ORCHESTRA: Rapid, Collaborative Sharing of Dynamic Data
Summary: ORCHESTRA proposes a bottom-up framework for rapid, collaborative scientific data sharing where autonomous groups publish, revise, and extend datasets without a predefined global schema. Novelty: explicit management of disagreement, revision provenance, authority and intermittent participation in a peer-to-peer integration model. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zachary Ives (University of Pennsylvania)
- 2. Nitin Khandelwal (University of Pennsylvania)
- 3. Aneesh Kapur (University of Pennsylvania)
- 4. Murat Cakir (Drexel University; University of Pennsylvania)
BibTeX Citation
@inproceedings{ives_cidr05,
address = {Amsterdam, Netherlands},
series = {{CIDR} '05},
title = {{ORCHESTRA: Rapid, Collaborative Sharing of Dynamic Data}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Ives, Zachary and Khandelwal, Nitin and Kapur, Aneesh and Cakir, Murat},
year = {2005}
}
Incoming Citations (Sorted by Pagerank)
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