1st Workshop on Conceptual Design for Internet of Robotic Things
The objective of the First Workshop on Conceptual Design for Internet of Robotic Things (CD4IoRT) is to foster the use of conceptual design in the Internet of Robotic Things (IoRT) domain. Thanks to the advantages brought into everyday human life, IoRT systems have emerged as key technologies with a wide range of applications, in many application domains, e.g., agriculture, manufacturing, industry, domotics, and health. However, the implementation and management of these systems require a broad set of skills. This knowledge gap can be closed by novel conceptual modeling and engineering approaches specific to these software systems. The workshop aims to be a point of contact for practitioners and researchers from Conceptual Modeling with other communities such as Software Engineering, Databases, Business Process Management, Distributed Systems, Formal Methods, and Information Systems where creating a dialogue centered on the development of scientific foundations in this topic. The workshop will foster the discussion of research works, case studies, experiences, and industry showcases in order to set up joint activities and future research directions.
4th International Workshop on Conceptual Modeling for Life Sciences
The fourth edition of the Workshop on Conceptual Modeling for Life Sciences aims to be a meeting point for Information Systems (IS), Conceptual Modeling (CM), and Data Management (DM) researchers working on health care and life science problems. It is also an opportunity to share, discuss and find new approaches to improve promising fields, with a special focus on Genomic Data Management (how to use the information from the genome to better understand biological and clinical features) and Precision Medicine (giving to each patient an individualized treatment by understanding the peculiar aspects of the disease).
3rd Workshop on Conceptual Modeling, Ontologies and (Meta)data Management for Findable, Accessible, Interoperable and Reusable (FAIR) Data
In order to improve findability, accessibility, interoperability and reusability of different types of digital objects at scale, the FAIR principles focus on machine actionability. Therefore, a critical aspect to achieve this machine actionability is semantics. Proper semantic descriptions should be available to make “intelligible” for computational agents the elements of a FAIR data ecosystem such as data policies, data management plans, identifier mechanisms, standards, FAIRification processes, FAIRness assessment criteria and methods, data repositories and supporting tools.
The goal of the workshop on Conceptual Modeling, Ontologies and Metadata Management for FAIR Data is to discuss challenges, solutions and impact of, for one side, the use of conceptual modeling and metadata and data management to support the improvement of FAIRness in digital objects and, for the other side, the adoption of the FAIR principles to guide improvements in conceptual modeling.
6th International Workshop on Empirical Methods in Conceptual Modeling
Conceptual modeling has enjoyed substantial growth over the past decades in fields ranging from Information Systems Analysis to Business Process Engineering. A plethora of conceptual modeling practices (languages, frameworks, methods, etc.) have been proposed, promising to facilitate activities such as communication, design, or decision-making.
Success in adopting a conceptual modeling practice is, however, predicated on convincingly demonstrating that it indeed successfully supports these activities. Furthermore, the way individuals and groups produce and consume models gives raise to cognitive, behavioral, organizational, or other phenomena, whose systematic observation may help us better understand how models are used in practice and how we can make them more effective. At the same time, the act of building conceptual models is ideally informed by empirical evidence that is nowadays abundant in the form of digital data. This overabundance of data, combined with the advent of advanced data analysis and artificial intelligence (AI) techniques, introduces major opportunities and challenges in an empirically-informed conceptual modeling practice.
This workshop aims at bringing together researchers with an interest in the empirical investigation of conceptual modeling practices, as well as with the study of a data-driven, evidence-based conceptual modelling practice.
2nd International Workshop on Digital Justice, Digital Law and Conceptual Modeling
The JUSMOD 2023 workshop aims to be a meeting place for a variety of researchers involved in digital justice and digital law, creating a rich community that crosses different disciplines beyond informatics, such as law, legal informatics, management, economics, philosophy, and social sciences. The workshop will provide an opportunity to share, discuss and identify new approaches and solutions for modeling, analyzing, formalizing and interpreting legal data and related processes. Our purpose, therefore, is to build a bridge between IT and Law professionals.
9th International Workshop on Ontologies and Conceptual Modeling
The International Workshop on Ontologies and Conceptual Modeling (OntoCom) is an academic workshop that focuses on the practical and formal application of ontologies to conceptual modeling. The importance of conceptual modeling has grown over the years and it is now common to find examples of conceptual models being developed and used in a range of diverse disciplines not related to computing including, for example, biology, business, construction and engineering. Among the reasons for this disciplinary expansion is also the increasing digitalisation of all aspects of modern life as well as the increased complexity that such digitalisation entails in terms of emerging needs and requirements. The natural consequence is a proliferation of conceptual models of multiple real-world domains which sooner or later require data and systems to interoperate and/or integrate. In this emerging scenario ontology-driven conceptual modeling becomes even more fundamental to modern life due to its intrinsic ability to represent reality in a theoretically and semantically consistent manner. Foundational (or upper ontologies) have the potential to resolve the difficult problems that derive from a lack of a consistent and sound ontological theory. The benefits that can derive from the application of a foundational ontology include improved mapping to the real world domain, increased level of communication and understanding among stakeholders, model reuse, semantic integration and interoperability and increased overall efficiency and effectiveness of information systems development and evolution. Foundational ontologies can also assist in overcoming the inscrutable nature of most mainstream artificial intelligence methods (i.e. neural networks and machine learning). Contributions in the form of research, research-in-progress papers and practitioner reports are welcome.
4th International Workshop on Quality and Measurement of Model-Driven Software Development
Model-driven development (MDD) is a widely adopted paradigm that automates software generation by means of model transformations and reuse of development knowledge. The MDD advantages have motivated the emergence of several modeling proposals and MDD tools related to different application domains and stages of the development lifecycle. In MDD, the quality of conceptual models is critical because it directly impacts the final software systems’ quality. Therefore, it is essential to evaluate conceptual models and predict the software products’ relevant characteristics. Additionally, MDD project management must be adapted to take into account that programming effort is being replaced by a modelling effort at an earlier stage. Hence, measuring models is crucial to support cost estimation and project management.
To address these challenges, QUAMES aims to attract research on methods, procedures, techniques, and tools for measuring and evaluating the quality of conceptual models that can be used in MDD environments. Its primary goal is to enable the development of high-quality software systems by promoting quality assurance in the modeling process
1st Workshop on Controlled Vocabularies and Data Platforms for Smart Food Systems
SmartFood is a forum meant to bring together researchers, industry workers (e.g. logistics, health, etc.), and consumer organizations that are concerned about the future of food-related systems and processes. More specifically, we hope to gather people that believe that Semantic technologies, such as controlled vocabularies and ontologies, Data platforms, and consumer behavior-based models are at the core of the solutions targeting this field. On the other hand, this forum aims to attract discussion on sustainable business models in data-driven agri-food.