November 11 – 16 , 2018, Dagstuhl Seminar 18462

Provenance and Logging for Sense Making


Jean-Daniel Fekete (INRIA Saclay – Orsay, FR)
T. J. Jankun-Kelly (Mississippi State University, US)
Melanie Tory (Tableau Software – Palo Alto, US)
Kai Xu (Middlesex University – London, GB)

For support, please contact

Susanne Bach-Bernhard for administrative matters

Michael Gerke for scientific matters


List of Participants
Shared Documents
Dagstuhl Seminar Schedule [pdf]


Sense making is one of the biggest challenges in data analysis faced by both the industry and the research community. It involves understanding the data and uncovering its model, generating a hypothesis, selecting analysis methods, creating novel solutions, designing evaluation, and also critical thinking and learning wherever needed. The research and development for such sense making tasks lags far behind the fast-changing user needs, such as those that emerged recently as the result of so-called “Big Data”. As a result, sense making is often performed manually and the limited human cognition capability becomes the bottleneck of sense making in data analysis and decision making.

One of the recent advances in sense making research is the capture, visualization, and analysis of provenance information. Provenance is the history and context of sense making, including the data/analysis used and the users’ critical thinking process. It has been shown that provenance can effectively support many sense making tasks. For instance, provenance can provide an overview of what has been examined and reveal gaps like unexplored information or solution possibilities. Besides, provenance can support collaborative sense making and communication by sharing the rich context of the sense making process.

Besides data analysis and decision making, provenance has been studied in many other fields, some- times under different names, for different types of sense making. For example, the Human-Computer Interaction community relies on the analysis of logging to understand user behaviors and intentions; the WWW and database community has been working on data lineage to understand uncertainty and trust- worthiness; and finally, reproducible science heavily relies on provenance to improve the reliability and efficiency of scientific research.

This Dagstuhl Seminar aims to bring together researchers from the diverse fields that relate to provenance and sense making to foster cross-community collaboration and develop novel solutions for shared challenges. More specifically, to

  • articulate the state of the art in provenance research and software development;
  • provide guidelines on how best to use provenance information for different scenarios;
  • encourage cross-community collaboration on novel solutions based on provenance; and
  • identify open research challenges and provide directions for further provenance research

  Creative Commons BY 3.0 DE
  Jean-Daniel Fekete, T. J. Jankun-Kelly, Melanie Tory, and Kai Xu


  • Computer Graphics / Computer Vision
  • Data Bases / Information Retrieval
  • Society / Human-computer Interaction


  • Visual Analytics
  • Provenance
  • Logging
  • Sensemaking
  • Reproducible Science

Book exhibition

Books from the participants of the current Seminar 

Book exhibition in the library, ground floor, during the seminar week.


In the series Dagstuhl Reports each Dagstuhl Seminar and Dagstuhl Perspectives Workshop is documented. The seminar organizers, in cooperation with the collector, prepare a report that includes contributions from the participants' talks together with a summary of the seminar.


Download overview leaflet (PDF).


Furthermore, a comprehensive peer-reviewed collection of research papers can be published in the series Dagstuhl Follow-Ups.

Dagstuhl's Impact

Please inform us when a publication was published as a result from your seminar. These publications are listed in the category Dagstuhl's Impact and are presented on a special shelf on the ground floor of the library.

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