In 2015, the United Nations (UN) put forward 17 Sustainable Development Goals (SDGs) to beachieved by 2030. Each member state should spare no effort to fulfill the goals for better lives. Thefirst objective of this study was to explore how Big Data could be used to monitor the progress,including the opportunities and challenges that such novel technologies brought. Previous studieswere reviewed critically for the first objective. The second objective was to find out what datainfrastructures were helpful in monitoring the achievement of SDG 7. A systematic mapping studywas performed to accomplish the second objective. 53 SDG-related academic papers were obtained.Their research data and where they were sourced from were manually analyzed and categorized togenerate data infrastructures for SDG 7. Besides, the automated qualitative coding was conductedbased on the manual structure to verify the manually identified data infrastructures and comparetheir frequencies in the selected papers. The methodology of combining manual and automatedqualitative analysis proposed in this study helped find a list of SDG 7 related data infrastructures.Although there were differences between the manual and automated results, the World Bank, UNdatabases, Eurostat, and IEA were considered the most frequently referred data sources; electricitydata and satellite imagery were regarded as the most commonly used data types.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-477148 |
| Date | January 2022 |
| Creators | Jiang, Yuwei |
| Publisher | Uppsala universitet, Institutionen för informatik och media |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0024 seconds