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Data Literacy Assessment - Measuring Data Literacy Competencies to Leverage Data-Driven Organizations
Lara Pörtner, Andreas Riel, Vivian Klaassen, Dilara Sezgin, Ysaline Kievits

Data Literacy Assessment - Measuring Data Literacy Competencies to Leverage Data-Driven Organizations

Science & Mathematics Published 2024 Verification Pending

Overview & Synopsis

In today's rapidly evolving data-driven landscape, the ability to understand, analyze, and interpret data is more important than ever. With an everincreasing amount of data being generated and collected at an unprecedented rate, both individuals and organizations are forced to develop a high level of data literacy. Data literacy, as the ability to work with, analyze, understand, use, and argue with data, is therefore the key not to drown in data. A detailed data literacy assessment can provide companies with a significant advantage and push their daily and data-related activities to a mature level. A literature review of existing data literacy frameworks with their competencies underscore the need for a flexible and adaptable approach to data literacy that considers the diverse needs and contexts of different stakeholders. While there is no one-size-fits-all assessment, the frameworks outlined in this review provide a useful starting point for developing a common language and set of data literacy skills. The purpose of this paper is to put an accent on the importance of data literacy by introducing an assessment of competencies applicable in different industry sectors that can sustainably support companies to make them realize the need for data literacy and for leveraging their skills. The competencies as part of a data literacy framework as a whole will be applied and validated in different industry sectors for continuous improvement in future research.

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Document Information

Document Title Data Literacy Assessment - Measuring Data Literacy Competencies to Leverage Data-Driven Organizations
Author / Organization Lara Pörtner, Andreas Riel, Vivian Klaassen, Dilara Sezgin, Ysaline Kievits
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2024
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-211044
Original Source Link Visit Source Page on hal.science »