Zhijun Yan
email: yanzhijun@bit.edu.cn

Kai Liu

Meiming Xing

Tianmei Wang
email: wangtianmei@cufe.edu.cn

Baowen Sun
email: sunbaowen@cufe.edu.cn

A Study of Complication Identification Based on Weighted Association Rule Mining

Keywords: Weighted association rule, Complications, Data mining, Neural network

With the fast development of big data technology, data mining algorithms are widely used to process the medical data and support clinical decision-making. In this paper, a new method is proposed to mine the disease association rule and predict the possible complications. The concept of disease concurrent weight is proposed and Back Propagation (BP) neural network model is applied to calculate the disease concurrent weight. Adopting the weighted association rule mining algorithm, diseases complication association rule are derived, which can help to remind doctors about patients' potential complications. The empirical evaluation using hospital patients' medical information shows that the proposed method is more effective than two baseline methods.

Introduction

Many hospitals use the Electronic Health Records system (EHRs) to integrate different kinds of medical data [START_REF] Esfandiari | Knowledge discovery in medicine: Current issue and future trend[END_REF][START_REF] Shea | Accelerating the use of electronic health records in physician practices[END_REF]. The data mining technology is widely applied on the EHRs to support clinical decision, including drug supervision [START_REF] Coloma | Data mining methods to detect sentinel associations and their application to drug safety surveillance[END_REF], complication identification [START_REF] Murff | Automated identification of postoperative complications within an electronic medical record using natural language processing[END_REF], disease prediction [START_REF] Eshlaghy | Using three machine learning techniques for predicting breast cancer recurrence[END_REF], patient stratification [START_REF] Jensen | Mining electronic health records: towards better research applications and clinical care[END_REF] and other related directions [START_REF] Kwon | Actionable Gene Expression-Based Patient Stratification for Molecular Targeted Therapy in Hepatocellular Carcinoma[END_REF]. Among them, medical complication identification gets special attention. Complications refer to diseases caused in the process of another disease. It is difficult to discover the potential relationship between disease and its complication based on a small dataset. The emerging of big data analytic technology makes it feasible to identify the possible complications by mining the massive data in EHRs. Previous studies on complication identification normally focused on the specific disease and adopted the data mining algorithms to find some potential complications for the specific disease. However, these researches rarely consider the complications of different diseases together and ignore individual disease's features. Aiming to mine the potential complication relationship in the EHRs, this study firstly proposes the concurrent weight of diseases to depict the possibility that one disease will be a complication of other diseases. Based on the concurrent weight, we adopt the weighted association rule mining algorithm to mine potential complication relationship and predict the possible complications for clinical decision-making.

The rest of the paper is organized as follows. Section 2 introduces the related works on complication identification. Then, the proposed complication mining method is presented in Section 3, followed by the experiment results in Section 4. Finally, we discuss major research findings and future research of this study in Section 5.

Related Works

Complications represent the concurrence and association relationships among different diseases. They normally affect the patients seriously and cost much higher medical expenditure. In order to identify the possible complications for the disease, various data mining techniques are applied in complication identification. Roque et al. [START_REF] Roque | Using electronic patient records to discover disease correlations and stratify patient cohorts[END_REF] uses the text mining technology to analyze the electronic patient records of a Danish Psychiatric Hospital. By extracting phenotype information from electronic patient records, they analyze the disease co-occurrence relationship. Hanauer et al. [START_REF] Hanauer | Exploring clinical associations using 'omics' based enrichment analyses[END_REF] uses the Molecular Concept Map (MCM) algorithm to mine the electronic medical database and successfully find some interesting new diseases associations. Holmes et al. [START_REF] Holmes | Discovering disease associations by integrating electronic clinical data and medical literature[END_REF] use Application for Discovering Disease Associations using Multiple Sources (ADAMS) to identify the co-morbidities of the rare diseases Kaposi sarcoma, toxoplasmosis, and Kawasaki disease. By incorporating textual information from PubMed and Wikipedia, they find some rare or previously unreported associations.

As one of the most popular data mining algorithms, Association Rule Mining (ARM) is widely used in complication identification of a certain disease. Tai and Chiu [START_REF] Tai | Comorbidity study of ADHD: applying association rule mining (ARM) to National Health Insurance Database of Taiwan[END_REF] focuses on the complications identification of Attention Deficit/Hyperactivity Disorder (ADHD). By employing the association rule mining algorithm, they find that ADHD case group has apparently higher risk of comorbidity with psychiatric comorbidity than with other physical illnesses. Kim et al. [START_REF] Kim | Comorbidity study on type 2 diabetes mellitus using data mining[END_REF] analyze the complications of type 2 diabetes mellitus. Based on the medical data of 411,414 patients from 1996 to 2007, they develop the Dx Analyze tool to clean data and reveal associations of comorbidity. The results show that association rule mining was practical for complication studies. Shin et al. [START_REF] Shin | Diagnostic analysis of patients with essential hypertension using association rule mining[END_REF] use Aprior algorithm and Clementine program to analyze the data of 5,022 patients with essential hypertension. The strong associations between hypertension, non-insulin-dependent diabetes mellitus and cerebral infarction are mined. Moreover, based on a large amount of data, Wright et al. [START_REF] Wright | An automated technique for identifying associations between medications, laboratory results and problems[END_REF] also use the association rule mining method to find out the association among different diseases and laboratory results. The results show that association rule mining is a useful tool for identifying clinically accurate associations and has a better performance over other knowledge-based methods.

In summary, some prior studies make great efforts to identify complication relationship by adopting association rule mining technique. However, they don't consider the different roles of different diseases on the complication identification, which can improve the mining performance. At the same time, patients' medical history is critical information for disease diagnosis and should be incorporated in mining complication relationship.

Methods

In this study, we firstly define the concurrent weight to evaluate the possibility that a disease develops as a complication of other diseases. Then we adopt the Back Propagation (BP) neural network to derive the concurrent weight of diseases and identify the disease complication relationship based on the weighted association rule mining algorithm. Finally, the list of possible complications is recommended to support clinical decision-making.

The Concurrent Weight of Diseases

Prior medical experience is very helpful to predict the future health status and possible diseases. We assume that some diseases will appear as complication more frequent than others. A concurrent weight is proposed to represent the possibility that a disease becomes the complication of other diseases. The higher the disease's concurrent weight, the more likely it is the complication of certain diseases. Assume that the disease set is D, and every item in D is one disease. Each disease di also has a corresponding set Ci to describe its known complications. So the concurrent weight of the disease di can be defined as follows:

𝑊(𝑑 𝑖 ) = ∑ 𝑚 𝑖𝑗 𝑛 𝑗=1 𝑛 (1)
where w(di) is the concurrent weight of the disease di, n is the total number of diseases in the set D, and mij describes whether the disease di appears in the complication set of dj or not. When the disease di appears in the Cj, then mij is equal to 1, otherwise it is zero.

However, it is impossible to generate a complete complication list for each disease, and we can't directly obtain concurrent weights for all diseases by prior knowledge. Thus we firstly collect the complications of some traditional diseases, then apply some artificial intelligent algorithms to train the collected data and predict the whole set of concurrent weight. For the initial set of traditional diseases and its complications, we used the web crawler to download disease information from domestic professional medical website "Clove Garden" (http://www.dxy.cn/). Then 596 kinds of diseases and their occurrence frequency as complications are collected as the known complication knowledge.

BP Neural Network Model

The Back Propagation (BP) neural network is one of the most used forward neural networks [START_REF] Kuo | Automatic inspection system of LED chip using two-stages back-propagation neural network[END_REF]. We selected the three layer BP neural network to predict the concurrent weight of the diseases. It includes input, output and hidden layer.

Input Layer of the Model. First of all, we describe the disease as a three-dimension vector to characterize the properties of comorbid diseases. The three dimensions include the position of the disease in the International Classification of Disease (ICD) coding schema, the importance of the disease, and the appearing order in diagnosis.

The position of the disease in the International Classification of Disease (ICD) coding schema represents the location of the disease in the ICD list. The importance of the disease represents the impact of the disease on the patient's recovery process. For inpatients, the hospital will normally record all diseases they have and each disease will be assigned an importance value, which describes how it is important for patients' treatment. During the hospital stay, patients may have several diseases. These diseases will be recorded in the appearing order. By converting each disease to a vector, we used the 596 kinds of diseases and their weights as the input of the BP neural network model. At the same time, each dimension of the disease vector is normalized to makes sure that each value is ranged from 0 to 1.

Output Layer of the Model. The output layer represents the learning result of the BP neural network model. In this study, BP model is adopted to predict the disease concurrent weight. Thus the output layer is the disease concurrent weight.

We firstly discretize the concurrent weights of diseases. The discretization process can effectively avoid the hidden defects in the training dataset and make the model more stable. Moreover, the values of the concurrent weights of diseases are commonly very small considering the large number of diseases, thus we amplify the concurrent weights to get significant results. The discretization calculation formula of the concurrent weights is given as follows:

𝑓(𝑤) = { 0.
where f(w) is the discretization result of the concurrent weight w of a disease.

Then the number of neurons in output layer is set to 2, and the output value of each neuron cell is 0 or 1. Four output values of two neurons: (0,0), (0,1), (1,0) and (1,1) are mapped to four kinds of weights: 0.2, 0.4, 0.6 and 0.8 respectively. Thus we establish the direct connection between input layer and output layer.

