EmpER'23 will be held in conjunction with ER 2023 from November 6th to 9th.
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Link to CfP (PDF, 180kB)
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. At the same time, 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.
Furthermore, 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.
Aim and Topics
We aim 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. Contributions include but are not limited to:
- Complete, on-going or planned empirical studies in conceptual modeling.
- Literature Reviews on empirical research.
- Theoretical/philosophical positions.
- Technical contributions, case studies, or position and vision papers on data-driven, evidence-based conceptual modeling.
- Discussions/positions on statistical and methodological issues.
- Lessons learned from past studies.
Paper submission: 2 August 2023
Author notification: 4 September 2023
Camera-ready Version: 20 September 2023
We solicit three types of papers:
- Full papers describing a completed study or a technical contribution in empirical conceptual modeling.
- Work-in-progress papers describing a planned study, a study in progress, or other early results.
- Position, vision and lessons papers about the use of empirical methods for conceptual modelling.
Papers shall be limited to no more than 10 pages in LNCS format. The EmpER’23 accepted papers will be published within the ER Workshop proceedings, in the Springer LNCS Series.
Authors should consult Springer’s authors’ guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers. Springer encourages authors to include their ORCIDs in their papers. In addition, the corresponding author of each paper, acting on behalf of all of the authors of that paper, must complete and sign a Consent-to-Publish form. The corresponding author signing the copyright form should match the corresponding author marked on the paper. Once the files have been sent to Springer, changes relating to the authorship of the papers cannot be made.
Papers must adhere to the length restrictions above (including figures, references, etc.) and must use the LNCS template. For submitting your paper, please use the ER 2023 EasyChair installation and select the Workshop on Empirical Methods in Conceptual Modeling track.
The EmpER’23 accepted papers will be published within the ER Workshop proceedings, in the Springer LNCS Series. At least one of the authors for each accepted paper must be registered and attend the conference for paper presentation.
- Anna Bernasconi, Politecnico di Milano, Italy
- Robert Andrei Buchmann, Babeș-Bolyai University of Cluj Napoca, Romania
- Michel Chaudron, Eindhoven University of Technology, The Netherlands
- Marian Daun, University of Applied Sciences Würzburg-Schweinfurt, Germany
- Istvan David, University of Montreal, Canada
- Robson Fidalgo, Universidade Federal de Pernambuco, Brazil
- Antonio Garmendia, Universidad Autónoma de Madrid, Spain
- Vincenzo Gervasi, University of Pisa, Italy
- Sepideh Ghanavati, University of Maine, USA
- Andrea Herrmann, Herrmann & Ehrlich, Germany
- Jennifer Horkoff, Chalmers University of Technology, Sweden
- Katsiaryna Labunets, Utrecht University, The Netherlands
- Tong Li, Beijing University of Technology, China
- Grischa Liebel, Reykjavik University, Iceland
- Lin Liu, Tsinghua University, China
- Raimundas Matulevičius, University of Tartu, Estonia
- Jeffrey Parsons, Memorial University of Newfoundland, Canada
- Geert Poels, Ghent University, Belgium
- Jan Recker, University of Hamburg, Germany
- Ben Roelens, Open Universiteit, Ghent University, Belgium
- Carla Silva, Universidade Federal de Pernambuco, Brazil
- Irene Vanderfeesten, KU Leuven, Belgium
- Manuel Wimmer, Johannes Kepler University Linz, Austria
- Dominik Bork, TU Wien, Austria
- Miguel Goulao, Universidade Nova de Lisboa, Portugal
- Sotirios Liaskos, York University