Record link: 
http://hdl.handle.net/20.500.12708/145942
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Title: 
Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151)
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Citation: 
Abiteboul, S., Arenas, M., Barceló, P., Bienvenu, M., Calvanese, D., David, C., Hull, R., Hüllermeier, E., Kimelfeld, B., Libkin, L., Martens, W., Milo, T., Murlak, F., Neven, F., Ortiz de la Fuente, M. M., Schwentick, T., Stoyanovich, J., Su, J., Suciu, D., … Yi, K. (2018). Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151). In Dagstuhl Perspectives Workshop 16151 (Vols. 7, 1, Issue 1, pp. 1–29). https://doi.org/10.4230/DagMan.7.1.1
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Publisher DOI: 
10.4230/DagMan.7.1.1
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Authors: 
Abiteboul, Serge 
Arenas, Marcelo 
Barceló, Pablo 
Bienvenu, Meghyn 
Calvanese, Diego 
David, Claire 
Hull, Richard 
Hüllermeier, Eyke 
Kimelfeld, Benny 
Libkin, Leonid 
Martens, Wim 
Milo, Tova 
Murlak, Filip 
Neven, Frank 
Ortiz de la Fuente, M.Magdalena 
Schwentick, Thomas 
Stoyanovich, Julia 
Su, Jianwen 
Suciu, Dan 
Vianu, Victor 
Yi, Ke 
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Organisational Unit: 
E192-03 - Forschungsbereich Knowledge Based Systems 
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Published in: 
Dagstuhl Perspectives Workshop 16151 
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Volume: 
7, 1
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Issue: 
1
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Date (published): 
2018
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Event name: 
Dagstuhl Perspectives Workshop 16151: Foundations of Data Management 
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Event date: 
10-Apr-2016 - 15-Apr-2016
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Event place: 
Germany
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Number of Pages: 
29
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Keywords: 
machine learning; workflows; uncertainty; database theory; principles of data management; query languages; efficient query processing; query optimization; heterogeneous data; knowledge-enriched data management; human-relat
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Abstract: 
The area of Principles of Data Management (PDM) has made crucial contributions to the development of formal frameworks for understanding and managing data and knowledge. This work has involved a rich cross-fertilization between PDM and other disciplines in mathematics and computer science, including logic, complexity theory, and knowledge representation. We anticipate on-going expansion of PDM research as the technology and applications involving data management continue to grow and evolve. In particular, the lifecycle of Big Data Analytics raises a wealth of challenge areas that PDM can help with. In this report we identify some of the most important research directions where the PDM community has the potential to make significant contributions. This is done from three perspectives: potential practical relevance, results already obtained, and research questions that appear surmountable in the short and medium term.
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Research Areas: 
Logic and Computation: 100%
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Science Branch: 
Informatik
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