Hidden Layer of the Model. The hidden layer of BP model is responsible for the information transformation. It can have one or several layers. As a single hidden layer BP neural network can approximate any nonlinear function with high precision [START_REF] Wang | Back propagation neural network with adaptive differential evolution algorithm for time series forecasting[END_REF], only one hidden layer is set in this study. The number of the neuron in the input and output layer is determined according to the input data and output data. For the hidden nodes number in the hidden layer, although many approaches have been proposed, no one works efficiently for all problems. The most common method is to determine the appropriate number of hidden nodes by experiments performance comparison. Thus we do experiments on a set of values as the number of the neuron in the hidden layer. The value that brings the least training time is the final number of hidden nodes.

3.3

The Weighted Association Rule Mining Differences among diseases are significant and different disease will have different roles in identifying complications. Thus the weighted association rule mining method [START_REF] Cai | Mining association rules with weighted items[END_REF] is adopted in this study. It attempts to provide a weight to individual items that are not based solely on item support. And thresholds of weighted support and confidence are also defined to measure the significance of the association rules mined.

Similar with the traditional association rule mining algorithm, the support of the item set X is denoted as support(X), if the number of items in X is n, the weighted support of X is:

Wsupport(X) = support(X) × ( 1 𝑛 × ∑ 𝑤 𝑗 𝑛 𝑗=1 ) (3)
The item set X is weighted frequent if the weighted support of X is greater than a predefined minimum weighted support threshold (wminsup):

Wsupport(X) ≥ 𝑤𝑚𝑖𝑛𝑠𝑢𝑝 (4)
The weighted support of a rule X→Y can be defined as:

Wsupport(X → Y) = support(X → Y) × ( 1 𝑚 × ∑ 𝑤 𝑗 𝑚 𝑖 𝑗 ∈(𝑋∪𝑌),𝑗=1 ) (5)
in which m is the total number of items in the set of (X∪Y). The weighted association rule mining algorithm will retrieve all rules X→Y, where X∪Y is weighted frequent and whose confidence is greater than or equal to a minimum confidence threshold [START_REF] Pears | Weighted association rule mining via a graph based connectivity model[END_REF].

In order to improve the algorithm efficiency, we adopt the frequent pattern (FP) tree structure to optimize the weighted association rule mining algorithm [START_REF] Li | Novel alarm correlation analysis system based on association rules mining in telecommunication networks[END_REF]. At first, by scanning transaction database and define the minimum weighted support threshold (wminsup), the weighted FP-tree is constructed with the weighted potential frequent 1-itemsets. Then the list of potential rules is mined by the weighted association mining approach.

Complication Prediction

The mined complication association rules among diseases provide valuable information for patient diagnosis. Based on patients' medical history, we can predict patients' possible complication by applying the mined complication rules.

When a patient has a new visit to the hospital and the doctor identifies his/her disease, the patient's main diseases in several latest visits are considered as a disease set, which includes patients' medical history information. The antecedents of mined complication association rules will be browsed to identify whether it contains all diseases in the set. If some rules are matched, the consequents will be displayed as the possible complications. If no rules have antecedents that contain all diseases in the set, the oldest diagnosis will be excluded. Suppose there have n diseases in the original set, the set will be n-1 diseases after the exclusion. Then the antecedents of mined complication association rules will be browsed again to find the matched rules. Iterate the above steps until some complication rules are matched or the set is empty. If the set is empty, no prediction will be given. Because only few rules include more than 6 diseases, we consider patients' 6 latest visits for prediction in the first step. For the matched rules, the possible complications are listed in the order of confidence of the complication association rules.

Evaluation

We have conducted an empirical evaluation of the proposed approach by using electronic medical records from a hospital in China and using the methods proposed by Wright et al. [START_REF] Wright | An automated technique for identifying associations between medications, laboratory results and problems[END_REF] and Hoque et al. [START_REF] Hoque | A New Approach on Rare Association Rule Mining[END_REF] as the benchmarks.

Data Preprocessing

The medical dataset we used is from a hospital in China. The dataset includes the information of inpatients and outpatients. Each patient gets a descriptive and longitudinal record to describe what happened during each visit. The record covers the information of diagnoses, lab test results, medications and procedures. The total number of records is about one million. Because we focus on the disease comorbidity relationship mining, we exclude the patients' data with only one visit to the hospital. Before mining complication association rules from the dataset, we firstly clean the data. First, the outpatient information is excluded. In the dataset, some medical information of outpatients is missing or incomplete. Moreover, the treatment outcome of outpatients is not recorded and the correctness of the diagnosis can't be evaluated. Second, some doctors may fail to diagnose patients' diseases and patients don't get better after the inpatient treatment. Thus we remove the inpatients information with unclear or uncured treatment results. Third, for those records that missed some important information, we mark them as invalid and exclude from the experiment.

After the data preprocessing, the final qualified diagnosis data includes 253,271 records, and it is related with 24,754 patients and 6,698 diseases.

Metric and Benchmarks

We used precision (P) as the metric to assess the effectiveness of the proposed approach. Specifically, precision is the fraction of complication predictions that are correct. Higher value of P indicates better performance. We use the diagnosis with the complication information as test dataset. The dataset includes 1,410 diagnosis records, which include the main disease and complication information. Based on the mined complication association rules, a list of possible complications for each patient can be generated. If the list includes the actual complications, we count that as a correct predication. Thus, the metric P is defined as:

𝑃 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑜𝑟𝑟𝑒𝑐𝑡𝑒𝑑 𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑖𝑜𝑛 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑡𝑒𝑠𝑡 𝑑𝑎𝑡𝑎 × 100% (6)
To evaluate the effectiveness of the proposed approach, the association rule mining (ARM) algorithm introduced by Wright et al. [START_REF] Wright | An automated technique for identifying associations between medications, laboratory results and problems[END_REF] and a rare association rule (RAR) mining approach proposed by Hoque et al. [START_REF] Hoque | A New Approach on Rare Association Rule Mining[END_REF] are chosen as benchmarks. Wright et al. applied the tradition association rule mining algorithms in the medical data and confirmed the validity of the association rule mining algorithms. Hoque et al. focused on the improved low-frequency association rule mining and the effectiveness of the generated rules has been validated over several real life datasets.

Data Analysis and Results

Derive the Concurrent Weight. In the process of deriving disease concurrent weight, there has one important parameter which influences the effect of the BP network. It is the number of neurons in the hidden layer of BP network. Therefore, we choose the training time of the BP network as the evaluation metric and compare the performances with different values of the number of neurons in the hidden layer. By comparing the training time, the number of neurons in the hidden layer is set to 7.

After determining the parameters of BP network, we predict the concurrent weight of the whole 6,698 diseases. The known weights of 596 diseases are inputted to train the model. The weight of other diseases is predicted through the trained model. Finally, the weight of 3,340 diseases is calculated. For those diseases whose weights failed to be predicted, we set their weight as 0.

Weighted Association Rules Mining. Based on the derived concurrent weight, we develop the weighted association rule mining approach by Java language and mine lots of interesting complication relationship. For the mined complication association rules, the number of items in rules is varying. Fig. 1 demonstrates the distribution of the number of items in mined rules. Obviously, most rules include 4 items, which accounts for 21% of the total association rules. The rules that include 3, 4 or 5 items are more than half of the total rules. Surprisingly, there has a little of rules that only include two items. We also apply the baseline methods to mine the complication association rules in the experiment dataset. The RAR method is trying the find the rare association rules and the number of generated rules is the biggest, i.e., 96,637. The ARM method derives 42,142 rules. Because some uncommon diseases are weighted, 83,029 rules are mined by the proposed method.

Performance Comparison. We compare three algorithms from two perspectives: processing time and accuracy. For processing time, three algorithms have significant differences on the time consumption for complication association mining. All tests were performed on a PC with 3.4 GHz Intel i7-4770 CPU and 12G RAM. The running time of RAR, RAM, and the proposed method are 262, 196, and 27 minutes, respectively. The predication accuracy of RAR, ARM and the proposed method are 45.3%, 38.5% and 80% respectively. The results show that the proposed method performs better than two baseline methods in processing time and accuracy.

As we mentioned before, the prediction step is to go through all mined complication rules and identify the consequent items of the matched rules as the predicted complications. And the prediction list includes several diseases. However, in the practical scenario, it is important to limit the list length, which can give more insightful suggestions for doctors. Thus we also compare the accuracy of three algorithms with different length of prediction list (Table 1). The results show that the proposed method is better than the baseline methods in three scenarios.

Conclusions

This paper focuses on mining disease complication association rules based on medical information. The concept of concurrent weight of diseases is proposed and defined.

And the BP neural network model is introduced to predict the weight for all related diseases. Then, we adopt the weighted association rule mining algorithm and FP-tree structure to retrieve the complication relationship among diseases. Based on the mined rules, the potential list of patients' complication can be generated. This research provides several research contributions. First, we propose a new index to evaluate the importance of different diseases on complication prediction. The defined index, i.e., concurrent weight, can describe the possibility that a disease become a complication of other diseases. Second, we introduce the BP network to predict the disease weight and design the appropriate input and output data. We define the disease information as a three dimension vector and the output of BP network is described by two neurons. By using the BP model, we can deduce a relatively complete disease knowledgebase. Third, we adopt the weighted association rule approach to mine the diseases association rules. To the best of our knowledge, it is the first time to apply the weighted association rule mining approach in the medical field. And some interesting association rules are retrieved.

