The Physics of Notations: Evidence-based principles for designing cognitively effective visual notations

Description:

Visual notations play a critical role in conceptual modelling, and have dominated the field from its beginning. Almost all conceptual modelling notations use diagrams as the primary basis for communicating and documenting requirements. In fact, a conceptual modelling technique method without a visual representation is almost unheard-of. Visual notations play a particularly important role in communicating with end users and customers, as diagrams are believed to convey information more effectively to nontechnical people than text. Visual notations play an important role in all engineering disciplines, but we lack scientific principles for designing them It is therefore surprising that so little research attention has been given to visual representation in conceptual modelling research. Evaluations and comparisons of conceptual modelling notations tend to be conducted based exclusively on their semantics, with issues of visual syntax rarely mentioned. Also, the design of visual notations remains largely ad hoc. Decisions about visual representation are typically made in a subjective way, without reference to theory or empirical evidence. Graphical conventions are defined without any explanation as to why they were chosen (design rationale). The majority of effort is spent designing and justifying the semantics of notations (what constructs to include and what they mean), with the design of visual syntax (how to visually represent these constructs) often an afterthought. While conceptual modelling now has mature methods for designing semantics of notations (e.g. ontological analysis, formal semantics), equivalent methods for visual syntax are notably absent. There is a lack of accepted principles for designing effective visual notations. As a result, in evaluating, comparing and constructing visual notations, we have little to go on but intuition and rule of thumb. We have neither theory nor a systematic body of empirical evidence to guide us.

The aim of this tutorial is to establish the foundation for a science of visual notation design, to help it progress from a craft (as it is currently practised) to a design discipline It defines a set of principles (summarised in the diagram below) for designing cognitively effective visual notations: ones that are optimised for human understanding and problem solving.

Short bio:

Daniel Moody is a Visiting Professor in the Department of Information Systems at the University of Twente (the Netherlands). He holds a PhD in Information Systems from the University of Melbourne, but his experience spans both research and practice. Daniel has held academic positions at universities in Australia, Norway, Spain, Czech Republic, Slovenia, Iceland and the Netherlands, has published over 100 scientific papers and chaired several international conferences. He has also held senior positions in major corporations and IT consulting firms. He has conducted consulting assignments in 12 different countries in a range of industries including banking, law enforcement, television broadcasting, pharmaceuticals, biotechnology, airline travel, emergency services, healthcare, education and forestry. He is the current President of the Australian Data Management Association (DAMA) and is listed in Who's Who in Science and Engineering.

Ontological Foundations for Conceptual Modeling with Applications

Description:

The main objective of this tutorial is to introduce researchers to the theory and practice of advanced conceptual modeling through the application of a new emerging discipline named Ontology Driven Conceptual Modeling. Conceptual Modeling is a discipline of great importance to several areas in Computer Science. Its main objective is concerned with identifying, analyzing and describing the essential concepts and constraints of a universe of discourse, with the help of a (diagrammatic) modeling language that is based on a set of basic modeling concepts (forming a metamodel). In this tutorial, we show how conceptual modeling and requirements engineering languages (e.g., UML, ORM, EER, TROPOS) can be evaluated and (re)designed with the purpose of improving their ontological adequacy. In simple terms, ontological adequacy is a measure of how truthful the models produced using a modeling language are to the situations in the reality they are supposed to represent, and how easy it is for users to use these models for communicating, domain learning and problem-solving.

The tutorial starts by briefly discussing a systematic evaluation method for comparing a metamodel of the concepts underlying a language to a reference ontology of the corresponding domain in reality. The focus is on general conceptual modeling languages (as opposed to domain specific ones). Hence, the reference ontology employed here is a foundational (or upper-level) ontology. Moreover, since, it focuses on structural modeling aspects (as opposed to dynamic ones), this foundational ontology is an ontology of objects, their properties and relations, their parts, the roles they play, and the types they instantiate. The foundational ontology which is adopted in this tutorial has been developed by adapting and extending a number of theories coming, primarily, from formal ontology in philosophy, but also from cognitive science, philosophical logics and linguistics. Once developed, every sub-theory of the ontology is used for the creation of methodological tools (e.g., modeling profiles, guidelines and design patterns). The expressiveness and relevance of these tools are shown throughout the presentation to solve some classical and recurrent conceptual modeling problems. Moreover, their application is exemplified through their use in two different scenarios, namely, the construction of a heart electrophysiology reference model, and the evolution of an ontology in the domain of Petroleum and Gas. Finally, the tutorial includes the presentation of a computational environment that automates the aforementioned methodological tools, thus, providing support for: (i) "ontological correctness by design" in conceptual modeling; (ii) model validation by simulation.

