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Authors: Stefan Pröll 1 and Andreas Rauber 2

Affiliations: 1 SBA Research and Technical University of Vienna, Austria ; 2 SBA Research, Austria

Keyword(s): Research Data Citation, Subset Versioning, Subset Authenticity, Data Sharing.

Related Ontology Subjects/Areas/Topics: Data Curation ; Data Engineering ; Data Management and Quality ; Information Quality ; Open Data ; Transparency in Research Data

Abstract: Sharing research data is becoming increasingly important as it enables peers to validate and reproduce data driven experiments. Also exchanging data allows scientists to reuse data in different contexts and gather new knowledge from available sources. But with increasing volume of data, researchers need to reference exact versions of datasets. Until now access to research data often based on single archives of data files where versioning and subsetting support is limited. In this paper we introduce a mechanism that allows researchers to create versioned subsets of research data which can be cited and shared in a lightweight manner. We demonstrate a prototype that supports researchers in creating subsets based on filtering and sorting source data. These subsets can be cited for later reference and reuse. The system produces evidence that allows users to verify the correctness and completeness of a subset based on cryptographic hashing. We describe a replication scenario for enabling s calable data citation in dynamic contexts. (More)

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Paper citation in several formats:
Pröll, S. and Rauber, A. (2014). A Scalable Framework for Dynamic Data Citation of Arbitrary Structured Data. In Proceedings of 3rd International Conference on Data Management Technologies and Applications - DATA; ISBN 978-989-758-035-2; ISSN 2184-285X, SciTePress, pages 223-230. DOI: 10.5220/0004991802230230

@conference{data14,
author={Stefan Pröll. and Andreas Rauber.},
title={A Scalable Framework for Dynamic Data Citation of Arbitrary Structured Data},
booktitle={Proceedings of 3rd International Conference on Data Management Technologies and Applications - DATA},
year={2014},
pages={223-230},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004991802230230},
isbn={978-989-758-035-2},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of 3rd International Conference on Data Management Technologies and Applications - DATA
TI - A Scalable Framework for Dynamic Data Citation of Arbitrary Structured Data
SN - 978-989-758-035-2
IS - 2184-285X
AU - Pröll, S.
AU - Rauber, A.
PY - 2014
SP - 223
EP - 230
DO - 10.5220/0004991802230230
PB - SciTePress

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