On Big Data guided Unconventional Digital Ecosystems and their Knowledge Management
dc.contributor.author | Nimmagadda, Shastri | |
dc.contributor.author | Reiners, Torsten | |
dc.contributor.author | Wood, Lincoln | |
dc.contributor.author | Zhu, Dengya | |
dc.date.accessioned | 2020-09-24T09:18:38Z | |
dc.date.available | 2020-09-24T09:18:38Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Nimmagadda, S. and Reiners, T. and Wood, L.C. and Zhu, D. 2019. On Big Data guided Unconventional Digital Ecosystems and their Knowledge Management, in Proceedings of the Twenty-Third Pacific Asia Conference of Information Systems (PACIS), Jul 8-12 2019. Xi’an, China: AIS. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/81146 | |
dc.description.abstract |
© Proceedings of the 23rd Pacific Asia Conference on Information Systems: Secure ICT Platform for the 4th Industrial Revolution, PACIS 2019. Establishing the reservoir connections is paramount in exploration and exploitation of unconventional petroleum systems and their reservoirs. In Big Data scale, multiple petroleum systems hold volumes and varieties of data sources. The connectivity between petroleum reservoirs and their existence in a single petroleum ecosystem is often ambiguously interpreted. They are heterogeneous and unstructured in multiple domains. They need better data integration methods to interpret the interplay between elements and processes of petroleum systems. Large-scale infrastructure is needed to build data relationships between different petroleum systems. The purpose of the research is to establish the connectivity between petroleum systems through resource data management and visual analytics. We articulate a Design Science Information System (DSIS) approach, bringing various artefacts together from multiple domains of petroleum provinces. The DSIS emerges as a knowledge-based digital ecosystem innovation, justifying its need, connecting geographically controlled petroleum systems and building knowledge of oil and gas prospects. | |
dc.relation.uri | https://aisel.aisnet.org/pacis2019/7 | |
dc.title | On Big Data guided Unconventional Digital Ecosystems and their Knowledge Management | |
dc.type | Conference Paper | |
dcterms.source.title | Proceedings of the 23rd Pacific Asia Conference on Information Systems: Secure ICT Platform for the 4th Industrial Revolution, PACIS 2019 | |
dcterms.source.conference | Pacific-Asian Conference of Information Systems (PACIS) | |
dcterms.source.conferencelocation | Xian, China | |
dc.date.updated | 2020-09-24T09:18:37Z | |
curtin.department | School of Management | |
curtin.accessStatus | Open access via publisher | |
curtin.faculty | Faculty of Business and Law | |
curtin.contributor.orcid | Reiners, Torsten [0000-0001-6243-4267] | |
curtin.contributor.orcid | Zhu, Dengya [0000-0003-0818-437X] | |
curtin.contributor.orcid | Nimmagadda, Shastri [0000-0002-0841-6727] | |
curtin.contributor.researcherid | Reiners, Torsten [G-3035-2012] | |
curtin.contributor.scopusauthorid | Reiners, Torsten [6603378573] | |
curtin.contributor.scopusauthorid | Wood, Lincoln [14065413700] | |
curtin.contributor.scopusauthorid | Zhu, Dengya [22037238600] | |
curtin.contributor.scopusauthorid | Nimmagadda, Shastri [23490052500] |