Dadzie, Aba-Sah and Domingue, John
(2015).
|
PDF (Accepted Manuscript)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (7MB) | Preview |
| URL: | http://ceur-ws.org/Vol-1456/paper1.pdf |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
The era of Big Data brings with it the need to develop new skills for managing this heterogenous, complex, large scale knowledge source, to extract its content for effective task completion and informed decision-making. Defining these skills and mapping them to demand is a first step in meeting this challenge. We discuss the outcomes of visual exploratory analysis of demand for Data Sci- entists in the EU, examining skill distribution across key industrial sectors and geolocation for two snapshots in time. Our aim is to translate the picture of skill capacity into a formal specification of user, task and data requirements for de- mand analysis. The knowledge thus obtained will be fed into the development of context-sensitive learning resources to fill the skill gaps recognised.
| Item Type: | Conference or Workshop Item |
|---|---|
| Copyright Holders: | 2015 The Authors |
| ISSN: | 1613-0073 |
| Extra Information: | Workshop co-located with ISWC 2015, October 11, 2015, Bethlehem, Pennsylvania, USA |
| Keywords: | big data; visual exploration; visual analytics; demand analysis; RtD; data-driven decision-making; ontology-guided design |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Related URLs: | |
| Item ID: | 44263 |
| Depositing User: | Kay Dave |
| Date Deposited: | 09 Sep 2015 08:15 |
| Last Modified: | 04 Oct 2016 11:49 |
| URI: | http://oro.open.ac.uk/id/eprint/44263 |
| Share this page: |     |
Download history for this item
These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)