'Fitness for Use' of Data Objects Described with Quality Maturity Matrix at Different Phases of Data Production
Fitness for use information should be stored to enable easy identification of data objects that are suitable for re-use – a feature which can only be assessed by the data user. With the described Quality Maturity Matrix (QMM), we want to provide a metric for a discrete measurement of the fitness for...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Ubiquity Press
2020-11-01
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| Series: | Data Science Journal |
| Subjects: | |
| Online Access: | https://datascience.codata.org/articles/1161 |
| _version_ | 1818844822739353600 |
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| author | Heinke Höck Frank Toussaint Hannes Thiemann |
| author_facet | Heinke Höck Frank Toussaint Hannes Thiemann |
| author_sort | Heinke Höck |
| collection | DOAJ |
| description | Fitness for use information should be stored to enable easy identification of data objects that are suitable for re-use – a feature which can only be assessed by the data user. With the described Quality Maturity Matrix (QMM), we want to provide a metric for a discrete measurement of the fitness for use of data objects. We use the data maturity to describe the degree of formalization and standardization of the data with respect to the quality of data and metadata. The data objects mature as they pass through the different post-production steps where they undergo different curation measures. The higher the maturity and the level in the QMM, the easier is it for the user to judge the appropriateness of the data for a possible re-use. For our development of the Quality Maturity Matrix we link the maturity levels to the five phases concept, production/processing, project collaboration/intended use, long-term archiving, and impact re-use. Each of the five levels is measured with regard to the four criteria consistency, completeness, accessibility, and accuracy. For the description we use the terms of the Open Archival Information System (OAIS). We relate our data focused QMM to some existing maturity matrices which put the focus on the maturity of the curation process rather than of the data objects themselves. In addition, we make an attempt to establish a connection between the QMM criteria of data assessment and the FAIR Data principles. |
| first_indexed | 2024-12-19T05:19:52Z |
| format | Article |
| id | doaj.art-8df50702f8084d798703bd569d73b8cf |
| institution | Directory Open Access Journal |
| issn | 1683-1470 |
| language | English |
| last_indexed | 2024-12-19T05:19:52Z |
| publishDate | 2020-11-01 |
| publisher | Ubiquity Press |
| record_format | Article |
| series | Data Science Journal |
| spelling | doaj.art-8df50702f8084d798703bd569d73b8cf2022-12-21T20:34:31ZengUbiquity PressData Science Journal1683-14702020-11-0119110.5334/dsj-2020-045800'Fitness for Use' of Data Objects Described with Quality Maturity Matrix at Different Phases of Data ProductionHeinke Höck0Frank Toussaint1Hannes Thiemann2Data Management, World Data Center for Climate (WDCC); Deutsches Klimarechenzentrum (DKRZ), HamburgData Management, World Data Center for Climate (WDCC); Deutsches Klimarechenzentrum (DKRZ), HamburgData Management, World Data Center for Climate (WDCC); Deutsches Klimarechenzentrum (DKRZ), HamburgFitness for use information should be stored to enable easy identification of data objects that are suitable for re-use – a feature which can only be assessed by the data user. With the described Quality Maturity Matrix (QMM), we want to provide a metric for a discrete measurement of the fitness for use of data objects. We use the data maturity to describe the degree of formalization and standardization of the data with respect to the quality of data and metadata. The data objects mature as they pass through the different post-production steps where they undergo different curation measures. The higher the maturity and the level in the QMM, the easier is it for the user to judge the appropriateness of the data for a possible re-use. For our development of the Quality Maturity Matrix we link the maturity levels to the five phases concept, production/processing, project collaboration/intended use, long-term archiving, and impact re-use. Each of the five levels is measured with regard to the four criteria consistency, completeness, accessibility, and accuracy. For the description we use the terms of the Open Archival Information System (OAIS). We relate our data focused QMM to some existing maturity matrices which put the focus on the maturity of the curation process rather than of the data objects themselves. In addition, we make an attempt to establish a connection between the QMM criteria of data assessment and the FAIR Data principles.https://datascience.codata.org/articles/1161data managementfitness for usedata production stepsquality maturity matrixfair data principles |
| spellingShingle | Heinke Höck Frank Toussaint Hannes Thiemann 'Fitness for Use' of Data Objects Described with Quality Maturity Matrix at Different Phases of Data Production Data Science Journal data management fitness for use data production steps quality maturity matrix fair data principles |
| title | 'Fitness for Use' of Data Objects Described with Quality Maturity Matrix at Different Phases of Data Production |
| title_full | 'Fitness for Use' of Data Objects Described with Quality Maturity Matrix at Different Phases of Data Production |
| title_fullStr | 'Fitness for Use' of Data Objects Described with Quality Maturity Matrix at Different Phases of Data Production |
| title_full_unstemmed | 'Fitness for Use' of Data Objects Described with Quality Maturity Matrix at Different Phases of Data Production |
| title_short | 'Fitness for Use' of Data Objects Described with Quality Maturity Matrix at Different Phases of Data Production |
| title_sort | fitness for use of data objects described with quality maturity matrix at different phases of data production |
| topic | data management fitness for use data production steps quality maturity matrix fair data principles |
| url | https://datascience.codata.org/articles/1161 |
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