1 / 18

Grey in the R&D Process

Keith G Jeffery Director, IT CCLRC keith.g.jeffery@rl.ac.uk. Anne G S Asserson Research Department University of Bergen anne.asserson@fa.uib.no. Grey in the R&D Process. The Problem: Tidal wave of publications, products, patents (especially datasets) The hypothesis is in 4 parts:

nasim-parker
Download Presentation

Grey in the R&D Process

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Keith G Jeffery Director, IT CCLRC keith.g.jeffery@rl.ac.uk Anne G S Asserson Research Department University of Bergen anne.asserson@fa.uib.no Grey in the R&D Process

  2. The Problem: Tidal wave of publications, products, patents (especially datasets) The hypothesis is in 4 parts: (a) that the R&D process itself provides some context for managing the information; (b) that linking the records of the process to the publications provides this context; (c) that questions of curation and provenance are addressed automatically in such an environment; (d) that such an environment integrates grey and white literature and other R&D outputs such as software, data, products and patents. Introduction

  3. The Difficulty • Formidable threshold barrier • the information is difficult to collect • end-user interface to systems presents a high threshold barrier (little KE support)

  4. The Difficulty • Formidable threshold barrier • the information is difficult to collect • end-user interface to systems presents a high threshold barrier (little KE support) • Ill-structured user environment • the end-user commonly works in an ill-structured environment; metadata recording: • not done • done without sufficient attention • simply forgotten

  5. The Difficulty • Formidable threshold barrier • the information is difficult to collect • end-user interface to systems presents a high threshold barrier (little KE support) • Ill-structured user environment • the end-user commonly works in an ill-structured environment; metadata recording: • not done • done without sufficient attention • simply forgotten • Much Information demanded all at once • demand for a large amount of information all at once

  6. The Difficulty and Solution • Formidable threshold barrier • the information is difficult to collect • end-user interface to systems presents a high threshold barrier (little KE support) • Ill-structured user environment • the end-user commonly works in an ill-structured environment ; metadata recording: • not done, • done without sufficient attention, • simply forgotten; • Much Information demanded all at once • demand for a large amount of information all at once • Use the Process • Build progressively the metadata corpus using small incremental data input steps at first instant metadata available • e.g. as a publication is conceived, submitted, accepted and published.

  7. The R&D Process: CERIF-CRIS Workprogramme CERIF-CRIS DATABASE Proposal Project Results Exploitation WealthCreation

  8. Research Process: Input Output a= process, a = data, a = white literature, a = grey, a = both

  9. Research Process: Input Output a= process, a = data, a = white literature, a = grey, a = both

  10. PROJECT ORGUNIT PERSON Prize/Award Event Contact Results Publication General Facility Skills Results Patent Particular Equipment CV Service Results Product CRIS: CERIF Model Funding Programme Classification

  11. Descriptive Title Subject Keywords Description Resource Type Coverage Temporal Coverage Spatial Proposed Formalised DC(improved hyperlinks, CRIS, metadata) Domain of CERIF Project Person OrgUnit Person OrgUnit UniqueId UniqueId Restrictive Security Privacy Quality Assessment AccessLevel Charge Annotation Classification ResourceIdentifier Navigational

  12. Overall : The Way Forward SCIENTIFIC DATASETS Data Information Knowledge CRIS Management of science PUBLICATIONS Data Information Knowledge

  13. Overall : The Way Forward Portal with knowledge-assisted user interface SCIENTIFIC DATASETS Data Information Knowledge CRIS Management of science CDR (CERIF) PUBLICATIONS Data Information Knowledge Digital Curation Facility

  14. Overall : The Way Forward Portal with knowledge-assisted user interface SCIENTIFIC DATASETS Data Information Knowledge metadata PUBLICATIONS Data Information Knowledge Digital Curation Facility

  15. Overall : The Way Forward Portal with knowledge-assisted user interface SCIENTIFIC DATASETS Data Information Knowledge metadata PUBLICATIONS Data Information Knowledge publish validate Digital Curation Facility

  16. Overall : The Way Forward Ambient, Pervasive Access Portal with knowledge-assisted user interface SCIENTIFIC DATASETS Data Information Knowledge metadata PUBLICATIONS Data Information Knowledge publish validate Digital Curation Facility GRIDs

  17. With • Workflow Support • Cooperative Working Facilities •  better R&D •  wealth creation •  improvement of the quality of life

  18. Conclusion • Supporting the Research Process with ICT • Overcomes the problems • End-user threshold barrier • End-user volume barrier • Puts Research Publications in context • Grey White • Related to CRIS data • Positions research organisations for the ‘new world’ • GRIDs & Ambient computing

More Related