Short bio:

Giancarlo Guizzardi obtained a PhD degree (with the highest distinction) from the University of Twente, in The Netherlands in 2005. Since 2003 he has been a Visiting Scientist, Research Collaborator and Associated Researcher at the Laboratory for Applied Ontology (LOA), Institute for Cognitive Science and Technology (ISTC), in Trento, Italy. He is currently an Associate Professor at the Computer Science Department at the Federal University of Espírito Santo, in Vitória, Brazil, where he is one of the coordinators of the Ontology and Conceptual Modeling Research Group (NEMO). He has been working for about twelve years in the development of Domain and Foundational Ontologies and their application in computer science and, primarily, in the area of Conceptual Modeling. His experience in the area has also been acquired in a number of academic and industrial projects in domains such as Off-Shore Software Development, Oil and Gas, and Medical Informatics. He is one of the initiators of the workshop series VORTE (Vocabularies, Ontologies and Rules for The Enterprise), a satellite event of the IEEE EDOC (Enterprise Computing) Conference, WOMSDE (Workshop on Ontologies and Metamodels in Software and Data Engineering), and MOST (Metamodels, Ontologies and Semantic Technologies), organized in 2009 as an ER workshop. He is the authors of nearly 80 publications in the subject of Ontologies and Conceptual Modeling published in journals, book chapters, conference proceedings and a book monograph, including the best-paper award winning of the CAiSE'2004 conference. He has been a guest editor of journals such as Applied Ontology, Information Systems, and the International Journal of Business Process Integration and Management (IJBPIM) and is currently an editorial board member of the International Journal of Information Systems Analysis and Design (IJISAD). Finally, he is currently entitled to a Brazilian National Research Council (CNPq) productivity grant and, very recently, has been nominated for the Christian Huygens Science Award at the Dutch Academy of Science (results still pending).

Conceptual Cloud Modeling

Description:

We will start with a brief introduction showing the progression from Information Systems to Web Information Systems and further to Web Services and Clouds, and the lack of Conceptual Modelling in the newer development. We will then outline the general idea of cloud computing through the provision of services on the web that can be searched for, composed and optimised, for which functional and non-functional criteria have to be combined -- the latter ones usually refereed to as Quality of Service properties.

Foundations of Clouds: Taking a provider view we start from the fundamental question: what is a cloud? Technically, we understand a cloud as a federation of software services that are made available via the web, and that can be used by any application. A common understanding in the web services community is that a service is defined as a function or operation with the appropriate input/output specification. In the tutorial we take a slighly more general view regarding a service as a piece of software that does not only provide functionality, but also data. We then formalise this view by Abstract State Services (ASSs) thereby adopting the theory of Abstract State Machines and its customisation to data intensive systems (ADTM thesis). An ASS abstracts from Web Information Systems including Web 2.0 systems. At its core it is defined by a hidden database layer, on top of which views that are extended by service operations are made publicly available. By abstracting from the conceptual model of WISs all features such as adaptivity, hierarchies, etc. can be exploited as well. Clouds are characterised as federations of ASSs that in addition provide an ontology describing the services that are available from the cloud. For this description logics can be exploited such that the provided services, i.e. the data in the views and the service operations define the ABox of the ontology. The TBox comprises functional characterisations of services by categorisation, typing, pre- and postconditions of operations, etc., and non-functional Quality of service (QoS) characterisations such as response time, availability, accuracy, costs, etc. We set this abstract conceptual model of clouds into perspective by briefly discussing the supporting and missing features in WSDL, UDDI and SOAP. Clouds can be integrated, i.e. an integrated, extended ontology with adaptor functions can be defined thereby making services in a set of clouds available in a uniform way. This leads to the model of trusted service brokers (TSBs) on top of clouds.

Searching in the Clouds: We finally take a user view asking how clouds and TSBs can be used to define applications and build new services. Key to the model is searching within the ontologies of clouds and TSBs to identify services that match a given query. In order to be successful it may be necessary to decompose the query. Furthermore, based on the reliability of the information in the ontologies we have to estimate the confidence in the search result. In general, a search result will consist of usables matches of services, i.e. ASS components plus their non-functional QoS characteristics. There will be more than one possible match. We will discuss the grade of query satisfaction and overlaps in the matches. The non-functional characteristics can be aggregated to define an objective QoS measure for the various matches. Together with the gaps in service satisfaction this gives rise to an optimisation problem, which has to be solved in order to determine the best suitable use of services available from clouds. The identified service components have to be composed to define the desired application.

Short bios:

Hui Ma (BE, BInfSci, MInfSci, PhD) received a BE in Civil Engineering from Tongji University, China in 1989, a BInfSci (Honours) and a MInfSci in Information Systems from Massey University, New Zealand in 2002 and 2003, respectively, and a Ph.D. in Information Systems from Massey University in 2007. Since 2008 she is Lecturer in Software Engineering at the School of Engineering and Comuter Science at Victoria University of Wellington, New Zealand. Her major research interests are distributed databases, web engineering, service-oriented systems and cloud computing, and geographical Information Systems.

