Meuble à deux corps, comprising artefacts showing constructional similarity, such as bookcase on chest, bookcase on sidecabinet, bureau bookcase (including cylinder-top bureau bookcase and secretary bookcase), chests on chests or double corner cupboard.

As our approach is focusing on a specific domain, we decided that the Neoclassica ontology should also reflect the historical semantics of concepts. For example the concept of a meuble à deux corps can be established from sources such as Charles Percier's 1812 treatise on interior decoration. Whenever possible we strive to provide concepts, labels and scope-notes based on extensive research in period sources such as Daniel Ramée's multilingual architectural dictionary, Antoine Quatremère de Quincy's historical dictionary of architecture, Henry Havard's dictionary of furniture and interior design or period publications from the field such as for instance Joseph Danhauser's and Thomas Sheraton's pattern-books or Thomas Hope's treatise on interior decoration. 7

CIDOC-CRM and Neoclassica

The Neoclassica-ontology is focused on driving research in the Humanities. So while it can be used to provide cultural object documentation, relies on well defined data and as a side-effect will certainly produce such data, our focus is currently on facilitating importing and accommodating existing data in the research framework.

Since CIDOC-CRM is an international standard its concepts can be used as a reference point both by us and our prospective partners. We thus try to develop our ontology to be (ideally) compatible with at least the reduced form of CIDOC-CRM as presented in the most recent iteration in [START_REF] Boeuf | Definition of the CIDOC Conceptual Reference Model[END_REF].

We are interested in expressing concepts like (E4 Period, E52 Time-Span and E53 Place) to represent for instance the Biedermeier Period and the relationships P7 took place at and P4 has time-span, and P10 falls within to represent that it took place in the countries of the German tongue (for instance the Grand-Duchy of Badenia, the Kingdom of Prussia, the Helvetic Republic, or the German-speaking parts of Cisleithania, etc.), Poland, Bohemia, Russia, or the Baltic region for different time spans, each. We are also interested in concepts such as E12 Production to denote the production-event and E39 Actor as well as its subclass E21 Person further to be specialized in our model as craftsman, architect, artist (painter etc.), maecenas or proprietor. Last but not least, concepts like E55 Type will enable us to accommodate thesauri about materials, techniques or iconography.

Current State

Currently the ontology is focused towards material artefacts and visual representations in a broad variety of media (historical photographs, paintings, prints etc.). At the present moment the ontology contains only hierarchies describing types of artefacts and their components as well as the is composed of relationship that will permit to describe the structure of the objects in terms of their parts. This was motivated by the need to combine the feature-extraction and object classification (cf. [START_REF] Bernmeitinger | Design and Evaluation of Multimodal Distributional Semantics for Automatic Style Recognition[END_REF]) approach (bottom-up) described in section 2 with the domain-knowledge representation approach (top-down) that we intend with ontology.

The Structure of the Neoclassica-ontology

The central concept of the ontology is currently the Artefact which is equivalent to the concept E22 Man-Made Object in the CIDOC CRM standard [START_REF] Boeuf | Definition of the CIDOC Conceptual Reference Model[END_REF]. It denotes all man-made objects. This artefact -for instance a piece of furniture or furnishing -can be described both as a concept and by its structure. Currently the basic concepts comprise five classes and a corresponding trove of subclasses.

They include components of artefacts (Component), what would traditionally be described as architecture (Built design artefact) and all movable equipment fitted to those built structures (Interior design artefact).

The Component class comprises subclasses that describe the structure of objects. One of them (Architectural element) describing the basic shapes that can be broken down only to geometrical forms (for instance ornaments such as various mouldings, or structural elements such as an arch). We defined the other (Architectural feature) as describing forms aggregated from architectural elements and / or other features. Features could comprise for instance a particular type of a bedpost, door or foot.

Furniture and furnishings are represented as subclasses of the class Interior design artefact. It is currently the most fleshed out class in the ontology, comprising furniture (264 concepts) and furnishings (68 concepts). The Architectural element class currently comprises 110 architectural elements, the Architectural feature class 167 features and the Structural component class 75 components.