There are several limitations of this study, which provide opportunities for future research. First of all, we only focus on the mining of relationship among diseases, which can't describe the complication relationship accurately. Second, due to the scope and complexity of this study, we do not invite medical professionals to evaluate mined complication association rules. Although the derived rules are surely helpful for doctors' decision-making in the real practice, some rules maybe not meaningful or even wrong from the view of clinical research. Third, this research only uses the predication accuracy as the metric.

Fig. 1 .

 1 Fig. 1. Number of items in complication rules

Table 1 .

 1 The accuracy comparison of three algorithms with different list length

	Methods		Accuracy
		length =10	length =20	Unlimited length
	The proposed method	32.4%	37.5%	80%
	RAM	13.1%	17.5%	38.5%
	RAR	14.9%	21.1%	45.3%

Acknowledgments. This paper was funded by National Natural Science Foundation of China (Grant No. 71272057, 71572013) and Beijing Natural Science Foundation (Grant No. 9152015).


José Silva

Roberto Pereira
email: rpereira@inf.ufpr.br

Samuel Bastos Buchdid

Emanuel Felipe Duarte
email: emanuel.duarte@ic.unicamp.br

Maria Baranauskas

José Valderlei Da Silva

Maria Cecília
email: cecilia@ic.unicamp.br

Calani Baranauskas

SAwD -Socially Aware Design: An Organizational Semiotics-Based CASE Tool to Support Early Design Activities

Keywords: Socially aware computing, Organizational Semiotics, Participatory design, Collaborative design tool

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

Introduction

In Software Engineering, Sommerville [START_REF] Sommerville | Software Engineering[END_REF] and Chung et al. [START_REF] Chung | Non-Functional Requirements in Software Engineering[END_REF] draw attention to "early requirements" or "organizational requirements", arguing that knowing the problem and envisaging solutions before creating a technical solution tend to avoid large future expenditures regarding human, time and financial resources. If the problem context is not well understood, a "bad" or neglected requirement can trigger additional problems. These additional problems may raise maintenance costs, restrict or affect the technology necessary to solve the problem, affect the project's scope and lead to changes in other requirements. Changes in other requirements, for instance, may impact later on stages of the project, sometimes causing a product rejection by some stakeholders or even rendering unfeasible the whole project.

Traditional software development models (e.g., cascade, iterative and incremental) tend to focus problem understanding on the identification of functional and nonfunctional requirements [START_REF] Sommerville | Software Engineering[END_REF]. This vision focuses on the solution of technical aspects and prevents a more comprehensive understanding of the problem being addressed, preventing those involved from having a wider sense-making of the problem and the proposed solution. A broader design view should include the point of view from different stakeholders, and pay attention to informal (e.g., culture, values, behavior patterns, preferences, etc.) and formal (e.g., laws, regulations, rules and policies) aspects related to these parties. However, IT professionals are rarely trained to deal with social, ethical and normative issues, and the mainstream methods, techniques and devices used do not favor the consideration of these aspects [START_REF] Baranauskas | Socially Aware Computing[END_REF].

There is a relevant amount of works and initiatives that either recognizes the need for a sociotechnical approach for Information and Communication Technology (ICT) design, or that favors the focus and attention to non-technical issues, especially in the Human-Computer Interaction (HCI) field. However, there is still a demand for a design process that meets the needs of a diverse audience to make design socially responsible. One initiative is Baranauskas' Semio-Participatory model, which we refer here as a Socially Aware Computing approach to design [START_REF] Baranauskas | Guiding the Process of Requirements Elicitation with a Semiotic Approach[END_REF][START_REF] Baranauskas | Social awareness in HCI[END_REF]. In such approach, Baranauskas articulates and extends ideas inspired by Organizational Semiotics (OS) [START_REF] Liu | Semiotics in Information Systems Engineering[END_REF] and Participatory Design (PD) [START_REF] Schuler | Participatory Design: Principles and Practices[END_REF], proposing a framework that considers a dialogue with design materials and, mainly, among individuals in their different roles (e.g., designer, developer, end-user, sponsor, other stakeholders) in order to conduct participatory work towards interactive system design. In Baranauskas' view, technical aspects of a system design depend on and affect the formal and informal aspects of organizations and society. As opposed to a technically centered perspective, the Socially Aware Computing support stakeholders in forming a wider sense-making of the problem and the proposed solution.

Baranauskas' approach has been applied in design contexts of high diversity in terms of users (e.g., skills, knowledge, age, gender, special needs, literacy, intentions, values, beliefs) and for creating different design products. For example: inclusive social networks [START_REF] Baranauskas | Guiding the Process of Requirements Elicitation with a Semiotic Approach[END_REF], applications; physical devices [START_REF] Miranda | Adjustable Interactive Rings for iDTV[END_REF]; interactive digital television [START_REF] Buchdid | Designing an IDTV Application in a Situated Scenario: A Participatory Approach Based on Patterns[END_REF][START_REF] Piccolo | Accessibility and Interactive TV: Design Recommendations for the Brazilian Scenario[END_REF]; systems for supporting problem solving and decision making in a manufacturing organization [START_REF] Baranauskas | Design -Indicating Through Signs[END_REF]; and accessible technologies [START_REF] Santana | Aprendendo sobre Acessibilidade e Construção de Websites para Todos[END_REF]. It has also been used as a theoretical and methodological ground for other design approaches and frameworks, such as [START_REF] Pereira | A value-oriented and culturally informed approach to the design of interactive systems[END_REF]. However, although practical results have demonstrated the contributions of her approach for a social responsible design in both academic and industrial settings, there is a demand for tools that support it and allow inexperienced designers to treat informal and formal aspects in their projects in a guided and practical manner. Such tools may support the dissemination of the approach, its usage by other professionals in different design contexts, as well as the dissemination of its background theories, such as Organizational Semiotics and its artifacts.

In this paper, we draw on the Socially Aware Computing approach as a theoretical and methodological background for the creation of an online system that supports the approach itself. The CASE tool, named Socially Aware Design (SAwD), is developed by experts in the approach and IT developers. Its current version offers a subset of artifacts used, created or adapted by Baranauskas' research group in its different projects, and was experimented in a case study by members of the InterHAD1 research group, from the Computing Institute of the State University of Campinas, to understand and organize the 17 th International Conference on Informatics and Semiotics in Organizations (ICISO '16). The results suggest there were benefits of using an online and collaborative CASE tool to support Baranauskas' approach for organizing the ICISO'16 conference. The current version of the CASE tool is available for free use on the Web.

The paper is organized as follows: Section 2 introduces the SAwD approach and its background. Section 3 describes the methods and practices applied to design the SAwD system. Section 4 presents the case study, and Section 5 discusses some findings from the CASE tool design and the case study. Finally, Section 6 presents our final considerations and directions for future work.

Background Theories

Hall [START_REF] Hall | The Silent Language[END_REF] introduces the notions of informal, formal, and technical levels in which humans operate and understand the world. The Organizational Semiotics (OS) theory proposes a structure nicknamed "Semiotic Onion" [START_REF] Stamper | Information in Business and Administrative Systems[END_REF] to explain how these levels coexist in the context of organizations and information systems, explaining that any technical artifact is embedded in a formal system that, in turn, is embedded in an informal one. The informal system represents organizational culture, customs, and values that are reflected as beliefs, habits, and individual behavior patterns of its members. The formal corresponds to aspects that are well established and accepted, becoming social conventions, norms, or laws. Finally, the technical, situated at the core of the onion, represents aspects that are so formalized that they can be technically approached and supported. The Socially Aware Computing [START_REF] Baranauskas | Using Patterns to Support the Design of Flexible User Interaction[END_REF] understands the design process as a movement that begins at society, crossing the informal and formal layers of signs to result in a technical system considering relevant aspects of the informal and formal layers of knowledge of the social group. Baranauskas [START_REF] Baranauskas | Socially Aware Computing[END_REF] argues that when a technical system is designed, it will impact on formal and informal layers alike, including the society and target audience. The Socially Aware Computing approach makes use of other artifacts and methods created and inspired by OS to bring to participatory discussions a structured and systemic view of the problem. This view involves knowledge layers (informal, formal and technical) and their interdependence, brought to discussion in order to propose a solution for a complex social system in which people and their behavior patterns are organized. For instance, the Problem Articulation Methods (PAM) from OS [START_REF] Kolkman | Problem Articulation Methodology[END_REF] provide practical artifacts (e.g., structures, guides, templates) that support the problem understanding from different perspectives. In Baranauskas' approach, the method attempts to bring out the complexity of the addressed problem and the solutions proposed among and for different stakeholders in a participatory way. Because problem clarification should be the first step in a project, the PAM can be used regardless of the design process, the technologies that will be used, and even the nature of the design.

The Stakeholders Identification Diagram (SID) and the Semiotic Framework (SF) are examples of PAM's artifacts. The SID [START_REF] Liu | Semiotics in Information Systems Engineering[END_REF] facilitates the identification of the ones direct or indirectly involved in a particular design process, allowing the identification of stakeholders according to five different categories (Operation, Contribution, Source, Market and Community) that represent different levels of involvement, interests, and expectations. The SF [START_REF] Stamper | Information in Business and Administrative Systems[END_REF], in turn, favors the identification and organization of requirements according to six different levels that represent different aspects of signs. The first three levels can be related to technological issues (the physical, empirical, and syntactic), and the other three levels can be related to aspects of human information functions (semantic, pragmatic and social world).

