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Data Discovery and Indexing for Semi-Structured Scientific Data

Topics: Big Data, Data Science and Analytics; Coupling and Integrating Heterogeneous Data Sources; Domain Specific and Multi-aspect IS Engineering; Enterprise Content Management; Interface Design; Knowledge Management; Non-Relational Databases; Tools, Techniques and Methodologies for System Development

Authors: Kaushik Jagini 1 ; Yifan Zhang 1 ; Yichen Guo 2 ; Julian Goddy 3 ; Dale Stansberry 4 ; Joshua Agar 3 and Jeff Heflin 1

Affiliations: 1 Computer Science and Engineering, Lehigh University, Bethlehem, PA, U.S.A. ; 2 Materials Science and Engineering, Lehigh University, Bethlehem, PA, U.S.A. ; 3 Mechanical Engineering and Mechanics, Drexel University, Philadelphia, PA, U.S.A. ; 4 National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, U.S.A.

Keyword(s): Scientific Data Discovery, Data-Centric Indexing, Federated Data, User Interface, Semi-Structured Data.

Abstract: There is a need for powerful, user-friendly tools for scientific data management and discovery. We present an architecture based on DataFed and Elasticsearch that allows scientists to easily share data they produce and a novel interface that allows other scientists to easily discover data of interest. This interface supports summary-level information about a collection of datasets that can be easily refined using schema-free search. We extend the recent idea of cell-centric search to semi-structured data, describe the architecture of the system, present a use case from the context of materials science, and evaluate the efficacy of the system.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Jagini, K.; Zhang, Y.; Guo, Y.; Goddy, J.; Stansberry, D.; Agar, J. and Heflin, J. (2024). Data Discovery and Indexing for Semi-Structured Scientific Data. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-692-7; ISSN 2184-4992, SciTePress, pages 264-271. DOI: 10.5220/0012706000003690

@conference{iceis24,
author={Kaushik Jagini. and Yifan Zhang. and Yichen Guo. and Julian Goddy. and Dale Stansberry. and Joshua Agar. and Jeff Heflin.},
title={Data Discovery and Indexing for Semi-Structured Scientific Data},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2024},
pages={264-271},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012706000003690},
isbn={978-989-758-692-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Data Discovery and Indexing for Semi-Structured Scientific Data
SN - 978-989-758-692-7
IS - 2184-4992
AU - Jagini, K.
AU - Zhang, Y.
AU - Guo, Y.
AU - Goddy, J.
AU - Stansberry, D.
AU - Agar, J.
AU - Heflin, J.
PY - 2024
SP - 264
EP - 271
DO - 10.5220/0012706000003690
PB - SciTePress