Objects are related to their components via the is composed of property having as domain and range the class Artefact since in our subject area everything is composed only of man-made objects. One of the great challenges, an ontology that is both research oriented and multilingual will face, is the presence or absence of concepts in various languages.

A glaring example we encountered was the concept of a continental armoire and the British concept of a press. While an armoire can be described as an upright wardrobe usually with fixtures for hanging clothing and sometimes with shelving or drawers in the interior, the press denotes a sort of cupboard, where the clothes or linens are entirely put on shelving or in drawers.

While an armoire is relatively uncommon to the realm of the English tongue (as denoted by the use of a French loan word), it is at least not entirely alien. The press, however, is essentially an unknown concept in Germany and France.

This poses interesting domain problems and modelling issues, because the German term Schrank and the French armoire are usually used interchangeably and denote an identical concept, clothes and linen presses have no conceptual counter model on the continent, and even worse, the distinction of cupboard (with shelving) and wardrobe is only valuable in English, as both terms may be represented by Schrank and armoire in German or French respectively.

To address this we decided to represent concepts unknown to a language by specifying their name in their language of origin as a label. We introduced two generic classes (Container and its subclass Case furniture to accommodate all possible types of concepts. (The latter corresponding to the AAT term case furniture). To the case furniture class we added the sub-class Cabinet comprising in turn the classes Press and Armoire and their respective subclasses because we see them as functional (albeit not constructional) equivalent. Due to their relation we can treat Armoire and Schrank as labels for the same concept. We then went on to flesh out the Armoire class by adding essentially the functional equivalents to the two presses and any constructional variant.

This illustrates the challenge we face by having both a narrow and a wide perspective in our subject material. Narrow in the sense that we deal only with specific period artefacts (Neoclassical artefacts) and wide in the sense that we trace these artefacts in different places and chronological periods and in variations of Classical styles. We hence had to represent concepts that are either identical, overlapping or disjoint across multiple cultural domains in a synthetic approach.

Descriptive power

Figure 2 shows a German cherrywood Biedermeier bookcase on a side cabinet originally from the refectory of a monastery in the region of Oberschwaben, dating around 1827-1830. We have chosen the artefact to demonstrate some of the descriptive capabilities of Neoclassica and also the conceptual refinement of the ontology required to accommodate the artefact. (We concentrate only on the most important features below.) Besides providing means for classifying types of artefacts, the ontology allows to document their structure and components. In our example it provides the concept of heading-and bottom-section used to describe the specific object.

Both sections possess a double door, consisting of a pair of panel frames and a pair of panels one pair with glazing, a pair executed in wood. The bottom-section also has a top drawer. Each section sports furthermore a pair of half-columns consisting of a base and a Corinthian capital. The shaft of the column is convex shaped. Other features accommodated by the ontology include for instance the square tapering feet combining profiled cyma recta-and cyma reversa-shapes, escutcheons, shelve-boards in the heading section or the ebonized half-round staffs dividing the sections vertically.

Below we include some RDF snippets to illustrate how these concepts are realized in our system. This bookcase on side cabinet corresponds to the RDF class http://www.neoclassica.network/ontology#Bookcase_on_side_cabinet " Aufsatzbuffet " @de , " Bookcase on side cabinet " @en , " Buffet vitrine " @fr ; rdfs : comment " A side cabinet with a bookcase on top similar to a bookcase on chest . Alternative French terms include buffet bibliotheque ." @en .

The specific Biedermeier bookcase is an instance of this class and we describe its structure using the is composed of object property.

neoclassica : i s_compos ed_of rdf : type owl : ObjectP roperty ; rdfs : label " is composed of " @en ; rdfs : comment " This property describes the structure of an artefact in terms of its parts ." @en ; rdfs : domain neoclassica : Artefact ; rdfs : range neoclassica : Artefact .

The RDF code for the specific object is Further on its constituent parts are described (double doors, feet, shelves, panels, panel frames, etc. ) Each of these parts is further classified using the Component hierarchy (see figure 1).

