Data management efforts such as Master Data Management and Data Curation are a popular approach for high quality enterprise data. However, Data Curation can be heavily centralised and labour intensive, where the cost and effort can become prohibitively high. The concentration of data management and stewardship onto a few highly skilled individuals, like developers and data experts, can be a significant bottleneck. This talk explores how to effectively involving a wider community of users within big data management activities. The bottom-up approach of involving crowds in the creation and management of data has been demonstrated by projects like Freebase, Wikipedia, and DBpedia. The talk discusses how crowdsourcing data management techniques can be applied within an enterprise context.
Topics covered include:
- Data Quality And Data Curation
- Case Studies on Crowdsourced Data Curation
- Setting up a Crowdsourced Data Curation Process
- Linked Open Data Example
- Future Research Challenges