Working Group Report in 'Provenance and Logging for Sense Making' report from Dagstuhl Seminar 18462: Provenance and Logging for Sense Making, Dagstuhl Reports, Volume 8, Issue 1

Attfield, Simon

Battle, Leilani

Bors, Christian

Dowling, Michelle

Endert, Alex

Koch, Steffen

Kulyk, Olga

Laramee, Robert

Troy, Melanie

Wenskovitch, John

English

International audienceSense making is one of the biggest challenges in data analysis faced by both the industry and theresearch community. It involves understanding the data and uncovering its model, generating ahypothesis, selecting analysis methods, creating novel solutions, designing evaluation, and alsocritical thinking and learning wherever needed. The research and development for such sensemaking tasks lags far behind the fast-changing user needs, such as those that emerged recentlyas the result of so-called “Big Data”. As a result, sense making is often performed manually andthe limited human cognition capability becomes the bottleneck of sense making in data analysisand decision making.One of the recent advances in sense making research is the capture, visualization, and analysisof provenance information. Provenance is the history and context of sense making, including thedata/analysis used and the users’ critical thinking process. It has been shown that provenance caneffectively support many sense making tasks. For instance, provenance can provide an overviewof what has been examined and reveal gaps like unexplored information or solution possibilities.Besides, provenance can support collaborative sense making and communication by sharing therich context of the sense making process.Besides data analysis and decision making, provenance has been studied in many other fields,sometimes 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 behavi-ors and intentions; the WWW and database community has been working on data lineage tounderstand uncertainty and trustworthiness; and finally, reproducible science heavily relies onprovenance to improve the reliability and efficiency of scientific research.This Dagstuhl Seminar brought together researchers from the diverse fields that relate toprovenance and sense making to foster cross-community collaboration. Shared challenges wereidentified and progress has been made towards developing novel solutions

Fekete, Jean-Daniel

Jankun-Kelly, T. J.

Tory, Melanie

Xu, Kai

HAL-CentraleSupelec

Report from Dagstuhl Seminar 18462: Provenance and Logging for Sense Making

INRIA a CCSD electronic archive server

Archive Ouverte en Sciences de l'Information et de la Communication

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\u27 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, sometimes 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 trustworthiness; and finally, reproducible science heavily relies on provenance to improve the reliability and efficiency of scientific research.

This Dagstuhl Seminar brought together researchers from the diverse fields that relate to provenance and sense making to foster cross-community collaboration. Shared challenges were identified and progress has been made towards developing novel solutions

Dagstuhl Research Online Publication Server

Provenance and Logging for Sense Making (Dagstuhl Seminar 18462)

https://eprints.mdx.ac.uk/28665/1/dagrep_v008_i011_p035_18462.pdf