Baranauskas and colleagues have also proposed and adapted other artifacts to support problem clarification and prospection of design solutions. For instance, the Evaluation Frame (EF) [START_REF] Baranauskas | Guiding the Process of Requirements Elicitation with a Semiotic Approach[END_REF] is an artifact to favor anticipation and discussion of problems and solutions related to each stakeholder identified through the SID, contributing to the identification of requirements and issues that might impact the solution to be designed. Other examples are the Culturally Aware Requirements Framework, Value Identification Frame [START_REF] Pereira | Keeping Values in Mind-Artifacts for a Value-oriented and Culturally Informed Design[END_REF] and Value Pie [START_REF] Pereira | Value Pie: A Culturally Informed Conceptual Scheme for Understanding Values in Design[END_REF]. The SAwD CASE tool is intended to support the use of such artifacts in a collaborative and practical way.

SAwD: a CASE tool to Support the Socially Aware Computing

The SAwD2 CASE tool is a result of a design process inspired by Baranauskas' Socially Aware Computing [START_REF] Baranauskas | Guiding the Process of Requirements Elicitation with a Semiotic Approach[END_REF]. The activities were structured in three main steps: i) understanding the problem domain to identify general requirements; ii) proposing and developing the CASE tool; and iii) technical evaluations and improvements.

Problem Understanding: activities begun early 2010 with only three people (researchers), one of them an expert in Organizational Semiotics and Socially Aware Computing. Weekly meetings were held to discuss and brainstorm about the possibility of a set of tools to support the use of PAM artifacts. It was then decided to use PAM artifacts to understand PAM artifacts themselves, and how they could be useful as an online CASE tool that supports the process of problem understanding. The Stakeholder Identification Diagram, Evaluation Frame and Semiotic Framework were the 3 artifacts used to support this activity; they were available in a plug-in for the Sakai environment used in closed distance learning courses. The project was initially named WebPAM.

Solution proposal and development: Iteratively, the team evolved the problem understanding, specifying and prototyping a solution to support the collaborative and open use of PAM artifacts on the Web as part of design projects. The Brain Drawing participatory technique was used to generate proposals for the tool user interface.

After several iterations, a first formal specification of the CASE tool was developed, and four new members (undergraduate students) were added to the project to work in software engineering and development activities. Fig. 1 illustrates the UML use case and class diagrams, as well as one prototype developed in 2012 to achieve a usable digital version of the artifacts. Evaluation: The tool's first version, see Fig. 2, was evaluated by 24 Information Technology undergraduate students of the University Center of Maringá3 in Brazil (UNICESUMAR). The evaluation was conducted using the System Usability Scale (SUS) [START_REF] Brooke | SUS: a 'Quick and Dirty' Usability Scale[END_REF]. The students discussed a hypothetical problem by means of the CASE tool, and then evaluated it by answering a SUS questionnaire.

Considering that the SUS questionnaire scale ranges from 0 (worst possible score) to 4 (best possible score) mapped for Usability Goals [START_REF] Sharp | Interaction Design: Beyond Human-Computer Interaction[END_REF], the 2012 version of the CASE tool had a score between 2 and 3 for Effective (effective to use), Efficient (efficient to use), Utility (have good utility) and Learnable (easy to learn). Memorable (easy to remember how to use), in turn, had a score lower than 2. Even though the overall results are positive, the results indicated that the CASE tool could be improved in several aspects, including usability and accessibility ones. Based on the results from the first evaluation and on the artifacts used to clarify the problem, the team started improvement tasks focusing both usability and technical improvements. From a back-end perspective, the nature of the data processed (mostly unstructured data, such as texts and images) led to the adoption of the non-relational (noSQL) database MongoDB 4 . Also from a back-end perspective, the need for efficiency when dealing with a relatively large number of concurrent connections led to the adoption of the Node.js5 runtime, due to its event-driven, non-blocking I/O model. To improve the usability, it was decided to adopt the well-established and documented Material Design language from Google6 . Therefore, from a front-end perspective, it was decided to adopt Angular Material7 , which is a reference implementation of Google's Material Design Specification for the Angular.js 8framework, and that provides reusable, well tested and accessible UI components. Finally, to improve the data communication between back-end and front-end, it was decided to adopt the Socket.io9 library, which allows real-time bidirectional eventbased communication, making possible for users to collaborate remotely in real time during the use of OS artifacts. Fig. 3 shows an abstraction for the SAwD Software Architecture: the front-end (chat, people, description, artifacts) are linked to the backend (messages, artifacts data sharing) and communication between back-end and database.

The results from the problem clarification and the tool evaluation led to a change in the project's purpose. From a web tool that would support the open use of PAM's artifacts it was transformed in a tool for supporting problem understanding from a systemic and socially responsible perspective, i.e., Baranauskas' view

Tool Experimentation

The International Conference on Informatics and Semiotics in Organisations (ICISO), promoted by the International Federation for Information Processing (IFIP), is held annually to discuss new research outcomes, applications, challenges and trends in OS.

The first edition was held in 1995 in Twente, The Netherlands, and since then it has taken place in different countries (e.g., Brazil, Canada, China, France, United Kingdom). Over the years, the conferences covered research themes such as people and information systems; web of things; information and knowledge management in complex systems, and socially aware organisations and technologies: impact and challenges. In 2016, ICISO will be held for second time in Campinas, Brazil. This activity involved a group of 10 people with experience in using OS artifacts and in organizing conferences. the participants were experienced in both OS and the problem domain, this was considered an ideal scenario to evaluate the current version of the CASE tool in terms of possible conceptual problems, technical issues and overall usability. This scenario also highlights how the CASE tool can be used for a wide range of problem understanding contexts, not only the development of a technological product. Fig. 4 illustrates the beginning of the planning activities, in which the group uses the SID to list and map every stakeholder that is involved and may somehow affect/be affected by the conference. Participants identified and mapped stakeholders from different layers, for instance, while technical stakeholders (e.g., EasyChair) are placed in the onion's core, social ones (e.g., Audience) are placed in the outermost layer of the onion.

Fig. 4. SID for ICISO'16

Following, the participants used the EF to discuss how the conference might influence/affect or be influenced/affected by the different stakeholders identified through the SID. Fig. 5 illustrates the design choice for the digital version of the EF artifact developed for the CASE tool. Every stakeholder identified in the SID is automatically displayed in the EF to assure they will not be forgot when switching between the artifacts. In the EF, the participants discussed every stakeholder identified previously in the SID, raising possible problems regarding them, and then discussing ideas and solutions for these problems. holistic view of the project in a single document. The online CASE tool enables new possibilities to reach stakeholders and involve them in the process of problem understanding and solution proposal. Because the tool allows people to remotely join the discussion and collaborate, physical distance is no longer an issue when it comes to stakeholders being included in the process. In this sense, a broader stakeholder engagement contributes to a more comprehensive and socially aware design process.

In the CASE tool current version, the included artifacts allow the discussion of relevant questions related to culture and human values during problem understanding. These artifacts were evaluated through practical research projects and learning activities, and the real case study about the ICISO'16 organization, providing positive results regarding a socially aware design. Additionally, the use of the CASE tool can also increase awareness about the importance of the socially aware design approach, especially among designers, developers and researchers without experience with OS. Because some of the artifacts were used to clarify the design problem for the SAwD, it was also possible to see technical issues (e.g., the used database system and interface framework) and abstract requirements (e.g., collaboration, flexibility) that were identified since the early stages of design, and that could have been neglected/forgotten if stakeholders, their problems, ideas and needs have not been considered in an explicit way.

Finally, the use of the CASE tool allowed an understanding about how this new set of tools would affect its stakeholders and society, with focus on how each stakeholder can benefit from this tool.

Conclusion

Technology influences people's daily activities, which, in turn, are formally defined. Thus, the design of a solution goes through informal, formal and technical layers of signs. By using artifacts from OS it is possible to understand and discuss the social impacts of a proposed solution; therefore, the development team may be able to make informed decisions regarding stakeholders' culture and values. There was a need for tools to support this process of problem understanding and ideally, these tools should be available to every stakeholder, so that they could contribute to the understanding of the problem and be part of the development of a solution that affects positively everyone involved. The SAwD implements some PAM artifacts and allows a collective work for discussion and understanding of the problem, leading the group to build a solution that makes sense to all the involved ones. The Tool is available online, favoring participatory work, enabling designers to propose creative solutions and promoting a decision-making space with stakeholders. The tool is in its first increment with six artifacts, and some minor programming and usability problems have been reported during the case study. These problems are addressed and the tool is being gradually improved. For future work, new artifacts will be incorporated into the tool to support the SAwD approach, such as Pereira's [START_REF] Pereira | Value Pie: A Culturally Informed Conceptual Scheme for Understanding Values in Design[END_REF] Value Pie. These artifacts are relevant in the process of socially aware design and will be part of the SAwD CASE tool in a new deliverable.

Finally, the tool is experienced in Computer Science graduate and undergraduate disciplines, such as Software Engineering and HCI (Human Computer Interaction), at University of Campinas, Federal University of Technology -Paraná (UTFR) and Federal University of Paraná UFPR in 2016 first semester. Its usage will contribute to both the evaluation of the tool itself, and the dissemination of the OS artifacts and the Socially Aware Computing approach to design.