For example the entablature of the heading section is an instance of class http://www.neoclassica.network/ontology#Entablature . neoclassica : Entablature rdf : type owl : Class ; rdfs : label " Entablement " @da , " Geb ä lk " @de , " Entablature " @en , " Entablement " @fr , " Trabeazione " @it , " Belkowanie " @pl , " Entablement " @se ; rdfs : subClassOf neoclassica : H o r i z o n t a l _ s u p p o r t ; rdfs : comment " A structure of moldings and bands resting on the capitals in the classical orders and supporting the pediment " @en . Further on we define the cornice both as an instance of class http://www.neoclassica.network/ontology#Cornice and the class http://www.neoclassica.network/ontology#Cavetto since the one refers to the structural feature and the other to the kind of moulding that the cornice is. The class definitions for Cornice and Cavetto are provided below.

neoclassica : Cornice rdf : type owl : Class ; rdfs : subClassOf neoclassica : Su p po rt _f e at ur e ; rdfs : label " Kranz " @de , " Cornice " @en , " Corniche " @fr , " Cornice " @ita ; rdfs : comment " Uppermost projecting element of the entablature ." @en .

neoclassica : Cavetto rdf : type owl : Class ; rdfs : subClassOf neoclassica : C o n c a v e _ m o u l d i n g ; rdfs : label " Hohlkehle " @de , " Cavetto " @en , " Cavet " @fr , " Guscio " @it ; rdfs : comment " A concave moulding with a cross section that approximates a quarter circle . Alternative terms in English comprise hollow , in German Hohlleiste and in Italian Trochilo ." @en .

Conclusion and outlook on future development

In this paper we presented the Neoclassica-ontology as part of the Neoclassica framework, the latter aiming to provide useful tools for researchers combining existing domain knowledge with the power of statistically analyzing multimodal data. The ontology so far includes concepts for representing mainly interior design artefacts and their components according to their form.

At the time of writing we strive to accommodate architecture and the built environment in the ontology. In the near future we will extend it to represent materials and techniques used in the creation of artefacts and to accommodate conceptual objects such as iconography, possibly by using open linked data to existing classification systems like Iconclass (http://iconclass.org/). Furthermore we would like to accommodate spacial information such as the placement of furniture in rooms and the arrangement of artefacts in groups.

We aspire to build a strong community around the Neoclassica platform that will contribute data to the Neoclassica research database, use Neoclassica as a research tool and disseminate the results. In this light we will also approach new institutional partners holding collections and intensify our collaboration with established partners such as the Kulturstiftung DessauWörlitz, a Unesco world-heritage site conserving an almost untouched ensemble of manor houses, gardens and furniture, most of them bearing Neoclassic traits, to bring a first prototype of the Neoclassica research-database into existence.

The Neoclassica ontology and the respective examples will be freely obtainable in the near future under a CC License from http://www.neoclassica.network.

7

  Danhauser, J.: Wiener Möbelformen, Wien (1801), Sheraton, T.: The cabinet dictionary. To which is added a supplementary treatise on geometrical lines, perspective, and painting in general. Smith, London (1803), Hope, T.: Household Furniture and Interior Decoration, executed from designs, Bensley, London (1807), Ramée, D.: Dictionnaire général des termes d'architecture en Français, Allemand, Anglais et Italien. C. Reinwald, Paris (1808); Percier, C.: Recueil de décorations intérieures. Didot, Paris (1812), Quatremère de Quincy, A.: Dictionnaire historique d'architecture. Librarie d'Adrien Le Clere et Cie., Paris (1832), Havard, H.: Dictionnaire de lameublement et de la décoration depuis le XIIIe siècle jusquà nos jours. Librairies-Imprimeries réunies, Paris (1887).

Fig. 1 .

 1 Fig. 1. The most important classes in the Neoclassica hierarchy. The number of concepts represented by each class is given in brackets

Fig. 2 .

