ABSTRACT

Data are often vividly depicted as strategic assets that organisations can (re)use to create value for myriad purposes. However, the same qualities that make data so appreciated – that is, their volume, their value for a plurality of stakeholders and their indefinite reuse capacity – also have a dark side: data reuse can lead to deviant data use that undermines the legitimacy of data analytics initiatives. To investigate this dynamic, we build on the notion of data ecosystems and provide empirical evidence from a longitudinal, 15-year case study of the emergence, expansion and eventual collapse of a large-scale data analytics project – called DAMD – in the Danish health care sector. We demonstrate that data reuse in the evolving data ecosystem elicited a data reuse dark side that was so dominant that it eventually resulted in the project’s demise. We conceptualise the reuse dark side’s three major mechanisms as function creep, stakeholder creep and data creep. Based on these insights, we develop an empirically grounded Data Analytics Ecosystem Model that extends the current understanding of data ecosystems and provides a view of these ecosystems as having both a bright and a dark side.

摘要

数据通常被生动地描述为组织可以（再）用于为无数目的创造价值的战略资产。然而，使数据如此受重视的相同品质——即它们的数量、它们对多个利益相关者的价值以及它们无限的重用能力——也有一个阴暗面：数据重用会导致数据使用的偏差，从而破坏数据的合法性分析举措。为了研究这种动态，我们以数据生态系统的概念为基础，并从一个名为DAMD的大型数据分析项目的出现、扩展和最终崩溃的 15 年纵向案例研究中提供经验证据– 在丹麦的医疗保健部门。我们证明，不断发展的数据生态系统中的数据重用引发了数据重用的阴暗面，这种阴暗面如此占主导地位，最终导致项目的终结。我们将复用黑暗面的三个主要机制概念化为功能蠕变、利益相关者蠕变和数据蠕变。基于这些见解，我们开发了一个以经验为基础的数据分析生态系统模型，该模型扩展了当前对数据生态系统的理解，并提供了这些生态系统既有光明面又有黑暗面的观点。