A Software Engineering Perspective on Data Quality Processes in Environmental Research - Recommendations Based on Software Engineering Practices Applied for Improving of Open Data Practices and Communication in Environmental Research

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dc.contributor.authorMOEN, MARKUS
dc.contributor.authorNORÉN, MAX
dc.contributor.departmentChalmers tekniska högskola / Institutionen för data och informationstekniksv
dc.contributor.departmentChalmers University of Technology / Department of Computer Science and Engineeringen
dc.contributor.examinerPenzenstadler, Birgit
dc.contributor.supervisorHeyn, Hans-Martin
dc.date.accessioned2024-09-18T16:16:20Z
dc.date.available2024-09-18T16:16:20Z
dc.date.issued2024
dc.date.submitted
dc.description.abstractThe many fields within environmental research have been on the path towards open science and, most importantly, open data. With the increase in available data, there are opportunities to apply data-driven and data-intensive methods, including recent developments such as machine learning. However, the success of applying machine learning depends significantly on the quality of the available training data. The purpose of this thesis was to investigate the field of environmental research in regards to current views, practices and communication of data quality and to identify software engineering principles and practices that can form possible recommendations to progress data quality in environmental research. This process identified six challenges and proposed eight recommendations. The result shows a great deal of effort towards open data, with the FAIR principles as the main arbiter to achieve it. Most identified challenges are based on data quality handling, communication, and difficulties in achieving open science. We found suitable software engineering practices for four of the six challenges, with two key perspectives being derived from open source software and requirements engineering practices. Our results demonstrate that there is a willingness among environmental researchers to investigate and adopt software engineering practices in environmental research. Importantly, there is a broad agreement that open science is an improvement over to previous methods, and the stated challenges and recommendations need to preserve those advancements. The recommendations should be regarded as a first design iteration of these recommendations, and they should be explored further in terms of their applicability to different fields within environmental research.
dc.identifier.coursecodeDATX05
dc.identifier.urihttp://hdl.handle.net/20.500.12380/308697
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectSoftware engineering
dc.subjectrequirements engineering
dc.subjectdata quality
dc.subjectenvironmental research
dc.subjectopen science
dc.subjectopen data
dc.subjectdata-intensive
dc.subjectbig data
dc.subjectFAIR
dc.subjectthesis
dc.titleA Software Engineering Perspective on Data Quality Processes in Environmental Research - Recommendations Based on Software Engineering Practices Applied for Improving of Open Data Practices and Communication in Environmental Research
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster's Thesisen
dc.type.uppsokH
local.programmeSoftware engineering and technology (MPSOF), MSc
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