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Show simple item record Schmitz, P Scheepers, L de Wit, PWC De la Rey, A 2007-11-07T12:49:17Z 2007-11-07T12:49:17Z 2007-09
dc.identifier.citation Schmitz, PMU et al. 2007. Understanding data supply chains by using the Supply-Chain Operations Reference (SCOR) model. Logistics Research Network Annual Conference, Hull, United Kingdom, September 5-7 2007, pp 6 en
dc.description 2007: Logistics Research Network Annual Conference, UK en
dc.description.abstract Spatial data such as roads and land parcels is increasingly becoming a commodity that is being created with the aim to sell or to provide spatial information to other institutions for further processing or to decision makers to aid in their decision processes. This paper looks into the spatial data supply chain of ESI-GIS unit of Eskom and the use of an adapted SCOR model (GISDataSCOR) to model and analyse the supply chain. Spatial data needs to be sourced from various sources (SOURCE), which is then stored in a data warehouse. The spatial data is then sourced from the data warehouse and transformed into a new spatial data set using Geographic Information Systems (GIS) (MAKE) and the new spatial data set is delivered to a customer (DELIVER). RETURN in this environment deals only with defective data sets. It is of the opinion from the researchers that data as a commodity will play an important part of the future economies and that data supply chains are one of the supply chains of the future and that supply chain management is going to play prominent role in ensuring that data is sourced, created and delivered efficiently and effectively. en
dc.language.iso en en
dc.subject Geographic information systems en
dc.subject Supply chains en
dc.subject Supply chain management en
dc.subject Spatial data en
dc.subject SCOR en
dc.subject Supply-chain operations reference en
dc.title Understanding data supply chains by using the Supply-Chain Operations Reference (SCOR) model en
dc.type Presentation en

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