Research data and metadata curation as institutional issues
Research data and metadata curation as institutional issues
复制标题
研究数据和元数据管理作为制度问题
DOI：
10.1002/asi.23425
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发表时间：
2016
影响因子：
3.5
通讯作者：
M. Mayernik
中科院分区：
文献类型：
--
作者：
M. Mayernik
研究数据管理举措必须支持不同种类的项目、数据和元数据。本文以“制度”作为关键理论概念，考察数据和元数据实践中的差异。这里所使用的“制度”是指人类行为的稳定模式，它在特定情境下构建、合法化或非法化行为、关系和理解。基于对制度的已有概念化，提出了一个理论框架，该框架概述了数据实践的5类“制度载体”：(a)规范和符号，(b)中介，(c)惯例，(d)标准，(e)物质对象。这些制度载体对于理解科学数据和元数据实践如何产生、稳定、演变和转移至关重要。这个制度框架应用于3个案例研究：嵌入式网络传感中心（CENS）、长期生态研究（LTER）网络以及大气研究大学联合体（UCAR）。这些案例用于说明在一个单一组织或学科内，对数据和元数据管理的制度支持并非是统一的。相反，在学科和组织内部及之间存在着管理数据和元数据的广泛制度配置。
Research data curation initiatives must support heterogeneous kinds of projects, data, and metadata. This article examines variability in data and metadata practices using “institutions” as the key theoretical concept. Institutions, in the sense used here, are stable patterns of human behavior that structure, legitimize, or delegitimize actions, relationships, and understandings within particular situations. Based on prior conceptualizations of institutions, a theoretical framework is presented that outlines 5 categories of “institutional carriers” for data practices: (a) norms and symbols, (b) intermediaries, (c) routines, (d) standards, and (e) material objects. These institutional carriers are central to understanding how scientific data and metadata practices originate, stabilize, evolve, and transfer. This institutional framework is applied to 3 case studies: the Center for Embedded Networked Sensing (CENS), the Long Term Ecological Research (LTER) network, and the University Corporation for Atmospheric Research (UCAR). These cases are used to illustrate how institutional support for data and metadata management are not uniform within a single organization or academic discipline. Instead, broad spectra of institutional configurations for managing data and metadata exist within and across disciplines and organizations.