Fig. 1 .

 1 Fig. 1. UML diagrams and design proposals for the CASE tool.

Fig. 2 .

 2 Fig. 2. The CASE tool's first version named WebPAM.

  for design, in an open and collaborative way, regardless the nature of the problem and solution to be designed. The CASE tool was, then, renamed to Socially Aware Design (SAwD). During the following years, technologies were experienced and the first version of the SAwD CASE tool was developed. In August 2015, the CASE tool first version was made available online and is being experienced by the InterHAD research group since then.

Fig. 3 .

 3 Fig. 3. System Components for SAwD tools.

Fig. 5 .

 5 Fig. 5. Evaluation Frame for ICISO'16

http://www.nied.unicamp.br/interhad

www.nied.unicamp.br/dsc

http://www.unicesumar.edu.br

https://www.mongodb.org/

https://nodejs.org/

https://www.google.com/design/spec/material-design/

https://material.angularjs.org/

https://angularjs.org/

http://socket.io/

Acknowledgments. We thank the Brazilian Research Foundations CNPq (Grant #308618/2014-9) and CAPES and States Secretary of Education of Parana (SEED). The authors thank the SAwD design and case study participants for their collaboration. The opinions expressed in this work do not necessarily reflect those of the funding agencies.


Kwasi Dankwa
email: k.d.dankwa@pgr.reading.ac.uk

Keiichi Nakata
email: k.nakata@henley.ac.uk

Making Sense of Non-compliance: A Semiotic Approach

Keywords: Compliance, Norms, Semiotics, Non-compliance, Agents, Behaviour

Compliance is an important aspect of operational requirements, and is essential to have a system that allows for compliance to be monitored, managed and improved. However, why non-compliance occurs in organisations is not always well understood. This paper proposes that the semiotic approach can aid in making sense of non-compliance behaviour by analysis of the actions of the agents. In particular, the organisational containment analysis highlights the division between informal and formal treatment of compliance. It also indicates that the established norms which are as a result of rules, regulations, beliefs and other patterns can influence behaviour. The paper proposes that these norms and patterns constitute the culture and beliefs of the organisation and determines how the agents embrace rules and regulations. An example of analysing compliance using the semiotic approach is presented using a case study of non-compliance to the quality management system at NHS Blood and Transplant (NHSBT).

Introduction

Compliance is central to the operations of organisations and its relevance cannot be over emphasised. It is an important component that can influence the behaviour of agents [START_REF] Solomon | Detecting and understanding non-compliance with conservation rules[END_REF], and impact on output of the organisation. The need for compliance may be as means of ensuring safety of consumers, quality of products or as a legal requirement. It is seen as the means of ensuring conformance to a rule: such as a specification, policy, standard or law [START_REF] Silveira | Aiding Compliance Governance in Service-Based Business Processes[END_REF]. According to O'Neill [START_REF] O'neill | An action framework for compliance and governance[END_REF], compliance is initiated by three main steps. 'First the societal imposition of rules and regulations; second, the organisation's decision to abide by the regulation and defines internal responsibility; and third, the act of implementing and managing the regulatory processes within the organisation to address the societal requirements'. To allow for this, the standards and regulations are well defined and act as means of measurement or audit of deviation within the organisation. Thus compliance describes the efforts organisations go through to ensure that they are aware of and take steps to comply with relevant laws and regulations. According to Governatori [START_REF] Governatori | ICT Support for Regulatory Compliance of Business Processes[END_REF], regulatory compliance is the set of activities an organisation does to ensure that its core business does not violate relevant regulations which allows the organisation to thrive.

As a result of the increasing number of regulations to allow for operational transparency, organisations are increasingly adopting the use of consolidated and harmonised sets of compliance controls [START_REF] Silveira | Aiding Compliance Governance in Service-Based Business Processes[END_REF]. Furthermore, the culture within many organisations has been changed to essentially promote climate which fosters the attitude to compliance matters [START_REF] Jenkinson | Compliance Culture[END_REF]. However, although many organisations may have systems in place to control compliance, there are instances where compliance to regulatory standards are not met. This has been shown to be apparent across different sectors; aviation, nuclear industries, banking, processing, health and manufacturing [START_REF] Park | The operators' non-compliance behaviour to conduct emergency operating procedures -Comparing with the work experience and the complexity of procedural steps[END_REF][START_REF] Richard | Factors influencing non-compliance with ASU 2010-06 in the banking industry[END_REF]. Evidently, these failures indicate that the current systems to manage compliance are not working and there is the need for further investigation.

Background

The motivation for this research derives from cases of non-compliance to the Quality Management Systems (QMS) at NHS (National Health Service) Blood and Transplant (NHSBT). The NHSBT collects blood and organs from voluntary donors to meet the demands of patients. To support these activities, it is essential that work is done within an efficient and effective QMS. Although QMS is in place, there have been reported instances of non-compliances. Examples include: a) Failure to supply specially matched product with resultant delay in treatment; b) Failure to correctly label product leading to delay in treatment; and c) selection of wrong donor leading to delay in stem cell collection. These instances of non-compliance have been shown to occur across different departments and involves different staff grades within the organisation with their effects ranging from impact on treatment and reputational impact on the organisation. The non-compliances have been reported across the NHS. A 2014 report by the Medicines and Healthcare products Regulatory Agency (MHRA) indicated that the number of Serious Adverse Events (SAEs) reported across NHS shows an increase of 8% (705/766) from 2013 [START_REF] Birse | Blood Consultative Committee New Letter[END_REF]. The cases of non-compliance indicate that although organisations have systems in place to manage compliance, there are still reported failures. These have led to a number of research across sectors such as the health, manufacturing, banking, aviation, food etc., to improve compliance [START_REF] O'neill | An action framework for compliance and governance[END_REF][START_REF] Park | The operators' non-compliance behaviour to conduct emergency operating procedures -Comparing with the work experience and the complexity of procedural steps[END_REF][START_REF] Richard | Factors influencing non-compliance with ASU 2010-06 in the banking industry[END_REF]. Although there have been improvement, there are still some gaps in knowledge when it comes to understanding non-compliance behaviour. In view of this, the research reported in this paper seeks to address the following research problems:

 What are the reasons behind non-compliance within organisations?  How can compliance to rules, standards and regulations be improved within the organisation in light of understanding the reasons behind non-compliance?

The next section reviews existing researches related to compliance to ascertain the current understanding of (non)compliance behaviour.

Compliance Behaviour

The review of literature shows that compliance is an important component required for organisations to thrive. It is therefore not surprising that measuring the level of compliance has emerged as a key performance indicator. As such, organisations have developed compliance performance indicators to facilitate analysis of compliance activities and its enforcement trends [START_REF] Read | Using compliance data to improve marine protected area management[END_REF]. Importantly, compliance culture within organisations have been shown to be vital to meet regulatory requirements to address customer needs in the competitive global market. This led to strategic plans to improve compliance culture and to encourage staff to align their values with the values of the organisation. Understanding compliance culture across organisations is important to understand compliance behaviour.

Compliance Cultures

The culture within different organisations may differ depending on the sector and how they perceive compliance issues. According to Jenkinson [START_REF] Jenkinson | Compliance Culture[END_REF], a compliance culture is essentially the climate which fosters the attitude to compliance matters. Compliance culture within organisations can be grouped into three main types [START_REF] Jenkinson | Compliance Culture[END_REF] as non-compliance, anti-compliance and pro-compliance cultures. In non-compliance culture, compliance rules are frequently breached by the organisation with no recognition of the need for compliance. This is more accepting to increase profits [START_REF] Hirschauer | An analytical framework for a behavioural analysis of non-compliance in food supply chains[END_REF]. With anti-compliance, compliance is generally seen as a threat and is merely tolerated. There is high risk of breach as compliance is seen as a reactive approach to the standards. Finally, in the pro-compliance culture, the organisation is inherently compliant and all the activities are compliantly performed. This view of categorization of different types of compliance culture is also shared by [START_REF] Hillson | Understanding and Managing Risk Attitude[END_REF] who split organisations between those that view compliance and risk management as an opportunity for continuous improvement and those that simply see it as a tick box exercise to satisfy periodic audit requirements. This shows that the culture within the organisation can relate to the way the agents perceives the rules and regulations. This can be useful when assessing the compliance behaviour as the culture within the organisation may determine how they comply. There may therefore be a link between the compliance cultures of the compliance behaviour of the staff.

Compliance Culture across Different Sectors

Many international institutions and conventions share a common aim of establishing and strengthening authorities to deliver effective compliance programs and enforcement [START_REF] Read | Using compliance data to improve marine protected area management[END_REF]. Such institutions try to promote effective ways of ensuring essential compliance culture that strengthens the compliance levels within organisations. This makes understanding compliance across different sectors useful.

