Research Data Curation in Visualization : Position Paper

Dimitar Garkov, C. Müller, Matthias Braun, D. Weiskopf, Falk Schreiber
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Abstract

Research data curation is the act of carefully preparing research data and artifacts for sharing and long-term preservation. Research data management is centrally implemented and formally defined in a data management plan to enable data curation. In tandem, data curation and management facilitate research repeatability. In contrast to other research fields, data curation and management in visualization are not yet part of the researcher’s compendium. In this position paper, we discuss the unique challenges visualization faces and propose how data curation can be practically realized. We share eight lessons learned in managing data in two large research consortia, outline the larger curation workflow, and define the typical roles. We complement our lessons with minimum criteria for selecting a suitable data repository and five challenging scenarios that occur in practice. We conclude with a vision of how the visualization research community can pave the way for new curation standards.
可视化中的研究数据管理:立场文件
研究数据管理是为了共享和长期保存而精心准备研究数据和人工制品的行为。研究数据管理集中实施,并在数据管理计划中正式定义,以实现数据管理。同时,数据管理和管理促进了研究的可重复性。与其他研究领域相比,可视化中的数据管理和管理尚未成为研究人员纲要的一部分。在这篇意见书中,我们讨论了可视化面临的独特挑战,并提出了如何实际实现数据管理。我们分享了在两个大型研究联盟中管理数据的八个经验教训,概述了更大的管理工作流程,并定义了典型的角色。我们用选择合适的数据存储库的最低标准和实践中发生的五个具有挑战性的场景来补充我们的课程。最后,我们展望了可视化研究界如何为新的策展标准铺平道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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