Data Quality as a Critical Success Factor for User Acceptance of Research Information Systems
Autor: | Joachim Schöpfel, Otmane Azeroual, Gunter Saake, Mohammad Abuosba |
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Přispěvatelé: | German Center for Higher Education Research and Science Studies (DZHW), Otto-von-Guericke-Universität Magdeburg, University of Applied Sciences [Berlin] (HTW), Groupe d'Études et de Recherche Interdisciplinaire en Information et COmmunication - ULR 4073 (GERIICO ), Université de Lille, Otto-von-Guericke-Universität Magdeburg = Otto-von-Guericke University [Magdeburg] (OVGU) |
Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Data cleansing
Information Systems and Management user acceptance Computer science [SHS.INFO]Humanities and Social Sciences/Library and information sciences 02 engineering and technology 050905 science studies computer.software_genre case study Critical success factor 0202 electrical engineering electronic engineering information engineering Research information research information systems (RIS) Statement (computer science) [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB] 05 social sciences RIS implementation Data science lcsh:Z Computer Science Applications lcsh:Bibliography. Library science. Information resources Data profiling Work (electrical) research information quality system quality Data quality Data wrangling 020201 artificial intelligence & image processing 0509 other social sciences computer Information Systems |
Zdroj: | Data Data, MDPI, 2020, 5 (2), pp.35. ⟨10.3390/data5020035⟩ Data, 2020, 5 (2), pp.35. ⟨10.3390/data5020035⟩ Volume 5 Issue 2 Data, Vol 5, Iss 35, p 35 (2020) |
ISSN: | 2306-5729 |
DOI: | 10.3390/data5020035⟩ |
Popis: | International audience; In our present paper, the influence of data quality on the success of the user acceptance of research information systems (RIS) is investigated and determined. Until today, only a little research has been done on this topic and no studies have been carried out. So far, just the importance of data quality in RIS, the investigation of its dimensions and techniques for measuring, improving, and increasing data quality in RIS (such as data profiling, data cleansing, data wrangling, and text data mining) has been focused. With this work, we try to derive an answer to the question of the impact of data quality on the success of RIS user acceptance. An acceptance of RIS users is achieved when the research institutions decide to replace the RIS and replace it with a new one. The result is a statement about the extent to which data quality influences the success of users' acceptance of RIS. |
Databáze: | OpenAIRE |
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