Conceptual Models as Ontological Contracts
Giancarlo Guizzardi, Free University of Bolzano-Bozen, Italy and University of Twente, Netherlands
The Need for Context in Software Engineering
Gail Murphy, University of British Columbia, Canada
About Synergies between Model-based Engineering and Artificial Intelligence
Sébastien Gérard, CEA, France
Conceptual Models as Ontological Contracts
Giancarlo Guizzardi
Free University of Bolzano-Bozen, Italy and University of Twente
Netherlands
Brief Bio
Giancarlo Guizzardi is a Full Professor of Computer Science, at the University of Twente, The Netherlands. He is also a Full Professor of Computer Science and head of the Conceptual and Cognitive Modeling Research Group (CORE), at the Free University of Bozen-Bolzano, Italy. He has been working for circa 25 years in Ontology-Driven Conceptual Modeling and has been one of the main contributors to the development of the Unified Foundational Ontology (UFO) and the OntoUML language. He is associate editor for Applied Ontology and Data & Knowledge Engineering, and a member of the Advisory Board of the International Association for Ontology and its Applications (IAOA).
Abstract
In the years to come, we will experience an increasing demand for building Reference Conceptual Models in critical domains in reality, as well as employing them to address classes of problems, for which sophisticated conceptual distinctions are demanded. One of these key problems is Semantic Interoperability. Effective semantic interoperability requires an alignment between worldviews or, to put it more accurately, it requires the precise understanding of the relation between the (inevitable) ontological commitments assumed by different representations and the systems based on them (including sociotechnical systems).
In this talk, I argue that, in this scenario, Reference Conceptual Models should be seen as Ontological Contracts, i.e., as precise descriptions that explicitly represent the Ontological Commitments of a collective of stakeholders sharing a certain worldview. I then elaborate on a number of theoretical, methodological and computational tools required for building these meaning contracts. Firstly, I discuss the importance of Formal Ontology in the philosophical sense and, in particular, I elaborate on the role of foundational axiomatic theories and principles in the design of conceptual modeling languages and methodologies. Secondly, I discuss the role played by three types of complexity management tools that are derived from these foundational theories, namely: Ontological Design Patterns (ODPs) as methodological mechanisms for encoding these ontological theories; Ontology Pattern Languages (OPLs) as systems of representation that take ODPs as higher-granularity modeling primitives; and Ontological Anti-Patterns (OAPs) as structures that can be used to systematically identify possible deviations between the set of valid state of affairs admitted by a model (the actual ontological commitment) and the set of state of affairs actually intended by the stakeholders (the intended ontological commitment). Finally, I illustrate the role played by a particular type of computer-based visual simulation approach in the validation of these reference models as well as for anti-pattern elicitation and rectification.
The Need for Context in Software Engineering
Gail Murphy
University of British Columbia
Canada
Brief Bio
Gail C. Murphy is a Professor of Computer Science and Vice-President Research and Innovation at the University of British Columbia. Her research interests are in improving the productivity of software developers and knowledge workers by giving them tools to identify, manage and coordinate the information that really matters for their work. She is a Fellow of the ACM and a Fellow of the Royal Society of Canada. She is the recipient of the 2018 IEEE Computer Society Harlan D. Mills award and a previous recipient of an NSERC E.W.R. Steacie Award and the AITO Dahl-Nygaard Junior Prize. She is also a co-founder and Director at Tasktop Technologies inc.
Abstract
The development of a software system requires the orchestration of many different people using many different tools. Despite the need for a developer who is performing a task to understand the context in which that task is undertaken, the tools we imagine, build and provide to support software developers are typically isolated. Instead of the tools helping a developer work within the appropriate context, it is the developer who must bring the context to the tools.
In this talk, I will argue that the lack of context in the software engineering tools we build limits the effectiveness of developers and of our software development practices.
About Synergies between Model-based Engineering and Artificial Intelligence
Sébastien Gérard
CEA
France
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Brief Bio
Sébastien Gérard is director of research at CEA and he is the research program leader around the knowledge co-engineering platform of the CEA LIST software and sytem engineering department. Working on research issues related to complex and critical system and software design for more than 20 years, his research interests include correct-by-construction specification and design of complex systems, model-based engineering of complex systems and visual modeling language engineering. He is the CEA representative at OMG for more than 15 years. In particular, he is the chair of the MARTE standardization task force. He is also leading the open-source project, Papyrus (www.eclipse.org/papyrus), the UML modeling tools of Eclipse. In 1995, he has a diploma in mechanics and aeronautics from the ENSMA high-school, in 2000 he obtained a PhD diploma in Computer Science from the Evry university and in 2013 he got his “habilitation à diriger des recherches” diploma in the domain of computer science from the Orsay univiersity. Sébastien is co-leading the Modelia initiative (www.modelia.eu) with Jordi Cabot where they investigate the usage of AI to empower MDE and reversely how MDE can benefit to AI design.
Abstract
Model-based Engineering (MBE) is about abstraction and automation: MBE enables to abstract system to design or problem to solve by modeling them and empower their exploitation thanks to model transformations used to automate steps of the design or thinking process. Standard modeling languages such as UML and SysML have been around for a long time now and are key artifacts of MBE success. However, even if both languages are now worldwide widespread being educated in all universities and used in a lot of industrial cases, there are still a lot of claims raised, mainly focussed on their complexity and the tool support user experience. Digital assistants such as Bots seem to be a promising solution to face those concerns and hence AI is expected to be a key enabling technology.
Artificial Intelligence (AI) is about data and automation: AI enables us to automate some activities including decision making and needs data to be implemented. Even, if the offer in terms of AI technologies is flourishing, issues related to AI design and deployment are still around and require attention. Above all, trustability of AI is a key topic for all domains where AI is expected to play an important role specially when decisions are made (e.g., heath or autonomous vehicle). Through its capacity to formalize data modeling and design processes, MBE
The purpose of this keynote is to explore those possible synergies between both MBE and AI showing use case on how AI can empower MBE and reversely on how MBE can help designing AI.