In conservation [START_REF] Solomon | Detecting and understanding non-compliance with conservation rules[END_REF], compliance is critical to the success of any conservation project, regardless of the scale of the conservation actions or the means of conservation governance. It is not different in the food supply chain as is critical to ensure safety of the supply chain [START_REF] Hirschauer | An analytical framework for a behavioural analysis of non-compliance in food supply chains[END_REF]. It is seen as a critical factor in the safety of products and services. Also, in the education sector, QMS for teaching and learning have been developed for the purpose of quality assurance for example to monitor theses of PhD students to ensure completion on time [START_REF] Daud | Compliance to thesis examination procedure in the ISO quality management system for teaching and learning[END_REF]. The health care sector is no exception as researches have been conducted from drug compliance to information governance of medical information. According to Cramer et al. [START_REF] Cramer | Medication compliance and persistence: terminology and definitions[END_REF], studies have demonstrated that inadequate compliance and non-persistence with prescribed medication regimens result in increased morbidity and mortality. These are not the only sectors that require compliance as many industries such as nuclear, aviation and chemical, see it as very important for the desired outcome to be achieved [START_REF] Park | The operators' non-compliance behaviour to conduct emergency operating procedures -Comparing with the work experience and the complexity of procedural steps[END_REF].

However, although there is enough evidence to demonstrate that organisations strive for compliance, there are still gaps in the literature in respect of systems and frameworks to assist organisations in managing compliance [START_REF] O'neill | An action framework for compliance and governance[END_REF]. This is supported by [START_REF] Shah | Towards changing healthcare workers' behaviour: a qualitative study exploring non-compliance through appraisals of infection prevention and control practices[END_REF] who indicated that there are still gaps between staff compliance behaviour to standards of practice. Moreover, despite many actions and systems, inadequate compliance is frequently observed [START_REF] Read | Using compliance data to improve marine protected area management[END_REF]. These systems and actions; Compliance Action Framework, Analytical Framework and ICT Approach as applied by [START_REF] O'neill | An action framework for compliance and governance[END_REF][START_REF] Governatori | ICT Support for Regulatory Compliance of Business Processes[END_REF][START_REF] Cramer | Medication compliance and persistence: terminology and definitions[END_REF] in dealing with compliance, have mainly focused on addressing the symptoms but fail to understand the reasons behind the non-compliances. There is therefore the need to have a system or approach that allows for the behaviour of the agents to be analysed to understand and make sense of the non-compliance behaviour. The semiotic approach which allows for the analysis of behaviour based on the interpretation of signs within the organisation and the norm analysis of the agents lends itself to the understanding of non-compliance behaviours. The next section analysis the semiotic approach and how it can be used to understand and to make sense of non-compliance behaviour.

Semiotic Analysis

Conceptual background

Semiotics is 'the study of signs', and is concerned with their creation, representation and interpretation. Peirce (1958) defined a sign 'as something which stands to somebody for something in some respect or capacity'. Peirce's concept of a sign involves three parts: the Representamen (the sign), the Object (which is signified by the Representamen) and the Interpretant (that links the Representamen to the Object).

Within the organisation, every setting and sign presents the potential for training, development and for relaying information between stakeholders. A significant but often overlooked resource is the everyday experience of interacting with the infrastructures (building, equipment, and procedures) and communication structures that are available within the organisation [START_REF] Shapiro | Structures That Teach : Using a Semiotic Framework to Study the Environmental Messages of Learning Settings[END_REF]. These structures represent cultural values and the beliefs of the organisation which influences the operations within the organisation. It is therefore useful to understand these elements and to make sense of them. According to [START_REF] Shapiro | Structures That Teach : Using a Semiotic Framework to Study the Environmental Messages of Learning Settings[END_REF], a semiotic interpretive approach allows for critique in the ways cultural structures help to understand the ideas and the values that binds the people within the organisation. Essentially, the semiotic approach can be applied in the analysis and understanding of non-compliance behaviour as it embraces culture.

Application of Organisational Containment Model

To understand non-compliance behaviour, an Organisational Semiotics (OS) perspective [START_REF] Liu | Semiotics in Information Systems Engineering[END_REF] is used. This allows for an organisation to be seen as an information system with interdependent links between the organisation, the business process and the IT system [START_REF] Liu | Semiotics in Information Systems Engineering[END_REF]. These links can be expressed as an organisational containment model [START_REF] Stamper | Language and computer in organised behaviour[END_REF] that models organisation as comprising three systemsinformal, formal and automated (technical)whereby the automated system is contained within the formal system which in turn is contained within the informal system. This means that changes in any of the systems may have impact in other systems. Typically the informal system is the organisation itself. Fig. 1 illustrates the organisational containment with the three systems and how they interact with each other.

Informal System Intentions and beliefs formed

Formal System Rules and procedures formulated Automated System Availability of IT Fig. 1. The Organisational Containment Model [START_REF] Stamper | Language and computer in organised behaviour[END_REF] The informal system is a sub-culture where meanings and beliefs are established and intentions confirmed. At this level, the cohesive relationship between individuals are built and commitments are formed. However, at the formal system, there is formation of rules and procedures and individuals are made to follow bureaucratic rules which is in contrast to the informal system. The automated system is part of the formal system which is automated, for example, by a computer-based system [START_REF] Liu | Semiotics in Information Systems Engineering[END_REF]. In the problem addressed in this paper, we focus on informal and formal systems as there is no automated system involved.

Because the organisation is seen as a social system in which people behave in a manner that conforms to certain norms, compliance analysis can be assessed using the organisational containment model. The norms may be as a result of rules, regulations, beliefs and other patterns which have been established over a period of time through practical experience [START_REF] Liu | Semiotics in Information Systems Engineering[END_REF]. They have been shown as the rules which determine how social organisms interact and controls their ability to perform actions [START_REF] Salter | Using Semantic Analysis and Norm Analysis to Model Organisations[END_REF]. They have the ability of directing, coordinating and controlling the actions of the agents. Norm has been described as a field of force that coerces the people in the community to think in a certain manner [START_REF] Stamper | Understanding the Roles of Signs and Norms in Organisations[END_REF]. Essentially, the agents within the organisation may act as a result of existing interactions between the systems and experience established over the years. By introducing the formal system, there is move towards automation of the system where the agents in the organisation work without understanding the meaning behind what they do. This is evident in NHSBT where there are rules and procedures as part of the QMS to guide the performance of task within the departments. This formal system replaces the meaning and the intention that existed at the informal system and this can lead to conflict between the two systems. This conflict can lead to staff detachment as they only efficiently perform their task due to the formal system but are not satisfied because of the decline in the meaning and commitment that existed in the informal system.

Shapiro [START_REF] Shapiro | Structures That Teach : Using a Semiotic Framework to Study the Environmental Messages of Learning Settings[END_REF] indicates that culture has two aspects: the known meanings and directions which members are trained to and the observed meanings which are offered and tested. In essence, the agent may follow a norm conforming action or normbreaking action although they have been trained and have knowledge of the rules and regulations. The agents may prefer to act in line with the norms in place to fit in due to the measure of patterns of behaviour set by the norms. This may be done depending on the prevailing situation at the time of the action. Consequently, an individual in a community who has learned the norms will be able to use the knowledge to guide their actions. However, the actions performed is invoked by different norms which may be irrelevant of the outcome. This is because norms selected are subjective and may not have predetermined connection to a particular outcome. In performing their task, agents may not think of the consequence of their actions as they invoke the norms they deem appropriate at the time. This may either be compliant or noncompliant behaviour to the procedures and rules that exist in the organisation. This analysis shows that the understanding of interaction between informal and formal systems is useful in making sense of non-compliance behaviour. The next section will analyse how analysing the norms can contribute to understanding of non-compliance behaviour.

5

Analysing Compliance through Norms

Culture of Compliance

For NHSBT to meet customer needs, performance of task in the departments requires a shared understanding of norms and culture among staff within the organisation. In semiotic terms, the interpretation of various signs that are used and exchanged among the staff is influenced by the experience, knowledge and the beliefs of the staff in the various departments. Although the culture within NHSBT is pro-compliance, there appears to be departmental differences when it comes to compliance with the rules and procedures. This is because there is sub-culture that exists in the department which tends to influence the behaviour of the staff. The established norms within the departments influences the way the staff in the departments perceive the rules and procedures. Review and discussion with the QA department about compliance to QMS revealed different non-compliances across different departments.

Let us analyse one of the cases at NHSBT where there was a failure to supply specially matched product. Although the staff received the correct order from the hospital, the wrong product was produced. This is because, in selecting the initial material, the staff failed to check that the correct material had been selected as per the procedure. Moreover, although there was requirement in the procedure to check the order against the selected material in the manufacturing department, this did not happen. There appeared to be an incorrect understanding and belief that existed between the staff which influenced the observed behaviour in this case. Consequently, the established meanings and beliefs in conflict with the formal system resulted in the non-compliant behaviour. The wrong product selected resulted in a conflict between the formal and informal system. The informal system, which tolerated the noncompliance behaviour, was considered as the established norm in the department which influenced the behaviour of the staff as evident in this non-compliant behaviour. The informal system which is the organisation itself contains the intentions, norms and beliefs which influences the behaviour of the agents.

