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A Semantic Workflow Approach to Web Science Analytics

Published: 25 June 2017 Publication History

Abstract

Reproducibility and reuse are rapidly becoming guiding principles in publishing and sharing scientific results. In order to enhance researchers' ability to leverage existing results, many are moving in the direction of semantic workflow systems, which enable users to define and share experimental procedures as linked data on the Web. These workflows provide a powerful mechanism for reproducing experiments and thus are well-suited for Web Science tasks. In order to aid users in the process of experiment design and reproduction, we are integrating the Workflow INstance Generation and Specialization (WINGS) system with our existing Semantic Numeric Exploration Technology (SemNExT) framework. This will provide a completely open-source stack for designing in silico experiments using a combination of semantic and numeric analyses. We will explore how this system may be configured to create reproducible Web Science workflows, especially as it pertains to data federation across the Web. We are leveraging our existing tooling as we develop new approaches for automatically generating provenance for interacting with remote endpoints of heterogeneous data sources. This will support not only the aggregation of diverse and geographically-disparate data sources across the Web, but also collaborative science by allowing other users to reproduce and expand on the same results using shared workflows.

References

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Daniel Garijo, Sarah Kinnings, Li Xie, Lei Xie, Yinliang Zhang, Philip E. Bourne, and Yolanda Gil. 2013. Quantifying reproducibility in computational biology: The case of the tuberculosis drugome. PLoS ONE 8, 11 (2013).
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Yolanda Gil, Varun Ratnakar, and Christian Fritz. 2010. Assisting Scientists with Complex Data Analysis Tasks through Semantic Workflows. In AAAI Fall Symposium: Proactive Assistant Agents. Citeseer.
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Yolanda Gil, Varun Ratnakar, Jihie Kim, Pedro González-Calero, Paul Groth, Joshua Moody, and Ewa Deelman. 2011. Wings: Intelligent workflow-based design of computational experiments. IEEE Intelligent Systems 26, 1 (2011), 62--72.
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Graham Klyne and Jeremy J Carroll. 2004. Resource Description Framework (RDF): Concepts and Abstract Syntax. W3C Recommendation 10, October (2004), 1--20. http://www.w3.org/TR/2004/REC-rdf-concepts-20040210/
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cover image ACM Conferences
WebSci '17: Proceedings of the 2017 ACM on Web Science Conference
June 2017
438 pages
ISBN:9781450348966
DOI:10.1145/3091478
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 June 2017

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  1. data federation
  2. reproducibility
  3. semantic workflows

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WebSci '17
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WebSci '17: ACM Web Science Conference
June 25 - 28, 2017
New York, Troy, USA

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WebSci '17 Paper Acceptance Rate 30 of 85 submissions, 35%;
Overall Acceptance Rate 245 of 933 submissions, 26%

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