Research Directions for Principles of Data Management (Abridged)

Abstract

In April 2016, a community of researchers working
in the area of Principles of Data Management
(PDM) joined in a workshop at the Dagstuhl Castle
in Germany. The workshop was organized jointly
by the Executive Committee of the ACM Symposium
on Principles of Database Systems (PODS)
and the Council of the International Conference on
Database Theory (ICDT). The mission of the workshop
was to identify and explore some of the most
important research directions that have high relevance
to society and to Computer Science today,
and where the PDM community has the potential to
make significant contributions. This article presents
a summary of the report created by the workshop
[4]. That report describes the family of research
directions that the workshop focused on from three
perspectives: potential practical relevance, results
already obtained, and research questions that appear
surmountable in the short and medium term.
The report organizes the identified research challenges
for PDM around seven core themes, namely
Managing Data at Scale, Multi-model Data, Uncertain
Information, Knowledge-enriched Data, Data
Management and Machine Learning, Process and
Data, and Ethics and Data Management. Since new
challenges in PDM arise all the time, we note that
this list of themes is not intended to be exclusive.