Norm Analysis in Compliance

Norm analysis aids understanding of the agents' behaviour in the organisation. This helps to capture the details of norms enacted by the agents and authorities who are responsible for the norms and the triggers which cause the norm to come into effect. In the case above, the staff involved in dealing with the orders were aware of the procedures and rules in place but failed to comply due to established beliefs and norms. Five norms, namely, perceptual norms, cognitive norms, evaluative norms, behavioural norms and denotative norms [START_REF] Liu | Semiotics in Information Systems Engineering[END_REF], have been considered to control human behaviour and, in turn, organisational behaviour. The perceptual norms influence how people react to signals from their environment through their senses. Here, the norms and values are embedded in the physical structures which influences the behaviour of the staff in the department. When the order was received, the staff might have been selective in terms of what aspects of the order to be recognised, which may have influenced the behaviour of the staff. The cognitive norms enabled the staff to interpret what they perceived based on the beliefs and knowledge. The staff interpreted the order based on the belief and knowledge that existed which may have led to the non-compliance behaviour. Although there is established rules and procedures, the acquired knowledge and beliefs coerced each staff differently to interpret the procedures. As such compliance in the organisation may be different across departments depending on experience of staff. In the analysis, the Evaluative norms aid in explaining the beliefs, values and objectives in the departments within the organisation. This helped in explaining the behaviour of the staff due to the understanding of the relationship between the formal and informal system. The behavioural norms govern the behaviour of the staff within the departments. These behaviours are as a result of the norms that exist within the department and this influenced the non-compliant behaviour observed. The knowledge, beliefs, values and the objectives that has been established within the departments controlled the behaviour of the staff in performing their actions. Finally, the denotative norms direct the choices of signs for signifying. These are culture dependant and may influence performance of task by staff within the department. This may have influenced the choice of flow of the process between the staff that received the order and the staff that manufactured the product.

Evidently, the behaviour of the staff is impacted by these norms which influenced non-compliance behaviour. In applying this to the case above, the staff involved in the process used one or a combination of the norms to complete the task. The performance of the task was initiated by staff who have the responsibility to select the initial material. The staff may have perceived or analysed the process differently to the required procedure leading to the failure to capture the required information from the order. Subsequently, staff in the chain of process also interpreted the task based on the established knowledge and beliefs culminating in the issue of non-compliant product. This is because, in the organisation the responsibility is determined by the established common agreements or policies. This leads to formation of 'life cycle' of responsibility which determines the role of each staff in the process. Non-compliance at this level was as a result of combination of one or more factors in the 'life cycle' of responsibility between all the stakeholders. This was due to persistent failures on the part of all the stakeholders who failed to check the requirements as a result of established beliefs and commitments.

The appropriateness of the responsibility of staff is influenced by the established norms which can either lead to compliance or non-compliance. In this case, the initiator of the 'life cycle' of responsibility was perceived as being compliant, so the process was carried out by subsequent staff without questioning, leading to noncompliance. On the other hand, if there was indication that the actions of the initiator of the process was not in line with the established norms, subsequent staff may have challenged their action leading to compliant outcome. Despite staff awareness of the procedures and rules, the established norms influenced staff in non-compliance behaviour. Moreover, because there is reliance on the interpretation of the request, the outcome depends on the skill set, the knowledge and the beliefs. At each stage of the process, there is the tendency for one or more agents to make a non-compliant decision based on how they perceived or interpreted the sign. There is indication that the established norms and beliefs influenced the behaviour of staff and by using the semiotic approach we can make sense of the non-compliant behaviour.

Discussion

Suitability and Benefit of Semiotic Approach

The Semiotic approach allowed for consideration of all the sign structures that exist within the organisation to be analysed and the impact on staff behaviour to be noted. Using the organisational containment analysis, the discrepancies between the formal and informal processes can be ascertained. Essentially, by understanding the conflict between the formal and the informal systems, improved procedures and rules can be formulated to guide activities within the organisation. The analysis allowed for sequential process to be followed to make sense of the reasons behind noncompliance. This also allowed for analysis of the actions performed by the various agents within the responsibility 'life cycle' which can be useful in dealing with noncompliance behaviours.

Limitations of Semiotic Approach

Although the analysis allowed for the investigation and understanding of noncompliance behaviour, the subjective nature of the analysis makes it difficult to generalise. Also the number of case studies used in this review limits the generalisation of this paper. The interpretation of signs within the organisation may differ depending on the experience, education, knowledge, beliefs, etc. of the staff who are involved in the process. In the case analysed, although it was evident that staff failed to follow the procedure, it is difficult to generalise that all the staff in the department will not be compliant due to the subjective nature of application of norms. Moreover, the perception of one staff member may be different from others and as such the outcome of their interaction with the procedures may be different at any given time which makes generalisation of findings difficult and problematic. Furthermore, although the semiotic approach allows for sense to be made of noncompliance behaviour, to allow for validity of the studies other analytical lens may be useful in future work.

Conclusion

Compliance has been shown to be an important aspect of the operations in organisations. Based on the concepts in organisational semiotics, in this paper, failures of compliance to rules, regulations and procedures are attributed to failure by agents to appropriately interpret and invoke the norms when required. The use of semiotic analysis has indicated that the established norms and beliefs in the organisation influences the actions taken to complete the task as noted. Moreover, subcultures within the departments have been shown to play a role in compliance behaviour. Furthermore, the organisational containment analysis points to possible discrepancies between the informal and formal systems that exist within the organisation. This influences how agents comply with rules, procedures and regulations and can influence compliance behaviour. Moreover, the actions of the agent that initiates the process have been shown to influence application of task by subsequent staff and this can impact on compliance behaviour. By establishing a culture that supports staff for compliance, there is indication that the appropriate actions may be compliantly performed routinely. Semiotic approach can aid in making sense of non-compliance behaviour in organisations.

In future work, a further analysis of compliance culture and non-compliance behaviour will be applied to develop a framework for enhancing compliance and monitoring non-compliance in organisations.

Acknowledgments. The authors would like to thank the Quality Assurance Department at NHSBT for their cooperation in this research.


John Effah
email: jeffah@ug.edu.gh

Semiotic Analysis of E-Document as a Composite Digital Sign: The Case of E-Boarding Pass

Keywords: organizational semiotics, e-document, composite sign, digital sign, e-boarding pass

This study draws on organizational semiotics models to analyze edocument as a composite digital sign. E-documents are increasingly becoming important in contemporary digital world. Yet research specifically focusing on analyzing it as an important information systems component remains limited. Moreover, in organizational semiotics research, semantic relationships between signs, objects and intepretants have traditionally been viewed from a single triangle perspective. This study therefore seeks to analyze e-document as a composite digital sign from multiple triangle perspective, using e-boarding pass as an illustrative case.

Introduction

The term document generally refers to an identified collection of recorded information [START_REF] Sprague | Electronic Document Management: Challenges and Opportunities for Information Systems Managers[END_REF]. Document is physical when it is on paper or electronic when it is in digital format. An e-document is considered as a composite object because it can contain multiple elements in varied forms, including text, image and diagram. Moreover, each of the individual elements can be considered as an object in its own right.

Following the emergence of the printing press and subsequent diffusion of computers and printers, documents have increasingly become significant parts of organizations and society. Moreover, administrative and governance systems in modern organizations have resulted in increased volume of documents in daily routines [START_REF] Sarantinos | Document Workflow: Modelling and Issues for the Non-savvy[END_REF]. As Latham [START_REF] Latham | Experiencing documents[END_REF] points out, documents are found in almost every area of human lives.

Documents have traditionally been paper-based. However, the advent of information and communication technologies has created the opportunity for edocuments [START_REF] Liu | E-Document Management Based on Web Services and XML[END_REF] as digital objects. Compared to paper documents, e-documents are not only cheaper but also more flexible, remotely accessible and easily transferrable. As a result, organizations and society in general are increasingly migrating from paper to edocuments. Yet information systems research specifically focusing on e-document as object of analysis in its own right remains scanty. This study therefore draws on organizational semiotics to highlight e-document as an important information system component for analysis.

The rest of this paper is structured as follows. Section 2 reviews related works on e-documents. Section 3 discusses the semiotic triangle and the semiotic framework as theoretical models for the study. Section 4 uses the two models for the e-document analyses. Section 5 uses e-boarding pass to illustrate e-document as a composite digital sign. Section 6 concludes the paper and offers direction for future research.

2

Related Works

E-Documents

While physical documents are paper-based, the advent of computers and related networks such as the Internet has afforded the creation and use of e-documents [START_REF] Lund | Document, text and medium: concepts, theories and disciplines[END_REF][START_REF] Renear | Towards Identity Conditions for Digital Documents[END_REF] as a collection of binary digits [START_REF] Buckland | What Is a "Document[END_REF]. Paper documents are static and have limited media content. However, e-documents are dynamic and multi-media. Their varied contents and formats can include text, audio, video and animation [START_REF] Lund | Document, text and medium: concepts, theories and disciplines[END_REF][START_REF] Sprague | Electronic Document Management: Challenges and Opportunities for Information Systems Managers[END_REF]. With these attributes, e-document can be considered as a composite digital object [START_REF] Sprague | Electronic Document Management: Challenges and Opportunities for Information Systems Managers[END_REF].

E-Documents Analysis

Information system studies [e.g. 4, 6, 9] on e-documents have largely focused on standards for interoperability. E-document standards were traditionally proprietary and thus restricted interoperability. However, recent development of platform and application-independent standards promotes open exchange and interoperability [START_REF] Magee | What's in a WordTM? When One Electronic Document Format Standard is not Enough[END_REF].

The extensible mark-up language (XML) is an example of such open standards [START_REF] Renear | Towards Identity Conditions for Digital Documents[END_REF]. Unlike proprietary standards, XML promotes open document exchange and interoperability [START_REF] Liu | E-Document Management Based on Web Services and XML[END_REF]. Thus various attempts on e-document analysis have focused more on standardization [START_REF] Magee | What's in a WordTM? When One Electronic Document Format Standard is not Enough[END_REF], which in semiotic terms relates to syntax. Less research therefore exists on other human and technical dimensions of semiotics. This study draws on organizational semiotics for e-document analysis beyond syntax.

