Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 82 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 14 tok/s Pro
GPT-5 High 16 tok/s Pro
GPT-4o 117 tok/s Pro
Kimi K2 200 tok/s Pro
GPT OSS 120B 469 tok/s Pro
Claude Sonnet 4 36 tok/s Pro
2000 character limit reached

CRISTAL-ISE : Provenance Applied in Industry (1402.6742v1)

Published 26 Feb 2014 in cs.DB and cs.SE

Abstract: This paper presents the CRISTAL-iSE project as a framework for the management of provenance information in industry. The project itself is a research collaboration between academia and industry. A key factor in the project is the use of a system known as CRISTAL which is a mature system based on proven description driven principles. A crucial element in the description driven approach is that the fact that objects (Items) are described at runtime enabling managed systems to be both dynamic and flexible. Another factor is the notion that all Items in CRISTAL are stored and versioned, therefore enabling a provenance collection system. In this paper a concrete application, called Agilium, is briefly described and a future application CIMAG-RA is presented which will harness the power of both CRISTAL and Agilium.

Citations (14)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

We haven't generated follow-up questions for this paper yet.