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A Vision for Autonomous Data Agent Collaboration: From Query-by-Integration to Query-by-Collaboration

Summary: Proposes decentralized query answering: autonomous agents as intelligent source interfaces collaborating via a Query Collaboration Protocol instead of centralized integration. Gives design principles and QCP; QCP-DB prototype matches integrated-system accuracy on heterogeneous/noisy sources while eliminating data-integration costs. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
h7af450ae77e7b0b3
Venue
CIDR
Year
2026
Pagerank
5.2283159e-05
Overall Rank
9,065 | 39.06%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{eckmann_cidr26,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '26},
        title = {{A Vision for Autonomous Data Agent Collaboration: From Query-by-Integration to Query-by-Collaboration}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Eckmann, Timo and Binnig, Carsten},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
11,034 Data Agents: Rethinking Data Systems in the AI Agent Era 2026 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
427 Big Data Integration 2013 VLDB 0.00018465558
2,158 Open Data Integration 2018 VLDB 8.941016e-05
3,423 AutoTQA: Towards Autonomous Tabular Question Answering through Multi-Agent Large Language Models 2024 VLDB 7.313499e-05
7,301 Mind the Data Gap: Bridging LLMs to Enterprise Data Integration 2025 CIDR 5.5602724e-05
Previous Page 1 / 1 Next

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