Klaus-Dieter Schewe (MSc, PhD, DSc) studied mathematics and computer science at the University of Bonn (Germany), from which he received his Ph.D. in Mathematics in 1985. From 1985 to 1990 be worked with large industrial companies in the fields of Artificial Intelligence, Software Engineering and Office Information Systems. Returning to Hamburg University in 1990 he worked on Formal specifications and semantics and Database Theory. In 1995 he received a D.Sc. in Computer Science from the Brandenburgian Technical University at Cottbus (Germany). From 1994 to 1999 he was Associate Professor with the Computer Science Department of the Technical University Clauthal, and from 2000 to 2008 he was Chair of Information Systems at Massey University in New Zealand. Since 2003 he is Director of the Information Science Research Centre in New Zealand (until 2007 part of Massey University). His major research interests are database theory and systems, logic in databases and systems development methodologies, in particular for web information systems. He has published more than 200 refereed publications, and has been programme committee chair and general chair for several international events such as ADC, FoIKS, QSIC, ER and WISE.

Qing Wang (BE, MEc, MIS) a Bachelor in Engineering from South China University of Technology in 1993 and a Master in Economics from Jinan University in 2000. From 1993 to 2003 she worked in the IT industry. In 2006 she received a Master of Information Systems from Massey University. She is currently completing her Ph.D. in Information Systems. Her research focuses on the areas of Complex Data Models, Query Languages and Database Transformations.

Web Information Systems Co-Design & Web 2.0

Description:

The tutorial will be organized into three parts, devoted to From Web 1.0 to Web 2.0 and Beyond, Service Orientation / WIS Co-Design, and Service Composition and Collaboration. Part I will give a brief description of three stages that websites have gone through and still will go through: author-driven Web 1.0, user-driven and content-centred Web 2.0, and Web 3.0, which is characterised by (4C + P + V S), where 4C means Content, Commerce, Community and Context, P means Personalization, and V S denotes Vertical Search. We will then discuss in detail Enterprise 2.0, cloud computing, mashups and Web-Oriented architecture in order to show the problems in WIS development and the need for WIS development methods.

For enterprise 2.0 we will highlight its components emphasising freeform, links, authorship, tagging, network-orientation, extensions, search, social aspects, emergence and signals. This leads to challenges and opportunities for a new marketplace,in particular with respect to office2.0. For cloud computing we discuss opportunities and risks. We then address the merger of SOA and cloud computing into Web2.0 leading to web-oriented architectures (WOA). In particular, we will provide a characterisation of the major WOA features emphasising its radically distributed, granular, web-oriented, open, and highly consumable nature. This will then be the ground for discussing online communities, in particular with respect to pull-based stories, and customer communities. With respect to mashups we highlight the need of supporting technology, and show examples, where this support is emerging. We distinguish between "organic" and "tool-supported" mashups. In particular, integrating enterprise2.0 and mashups will give rise to new eterprise opportunities, but several problems still have to be solved. Finally, we highlight quality problems associated with wikis, and summarise the challenges for WIS modelling.

Following this in part II, we plan to present the major blocks of our WIS development methodology dealing with strategic modelling of WISs, usage modelling of WISs by means of storyboarding, conceptual modelling of WISs by means of media types, and semantics and pragmatics of storyboarding. We will pay particularly attention to services and contributions to communities.

The strategic characterisation of a WIS starts from the very general question what the WIS is about, i.e. the purpose(s) of the system, and what are criteria for the WIS being successful. The general answer to these questions gives rise to an informal mission statement, and a characterisation of the brand of the WIS. The latter one will follow the general classification scheme for WISs. Going more into detail we first explore the kind of content that is to be presented in the WIS, and the kind of functionality, with which this content can be accessed, customised to the needs of particular WIS users, and updated. This defines the utilisation space and the utilisation portfolio of the WIS. The fourth and last part of a strategic WIS model concerns the ambience, i.e. general rules for the formation of the WIS presentation.

On a high-level of abstraction usage modelling emphasises storyboarding, which consists of three interconnected parts: the modelling of the story space, the modelling of the actors, i.e. classes of users, and the modelling of tasks. In a first step we present the modelling language of storyboarding. For the story space modelling by hierarchies od labelled, directed graphs is adopted. Taking a closer look into the sequencing of actions executed by a user we obtain an assignment-free process algebra. For the actors we first address the modelling of roles, then the profiling of users. The used model combines characteristics and then defines important user types. For each user type preference rules describing the user behaviour can be formulated. These preference rules will form the basis for the personalisation of the story space. The tasks link the actors with the story space. A task will consist of a goal, involved actors and required actions. Reasoning about tasks will permit to set up task execution plans. The goals will also link the tasks to the personalisation of the story space. In a second step we will briefly discuss semantic aspects of storyboarding focusing on an algebraic approach to reason about storyboards emphasising the personalisation with respect to preference rules, and the satisfiability of deontic constraints. For the former one starting from the story algebra this can in fact be represented as a Kleene algebra with tests (KATs) and thus enables a simple form of system personalisation by term rewriting. The roles of actors are associated with rights and obligations, which leads to a propositional deontic logic. We will demonstrate how deontic constraints impact on the personalisation, then outline how this can be used to reason about tasks.

