Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research Environment
At-risk data is an unfortunate research reality and can be present in all data formats in a range of research disciplines. This is defined as data that are at risk of loss due to various factors, including deterioration of the media, lack of accompanying documentation and data that exists in non-dig...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Ubiquity Press
2024-03-01
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| Series: | Data Science Journal |
| Subjects: | |
| Online Access: | https://account.datascience.codata.org/index.php/up-j-dsj/article/view/1543 |
| _version_ | 1797202876378906624 |
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| author | Louise H. Patterton Theo J. D. Bothma Martie J. van Deventer |
| author_facet | Louise H. Patterton Theo J. D. Bothma Martie J. van Deventer |
| author_sort | Louise H. Patterton |
| collection | DOAJ |
| description | At-risk data is an unfortunate research reality and can be present in all data formats in a range of research disciplines. This is defined as data that are at risk of loss due to various factors, including deterioration of the media, lack of accompanying documentation and data that exists in non-digital formats, which are often irreplaceable. Continued access to older data has a range of benefits. The factors that place valuable data at risk are therefore a cause for concern. This paper reports on a multi-method case study, comprising a survey and interviews. A web-based questionnaire was distributed to all research group leaders based at a leading South African research institute. This was followed by one-on-one interviews that were held with a sub-section of the same group of researchers. The combined findings of the two methods enabled a picture to be formed regarding factors that jeopardise research data, data rescue obstacles that the researchers encountered and the state of data rescue at the institute. Several recommendations and strategies are put forward to address identified risk factors and challenges. Suggestions include the launch of a data rescue project, awareness training around data at risk, involving the institute’s library and information services (LIS) section in data rescue and launching continued efforts to acquire a dedicated institutional data repository. It is also important to ensure that the scope of project risk management includes data considerations. The combined implementation of recommendations is anticipated to ensure the accessibility and usability of older at-risk data and reduce the chances of current and future data becoming compromised. |
| first_indexed | 2024-04-24T08:10:24Z |
| format | Article |
| id | doaj.art-387cae991523426d9f8c86468aabd64c |
| institution | Directory Open Access Journal |
| issn | 1683-1470 |
| language | English |
| last_indexed | 2024-04-24T08:10:24Z |
| publishDate | 2024-03-01 |
| publisher | Ubiquity Press |
| record_format | Article |
| series | Data Science Journal |
| spelling | doaj.art-387cae991523426d9f8c86468aabd64c2024-04-17T06:43:22ZengUbiquity PressData Science Journal1683-14702024-03-0123111110.5334/dsj-2024-011184Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research EnvironmentLouise H. Patterton0https://orcid.org/0000-0002-8067-8545Theo J. D. Bothma1https://orcid.org/0000-0001-7850-3263Martie J. van Deventer2https://orcid.org/0000-0002-9776-1177Department of Information Science, University of Pretoria, Pretoria; Council for Scientific and Industrial ResearchDepartment of Information Science, University of Pretoria, PretoriaDepartment of Information Science, University of Pretoria, PretoriaAt-risk data is an unfortunate research reality and can be present in all data formats in a range of research disciplines. This is defined as data that are at risk of loss due to various factors, including deterioration of the media, lack of accompanying documentation and data that exists in non-digital formats, which are often irreplaceable. Continued access to older data has a range of benefits. The factors that place valuable data at risk are therefore a cause for concern. This paper reports on a multi-method case study, comprising a survey and interviews. A web-based questionnaire was distributed to all research group leaders based at a leading South African research institute. This was followed by one-on-one interviews that were held with a sub-section of the same group of researchers. The combined findings of the two methods enabled a picture to be formed regarding factors that jeopardise research data, data rescue obstacles that the researchers encountered and the state of data rescue at the institute. Several recommendations and strategies are put forward to address identified risk factors and challenges. Suggestions include the launch of a data rescue project, awareness training around data at risk, involving the institute’s library and information services (LIS) section in data rescue and launching continued efforts to acquire a dedicated institutional data repository. It is also important to ensure that the scope of project risk management includes data considerations. The combined implementation of recommendations is anticipated to ensure the accessibility and usability of older at-risk data and reduce the chances of current and future data becoming compromised.https://account.datascience.codata.org/index.php/up-j-dsj/article/view/1543data at riskdata rescuehistoric datalegacy dataresearch data management |
| spellingShingle | Louise H. Patterton Theo J. D. Bothma Martie J. van Deventer Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research Environment Data Science Journal data at risk data rescue historic data legacy data research data management |
| title | Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research Environment |
| title_full | Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research Environment |
| title_fullStr | Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research Environment |
| title_full_unstemmed | Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research Environment |
| title_short | Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research Environment |
| title_sort | risky business data at risk in a dynamic and evolving multidisciplinary research environment |
| topic | data at risk data rescue historic data legacy data research data management |
| url | https://account.datascience.codata.org/index.php/up-j-dsj/article/view/1543 |
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