Research Directions for Principles of Data Management (Abridged)

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.