COVID-19: CoMinDs is planned as a physical, in-person event, with certain support for remote presence, both for speakers and for other participants who are unable or unwilling to come. Depending on the pandemic situation, we may have to make a decision whether to cancel the physical component of the event or not.
|12.30 - 14.00
|14.15 - 15.15
|Keynote:Process Mining for the Social Sciences: Methodological advances and Applications
|15.15 - 15.30
|15.30 - 16.00
|16.00 - 16.25
|Process Discovery for Collaborative Business Execution
|Flavio Corradini, Caterina Luciani, Andrea Morichetta, Marco Piangerelli and Andrea Polini
|16.25 - 16.50
|Event Log Pre-Processing with Semantic Enhancement in a Graph Database
|Kyle Smith and Emanuele Laurenzi
|16.50 - 17.15
|A Tag-based Methodology for the Automatic Generation of Collaborative Event Logs
|Flavio Corradini, Sara Pettinari, Barbara Re and Francesco Tiezzi
|19:00 - 20:00
Invited Speaker Andrea Vandin (Sant’Anna School for Advanced Studies, Pisa). Tenure-track Assistant Professor in Computer Science Sant’Anna School of Advanced Studies, Pisa, Italy Adjunct Associate Professor DTU Technical University of Denmark
Abstract EMbeDS is a newly established Department of Excellence of Sant’Anna School for Advanced Studies, Pisa, Italy, fostering the use of computer science and statistics in the Social Sciences. I joined EMbeDS in January 2020, and have since then interacted with people from social sciences like Economics, and Healthcare Management. In this talk, I will present the results of two ongoing collaborations centered on the use of Process Mining:
Nowadays, organizations increasingly need to coordinate to achieve their goals collaboratively and create new forms of business. This requires organizations to form (business-oriented) distributed systems, guaranteeing their interoperability. However, this task is made complex by the need to coordinate the interactions of various participants, dealing with requirements, constraints, and regulations coming from different organizations. In addition, many business scenarios started to involve more automated and highly distributed components such as robots and smart devices that perceive and interact with the dynamics arising from the physical world. Effective coordination and cooperation of such distributed systems demand the compatibility of the processes performed by each system component. Such cooperation can be supported by the observations of the whole systems’ behavior through collaborative mining, i.e., process mining applied in the presence of heterogeneous data produced by the system components, i.e., distributed event logs. Collaborative mining techniques address the discovery of collaborative models, thus fostering the coordination aspects that typically occur on distributed systems. The objective of the CoMinDS workshop is to attract researchers and industry practitioners to discuss collaborative mining and present open challenges, state of the art, in-progress research, and practical experiences, including case studies.
The topics of the workshop include, but are not limited to:
CoMinDs is an activity of the IEEE Task Force on Process Mining
CoMinDS wellcomes submission of abstract about ongoing researches, case studies, ideas, and practical experiences. Notably, abstracts will not be part of the proceedings. Authors have to submit their abstract (max 1 page full width exluding references in LNCS format ) at https://easychair.org/conferences/?conf=cominds2022.
CoMinDS welcomes submissions of short papers (max 8 pages) presenting novel ideas, position statements, and preliminary results within the theme of collaborative mining and regular paper (max 15 pages) discussing original research works. Papers must be formatted using CEUR-ART format (one column style) available http://ceur-ws.org/Vol-XXX/CEURART.zip, and must be submitted electronically via the EasyChair submission system, available at https://easychair.org/conferences/?conf=cominds2022.
Proceedings shall be submitted to CEUR-WS.org for online publication. Selected, accepted research papers will be considered for publication in an extended and revised form in a special issue to be published in Springer’s Computing journal.