 2 Fig. 2. A German Biedermeier Bookcase on Side Cabinet with Neoclassic features ca.1827-30

  neoclassica : B o o k c a s e _ o n _ s i d e _ c a b i n e t rdf : type owl : Class ; rdfs : subClassOf neoclassica : M e u b l e _ a _ d e u x _ c o r p s ; rdfs : label

  neoclassica : B i e d e r m e i e r _ b o o k c a s e rdf : type neoclassica : B o o k c a s e _ o n _ s i d e _ c a b i n e t , owl : Na m ed In di v id ua l ; rdfs : label " Biedermeier bookcase " @en ; rdfs : comment " German cherrywood Biedermeier bookcase on a side -cabinet originally from the refectory of a monastery in the region of Oberschwaben , dating around 1827 -1830. " @en ; neoclassica : i s_compo sed_of neoclassica : B i e d e r m e i e r _ b o o k c a s e _ b o t t o m _ s e c t i o n , neoclassica : B i e d e r m e i e r _ b o o k c a s e _ h e a d i n g _ s e c t i o n .

  neoclassica : B i e d e r m e i e r _ b o o k c a s e _ h e a d i n g _ s e c t i o n rdf : type neoclassica : He a di ng _s e ct io n , owl : Na m ed In di v id ua l ; neoclassica : i s_compo sed_of neoclassica : B B _ h e a d i n g _ s e c t i o n _ d o o r , neoclassica : B B _ h e a d i n g _ s e c t i o n _ e n t a b l a t u r e , neoclassica : B B _ h e a d i n g _ s e c t i o n _ f o o t 1 , neoclassica : B B _ h e a d i n g _ s e c t i o n _ f o o t 2 , neoclassica : B B _ h e a d i n g _ s e c t i o n _ f o o t 3 , neoclassica : B B _ h e a d i n g _ s e c t i o n _ f o o t 4 , neoclassica : B B _ h e a d i n g _ s e c t i o n _ l e f t _ c o l u m n , neoclassica : B B _ h e a d i n g _ s e c t i o n _ p l i n t h , neoclassica : B B _ h e a d i n g _ s e c t i o n _ r i g h t _ c o l u m n , neoclassica : B B _ h e a d i n g _ s e c t i o n _ s h e l v e 1 , neoclassica : B B _ h e a d i n g _ s e c t i o n _ s h e l v e 2 , neoclassica : B B _ h e a d i n g _ s e c t i o n _ s h e l v e 3 , neoclassica : B B _ h e a d i n g _ s e c t i o n _ s t a f f . neoclassica : B i e d e r m e i e r _ b o o k c a s e _ b o t t o m _ s e c t i o n rdf : type neoclassica : B ottom_se ction , neoclassica : Side_cabinet , owl : Na m ed In di v id ua l ; neoclassica : i s_compo sed_of neoclassica : B B _ b o t t o m _ s e c t i o n _ b e v e l , neoclassica : B B _ b o t

  neoclassica : B B _ h e a d i n g _ s e c t i o n _ e n t a b l a t u r e rdf : type neoclassica : Entablature , owl : Na m ed In di v id ua l ; neoclassica : i s_compo sed_of neoclassica : B B _ h e a d i n g _ s e c t i o n _ a r c h i t r a v e , neoclassica : B B _ h e a d i n g _ s e c t i o n _ c o r n i c e , neoclassica : B B _ h e a d i n g _ s e c t i o n _ f r i e z e .

  neoclassica : B B _ h e a d i n g _ s e c t i o n _ c o r n i c e rdf : type neoclassica : Cavetto , neoclassica : Cornice , owl : Na m ed In di v id ua l . neoclassica : B B _ h e a d i n g _ s e c t i o n _ f r i e z e rdf : type neoclassica : Frieze , owl : Na m ed In di v id ua l .

http://www.getty.edu/research/tools/vocabularies/aat/index.html

http://museum.zib.de/museumsvokabular/documents/systematik-moebel.pdf

http://data.culture.fr/thesaurus/page/ark:/67717/T96

http://tesauros.mecd.es/tesauros/tesauros

Cf. "Office", in: Ramée, D.: Dictionnaire général des termes d'architecture en Français, Allemand, Anglais et Italien. C. Reinwald, Paris (1808): 298, see also "Paneterie" idem: 308

 [START_REF] Assmann | Speichern oder Erinnern? Das kulturelle Gedächtnis zwischen Archiv und Kanon[END_REF]The work presented in this paper has been partly funded by the German Federal Ministry for Education and Research (BMBF) under grant no. 01UG1602-Passau Centre for eHumanities (PACE)