Towards big data as official statistics: Case study of the use of mobile positioning data to delineate metropolitan areas in Indonesia
| Autor: | Ade Koswara, Isnaeni Noviyanti, Dwi Puspita Sari, Edi Setiawan, Titi Kanti Lestari, M. Hanif Fahyuananto, Panca D. Prabawa |
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| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Statistical Journal of the IAOS. 36:943-954 |
| ISSN: | 1875-9254 1874-7655 |
| Popis: | Nowadays, the use of so-called big data as a new data source to complement official statistics has become an opportunity for organizations focusing on statistics. The use of big data can lead to a more efficient data collection. However, currently, there has not been any standard business process for big data collection and processing in BPS-Statistics Indonesia. Meanwhile, the adoption of technologies alone cannot determine the success of big data use. It is widely known that big data use can be challenging, since there are issues regarding data access, quality, and methodology, as well as the development of required skillsets. This paper proposes a framework for a business process that is specifically designed to support the use of big data for official statistics at BPS-Statistics Indonesia along with how existing technology will support it. The development of this framework is based on the wider Statistical Business Process Framework and Architecture (SBFA) developed by BPS-Statistics Indonesia to describe and manage its overall statistical business processes. The paper uses the example of the use of Mobile Positioning Data (MPD) as a big data source to delineate Metropolitan Areas in Indonesia as a way to explain the implementation of the framework. |
| Databáze: | OpenAIRE |
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