Scarce Data in Intelligent Technical Systems: Causes, Characteristics, and Implications
Technical systems generate an increasing amount of data as integrated sensors become more available. Even so, data are still often scarce because of technical limitations of sensors, an expensive labelling process, or rare concepts, such as machine faults, which are hard to capture. Data scarcity le...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Sci |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2413-4155/4/4/49 |
| _version_ | 1797455414453862400 |
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| author | Christoph-Alexander Holst Volker Lohweg |
| author_facet | Christoph-Alexander Holst Volker Lohweg |
| author_sort | Christoph-Alexander Holst |
| collection | DOAJ |
| description | Technical systems generate an increasing amount of data as integrated sensors become more available. Even so, data are still often scarce because of technical limitations of sensors, an expensive labelling process, or rare concepts, such as machine faults, which are hard to capture. Data scarcity leads to incomplete information about a concept of interest. This contribution details causes and effects of scarce data in technical systems. To this end, a typology is introduced which defines different types of incompleteness. Based on this, machine learning and information fusion methods are presented and discussed that are specifically designed to deal with scarce data. The paper closes with a motivation and a call for further research efforts into a combination of machine learning and information fusion. |
| first_indexed | 2024-03-09T15:54:03Z |
| format | Article |
| id | doaj.art-fb015c5e7af6469687d7a7e649fba82f |
| institution | Directory Open Access Journal |
| issn | 2413-4155 |
| language | English |
| last_indexed | 2024-03-09T15:54:03Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sci |
| spelling | doaj.art-fb015c5e7af6469687d7a7e649fba82f2023-11-24T17:51:22ZengMDPI AGSci2413-41552022-12-01444910.3390/sci4040049Scarce Data in Intelligent Technical Systems: Causes, Characteristics, and ImplicationsChristoph-Alexander Holst0Volker Lohweg1inIT—Institute Industrial IT, Technische Hochschule Ostwestfalen-Lippe, Campusallee 6, 32657 Lemgo, GermanyinIT—Institute Industrial IT, Technische Hochschule Ostwestfalen-Lippe, Campusallee 6, 32657 Lemgo, GermanyTechnical systems generate an increasing amount of data as integrated sensors become more available. Even so, data are still often scarce because of technical limitations of sensors, an expensive labelling process, or rare concepts, such as machine faults, which are hard to capture. Data scarcity leads to incomplete information about a concept of interest. This contribution details causes and effects of scarce data in technical systems. To this end, a typology is introduced which defines different types of incompleteness. Based on this, machine learning and information fusion methods are presented and discussed that are specifically designed to deal with scarce data. The paper closes with a motivation and a call for further research efforts into a combination of machine learning and information fusion.https://www.mdpi.com/2413-4155/4/4/49scarce datamachine learninginformation fusion |
| spellingShingle | Christoph-Alexander Holst Volker Lohweg Scarce Data in Intelligent Technical Systems: Causes, Characteristics, and Implications Sci scarce data machine learning information fusion |
| title | Scarce Data in Intelligent Technical Systems: Causes, Characteristics, and Implications |
| title_full | Scarce Data in Intelligent Technical Systems: Causes, Characteristics, and Implications |
| title_fullStr | Scarce Data in Intelligent Technical Systems: Causes, Characteristics, and Implications |
| title_full_unstemmed | Scarce Data in Intelligent Technical Systems: Causes, Characteristics, and Implications |
| title_short | Scarce Data in Intelligent Technical Systems: Causes, Characteristics, and Implications |
| title_sort | scarce data in intelligent technical systems causes characteristics and implications |
| topic | scarce data machine learning information fusion |
| url | https://www.mdpi.com/2413-4155/4/4/49 |
| work_keys_str_mv | AT christophalexanderholst scarcedatainintelligenttechnicalsystemscausescharacteristicsandimplications AT volkerlohweg scarcedatainintelligenttechnicalsystemscausescharacteristicsandimplications |