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http://hdl.handle.net/1942/43019
Title: | Demystifying Data Governance for Process Mining: Insights from a Delphi Study | Authors: | Goel, Kanika MARTIN, Niels ter Hofstede, Arthur |
Issue Date: | 2024 | Source: | INFORMATION & MANAGEMENT, 61 (Art N° 103973) | Abstract: | Data governance is recognised as a new capability for organisations to maximize the value of data. Process mining is essential for the resilient growth of businesses, making process data a strategic asset for organisations. Even though the availability of reliable process data is vital for obtaining dependable insights into process mining techniques, there exists no framework that explains how to govern process data holistically. We address this gap by presenting the first data governance framework for process mining that was derived from a Delphi study conducted with a panel of academics and practitioners from around the world. The framework provides multiple avenues for future research. | Keywords: | Data governance;Process mining;Delphi study;Process data | Document URI: | http://hdl.handle.net/1942/43019 | ISSN: | 0378-7206 | e-ISSN: | 1872-7530 | DOI: | 10.1016/j.im.2024.103973 | ISI #: | 001292533800001 | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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1-s2.0-S0378720624000557-main.pdf | Published version | 3.09 MB | Adobe PDF | View/Open |
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