Report from Dagstuhl Seminar 18462: Provenance and Logging for Sense Making
Résumé
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,
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 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.
Domaines
Interface homme-machine [cs.HC]Origine | Fichiers produits par l'(les) auteur(s) |
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