* At a Glance
. Submission Deadline: *NEW* August 9th, 2023
. Location: Lisbon, Portugal
. Papers: Complete studies, designs, or position papers (10 LNCS pages max)
. Web site: https://emper-workshop.github.io/2023/

* Overview
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.

* Submissions
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 or 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 10 pages in LNCS format. The EmpER’23 accepted papers will be published within the ER Workshop proceedings, in the Springer LNCS Series.

* NEW! Short Research Presentations
For EmpER 2023, we offer, for the first time, the opportunity to submit short research presentations. This format is aimed at providing researchers with the possibility to share their newest research ideas and receive early feedback from our community.

Short research presentations should follow the LNCS format and not exceed two pages (all inclusive). We will apply a lightweight review and aim to accept all submissions that fall within the scope of EmpER and might spark discussions. Short research presentations can be submitted any time before September, 29th. We will notify all authors closely after the submission of their proposal. Please note that the submitted proposals will intentionally *not be published*.

For more information please visit the workshop web-page: https://emper-workshop.github.io/2023/


* Format and Duration
The workshop will consist of paper presentations with an emphasis on discussion. Time permitting, papers presenting on-going studies will have a discussion session led by a designated member of the program committee.

* Location
The workshop will take place in Lisbon, Portugal in conjunction with the 42nd International Conference on Conceptual Modeling (ER 2023).

* Important Dates
. Submission date: August 2nd, 2023
. Workshop author notification: September 4th, 2023
. Camera-ready submission: September 20th, 2023
. Workshop dates: November 6th-9th, 2023 (exact day to be confirmed)

* Workshop Organizers
. Dominik Bork, TU Wien, Austria
. Miguel Goulão, Universidade Nova de Lisboa, Portugal
. Sotirios Liaskos, York University, Canada