Organizational Semiotics

Semiotics concerns the study of signs. Sign itself refers to anything that stands to someone for something else in a given context [START_REF] Stamper | Organisational Semiotics: Informatics without the Computer?[END_REF][START_REF] Stamper | Understanding the Roles of Signs and Norms in Organisations -a Semiotic Approach to Information Systems Design[END_REF]. Organizational semiotics is a branch of semiotics that studies development and use of information systems in organizations [START_REF] Liu | Organisational Semiotics for Business Informatics[END_REF]. This study draws on its semiotic triangle and framework [START_REF] Stamper | Understanding the Roles of Signs and Norms in Organisations -a Semiotic Approach to Information Systems Design[END_REF] for the analysis of e-document as a composite digital sign.

E-Documents Analysis

From a triadic perspective, Peirce's version of semiotic triangle presents semantic relationship between a sign, its referenced object and interpretant [START_REF] Mingers | An Integrative Semiotic Framework for Information Systems: the Social, Personal and Material Worlds[END_REF]. The semiotic triangle helps to explain how signs are interpreted by humans in a given context. Figure 1 shows a generic view of the semiotic triangle and its triadic relationship.

Fig. 1. Semiotic Triangle [13]

As Fig. 1 shows, a sign stands not for itself but for something else; the referenced object. Interpretant is the sense made of the sign in relation to the object; the interpreter is the person who makes sense of the sign [START_REF] Liu | Organisational Semiotics for Business Informatics[END_REF][START_REF] Mingers | An Integrative Semiotic Framework for Information Systems: the Social, Personal and Material Worlds[END_REF]. The position of this paper is that a single triangular relationship may be sufficient for simple signs with just one referenced object and interpretant. However, composite signs with multiple referenced objects and interpretants/interpreters such as e-documents require multiple triangular relationships.

The Semiotic Framework

The semiotic framework [START_REF] Liu | Organisational Semiotics for Business Informatics[END_REF][START_REF] Stamper | Understanding the Roles of Signs and Norms in Organisations -a Semiotic Approach to Information Systems Design[END_REF] presents six levels of a sign: physical, empirical, syntactic, semantic, pragmatic and social effects, as shown in Fig. 2. The six levels are further divided into two categories: the technical platform and human information contexts. The technical platform comprises the first three levels, namely the physical, empirical and syntactic; the human information context comprises the remaining three: semantic, pragmatic and social effects. The physical level comprises the material properties and structure of a sign including its storage, communication and access media. For documents, the physical level refers to paper and its properties in the case of physical documents or binary digits and related properties in the case of e-documents. The empirical level concerns the technical attributes and quality measures of transmission and communication of signs. For physical documents, the empirical level deals with quality measures of postal and personal delivery systems; for an e-document, the empirical concerns quality attributes and measures of electronic communication media including e-mail and document exchange protocols. The syntax layer deals with the technical structure of a sign in terms of rules and standards for its composition.

For the human information functions, the semantic layer concerns the meaning of a sign. For a document, the semantic layer deals with its interpretation. The pragmatic layer refers to interpersonal communication and use of a sign in relation to intentions and behavior of senders and receivers as responsible agents. The pragmatic level can be used to analyze the intentions a sender attaches to a document and its content as well as the subsequent reaction of the receiver. Finally, the social level concerns the effects of norms that result from the use of signs, such as agreements, commitments and obligations. At this level, a document can serve as evidence of a contract or commitment to an action. This study employs the semiotic framework to analyze e-document as a composite digital sign.

Semiotic Analysis of E-Document

This study employs the semiotic triangle and the framework to analyze e-document as a composite digital sign. In this study, digital sign refers to any sign that is electronic and therefore based on binary digit format; composite sign is any sign that contains other signs.

Semiotic Triangle View of E-Document

The semiotic triangle is used to model e-document as a composite digital sign -a sign of signs. Fig. 3 illustrates the triangular relationships between an e-document as a sign and its multiple referenced objects and interpretants.

Fig. 3. Semiotic Triangle Composite signs

The figure shows that as a composite sign, an e-document can stand for multiple objects in relation to multiple interpretants. Moreover, while the e-document itself can be a sign, each of its components can also be a sign on its own. Traditionally, semantic analysis in organizational semiotics research has focused on signs with single objects and interpretants. However, the composite nature of e-document calls for a more complex triangular relationships.

Semiotic Framework View of E-Document

The semiotic framework provides a useful model for representing e-document as digital sign. Fig. 4 shows the semiotic framework view of e-document in terms of its technical platform and human/social context. The physical layer concerns binary digits as the base constituents of an e-document. It also includes the multi-media forms of e-documents including, text, image, audio, video and more. Other components of the physical layer include computer and network devices that provide the medium for the existence of e-document as a sign. Examples of such devices include desktop, mobile devices (mobile phones, PDAs, tablets and laptops), servers and telecommunication devices (modems, hubs and bridges) that support the display and communication of digital signs.

The empirical layer concerns quality attributes of e-document communication via computer displays and telecommunication devices. Examples of such empirical attributes include readability, clarity, brightness, size and software/hardware protocols that affect such qualities during display and communication of e-documents. The syntactic layer deals with rules, standards and conventions that govern the structural composition of e-document as a digital sign. For e-documents, such syntactical issues concern the natural language of composing the document, related application/platform standards as well as international, national and industry standards. An example of such standards is XML. Specific industries such as air transportation and international trade also have specified standards for specific documents just as some countries have also defined technical standards for specific documents.

Fig. 4. Semiotic Framework View of E-Document as a Digital Sign

The semantic layer deals with the meaning of an e-document in relation to a particular interpreter. Since a digital document can be multi-media, there could be multiple semantics of it at the same time given different interpretants/interpreters. The pragmatic layer deals with intention behind the communication of an e-document by a sender and intended effects on a receiver. It concerns the assessment of the effectiveness or otherwise of the intended purpose on the receiver of the e-document. As in the case of the semantic layer, an e-document communication from a sender to receivers can generate multiple pragmatic effects.

Finally, social effects refer to norms that result from using an e-document in a given context. Again, like the semantic and pragmatic layers, the social effects layer can also be multiple for a given e-document. As Fig. 5 shows, an e-document with a single technical platform can have multiple social contexts involving multiple human actors with varied forms of semantics, pragmatics and social effects.

Semiotic Analysis of E-Boarding Pass

Following the semiotic analysis at the generic level, this section provides an illustration of e-boarding pass as an exemplary composite digital sign. The issuing of e-boarding pass is increasingly becoming the norm in air transportation. Fig. 6 shows an excerpt of a sample e-boarding pass used for the illustration. While the technical level illustrate the physical composition of the e-boarding pass as a single unit, the human information context shows multiple forms of semantic, pragmatic and social effects attributes, given the involvement of multiple interpreters and referenced objects. The semantic layer deals with how each of the different interpreters makes sense of the e-boarding pass. For example the passenger, the ground airline staff and the flight attendants may each interpret the boarding pass differently.

The pragmatic layer concerns communication of the e-boarding pass from one actor to another. Within the boarding process, there can be multiple communication of the e-boarding pass, such as from the airline's server to the customer's mobile phone, the customer showing the e-boarding pass to ground staff and the customer showing it to a flight attendant. In each of these interactions, there could be counter communication from the receiver to the sender, thus reversing the communication direction. Hence, there could be several scenarios of pragmatic enactments. Similarly, there could be multiple scenarios of social effects depending on the variety user groups involved, including permission to travel, right to travel, right to sit on a particular seat etc.

Conclusion

This paper focused on organizational semiotic analysis of e-document as a composite digital sign. It used an extended version of the semiotic triangle and alternative conceptualization of the semiotic framework to analyse e-document as a composite digital sign and illustrated the analysis with an e-boarding pass case. The study contributes to organizational semiotic research in two ways. First, it extends the single triangle view of sign-object-interpretant relationship to a multiple triangle view for composite signs. The extended model can be used for analysis and modelling of information system components that share characteristics of component signs.

Second, the study offers alternative conceptualization of the semiotic framework to account for semiotic analysis of composite digital signs with single technical platform but multiple human contexts. Again, this reconceptualization can be used for organizational semiotics research on individual information technology components with varied human information contexts, given multiple stakeholders' interpretations, intentions and social effects. For practical contribution, the conceptualization of composite digital signs can be used by information systems analysts and designers to account for attributes of entities with different interpretations by varied user groups. Future research can focus on pragmatic analysis of e-document communication in networked organizational environments.

Fig. 2 .

 2 Fig.2. Generic semiotic framework, Adapted from[START_REF] Mingers | Guidelines for Conducting Semiotic Research in Information Systems[END_REF]

Fig. 5 .

 5 Fig. 5. Socio-technical semiotic framework for e-document as a composite digital sign

Fig. 6 .. 1 Semiotic

 61 Fig. 6. An excerpt of e-boarding pass

Fig. 7 .

 7 Fig. 7. Semiotic triangle view of e-boarding pass as a composite digital sign

Fig. 8 .

 8 Fig. 8. Semiotic Framework View of e-boarding pass