Managing Scientific Data: Lessons, Challenges, and Opportunities
Summary: Global survey of scientific data management: lessons, challenges, opportunities for analysis. Pushes back against general-purpose DBMS inefficiencies; advocates preserving data independence while enabling growth in datasets and complex queries. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Anastasia Ailamaki (EPFL)
BibTeX Citation
@inproceedings{ailamaki_sigmod11,
title = {{Managing Scientific Data: Lessons, Challenges, and Opportunities}},
author = {Ailamaki, Anastasia},
series = {{SIGMOD} '11},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1989323.1989433},
url = {https://dl.acm.org/doi/10.1145/1989323.1989433},
year = {2011}
}
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