In a third step we will introduce media types as a core design construct in the co-design approach for WISs. Media types are employed as interface abstractions for describing content, functionality, context and adaptivity to user preferences and intentions, end-devices, and channel limitations. Furthermore, extensions such as hierarchical versions and cohesion enable granularity and adaptivity. Further, we will show that media types not only are linked to scenes in the storyboard but also support sessions, collaboration and context. In a fourth step we will address pragmatics of storyboarding, i.e. the necessary complement devoted to what the storyboard means for its users. The part of pragmatics is concerned with usage analysis by means of life cases, user models and contexts that permit a deeper understand of what users actually understand the system to be used for. They further provide aids for practical storyboarding. Then we complement usage analysis by WIS portfolios, which comprise two parts: the information portfolio and the utilisation portfolio. The former one is concerned with information consumed and produced by the WIS users, which leads to content chunks; the latter one captures functionality requirements. Part III will focus on service composition and collaboration. We will look at how our WIS co-design techniques presented in Part II can be adopted to solutions to various Web x.y applications, including E-Business, Enterprise 2.0, Mashups, thus picking up on the challenges we highlighted in part I.

The starting point is naturally a brief discussion, which web2.0 features have already been covered by the methodology and in which way. In particular, we will show how media types and storyboards are used to support Wikis and mashups. We will show that indeed not many problems are left, among which collaboration is the the most profound. Therefore, we highlight that collaboration comprises cooperation, communication and coordination, for which we present the media type based approach by exchange frames, which we then apply to wikis. We illustrate this by looking at the potential of web2.0 for e-business.

Short bios:

Hui Ma (BEng, MInfSci, PhD) is Lecturer in the School of Engineering and Computer Science at Victoria University of Wellington in New Zealand. Her major research interests are distributed databases, service-oriented systems and the web, and geographical information systems.

Bernhard Thalheim (MSc, PhD, DSc) is full professor at Christian-Albrechts-University Kiel in Germany. His major research interests are database theory, logic in databases, and systems development methodologies, in particular for web information systems. He has published more than 250 refereed publications, and has been programme committee chair and general chair for several international events such as MFDBS, ER, FoIKS, ASM, NLDB, ADBIS and WISE.

The Database Design Module of an Animated Database Courseware (ADbC)

Description:

The Animated Database Courseware (ADbC) is funded by NSF Grant# 0717707. It is a collection of software animations designed to support the teaching of database concepts. Currently, it includes four modules: database design, sql, transactions and security. The software is located at http://adbc.kennesaw.edu, has a very low learning curve and is freely available. The animations are not tailored to any specific product or textbook nor are they intended to substitute for them. Instead, they provide a means to facilitate student learning resulting in an opportunity to include more depth or breadth to the concepts covered in a database course.

The tutorial will explore different ways the software may be incorporated into the classroom environment. It will focus on the database design module of ADbC. This module consists of seven sub-modules.

Short bios:

Dr. Mario A.M. Guimaraes is a Professor of Computer Science at Kennesaw State University. His main areas of interests are database technology and instructional systems development. He also has extensive experience in the development of educational software. Instructional software he developed in the areas of introductory programming and trigonometry has been commercialized and is used heavily throughout Brazil. 10 years of experience teaching database fundamentals, database security, videogame design, systems analysis, programming, software engineering and project management. He has been a PI for multiple NSF, Eisenhower and RTA grants and is currently the PI for an NSF funded grant to developed database courseware. He recently completed an NSF post-doctorate in fellowship in Information Assurance with an emphasis in Database Security.

Dr. Meg C. Murray, an Associate Professor of Information Systems at Kennesaw State University, has extensive experience, both in academe and in industry, in the area of software design, development and architecture. Her current work has been in the area of web services and using XML as a medium for data exchange and she has been an author and presenter on the technical and societal implications of the evolving software paradigm referred to as "Software as a Service." She developed a model for a healthcare information systems portal to facilitate the exchange of healthcare data stored in a variety of backend database systems. She has taught undergraduate database courses and software development courses that focus on developing program code as an interface to database systems, has a great deal of experience in curriculum development and instructional materials creation and is the co-PI on an NSF grant to develop database courseware. She was the recipient of the KSU College of Science and Mathematics Distinguished Teaching Award and was named a semifinalist as the Women of the Year in Technology in Georgia.