Towards an Objective Metric for Data Value Through Relevance
Summary: Introduce an objective metric for data value via formalized 'data relevance' and efficient computation/maintenance for evolving tabular and semi-structured datasets. Apply relevance-driven value to prioritize storage/query layout, guide curation/pricing/catalogs, and manage 'dark data' and workload–data interactions. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Boris Glavic (Illinois Institute of Technology)
- 2. Pengyuan Li (Illinois Institute of Technology)
- 3. Ziyu Liu (Illinois Institute of Technology)
- 4. Dieter Gawlick (Oracle)
- 5. Vasudha Krishnaswamy (Oracle)
- 6. Danica Porobic (Oracle)
- 7. Zhen Hua Liu (Oracle)
BibTeX Citation
@inproceedings{glavic_cidr24,
address = {Amsterdam, Netherlands},
series = {{CIDR} '24},
title = {{Towards an Objective Metric for Data Value Through Relevance}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Glavic, Boris and Li, Pengyuan and Liu, Ziyu and Gawlick, Dieter and Krishnaswamy, Vasudha and Porobic, Danica and Liu, Zhen Hua},
year = {2024}
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 48 | DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases | 1997 | VLDB | 0.00044033592 |
| 514 | Goods: Organizing Google's Datasets | 2016 | SIGMOD | 0.00017178673 |
| 749 | Data Lake Management: Challenges and Opportunities | 2019 | VLDB | 0.00014379989 |
| 2,025 | Data Market Platforms: Trading Data Assets to Solve Data Problems | 2020 | VLDB | 9.2903125e-05 |
| 2,503 | The Semiring Framework for Database Provenance | 2017 | PODS | 8.4964654e-05 |
| 2,719 | Toward Practical Query Pricing with QueryMarket | 2013 | SIGMOD | 8.209612e-05 |
| 3,991 | The Complexity of Resilience and Responsibility for Self-Join-Free Conjunctive Queries | 2016 | VLDB | 6.9695922e-05 |
| 8,889 | Provenance-based Data Skipping | 2022 | VLDB | 5.3512428e-05 |
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