Module 7 Knowledge exchange II: supporting data use
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This presentation aims to provide some contents to start the discussions in this knowledge exchange session about the promotion of data use, especially among those communities that are less aware of GBIF.
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Module 7 Knowledge exchange II: supporting data use
- 1. GB20 Nodes training course Module 7 – Knowledge exchange II Supporting data use Facilitator: Alberto González-Talaván Senior Programme Officer for Training GBIF Secretariat 5 October 2013
- 2. Summary This is a discussion and knowledge exchange session on best practices to support data use to the furthest extend possible. This is side of GBIF’s work that has been frequently neglected In this session we will concentrate on addressing social and cultural barriers to the use data for policy and science. With this presentation we just want to bring some ideas to the table to start the discussions. This presentation corresponds to Module 7 of the GB20 Training course for Nodes hold in October 2013 in Berlin, Germany.
- 3. Outline 1. Barriers to data use 2. Strategies to increased data use
- 4. Barriers 1. The data does not exist 2. Lack of access 3. Wrong format 4. Data exists, but user unaware 5. Lack of capacity 6. Lack of will 7. Do not comply with user’s requirements 8. License too restrictive 9. Lack of infrastructure Related to mobilization Practical barriers Capacity barriers Cultural barriers Related to fitness
- 5. Strategies 1. Challenge perceived data quality concerns 2. Promotion among target communities 3. Promotion of existing data use cases 4. Capacity enhancement and training 5. Demonstrate potential savings 6. Show the benefit for their scientific careers. 7. Peer pressure. 8. Start / support programmes to increase access to infrastructure
- 6. GB20 Nodes training course Module 7 – Knowledge exchange II Supporting data use Facilitator: Alberto González-Talaván Senior Programme Officer for Training GBIF Secretariat 5 October 2013
- 7. GB20 Nodes training course Module 7 – Knowledge exchange II Supporting data use Facilitator: Alberto González-Talaván Senior Programme Officer for Training GBIF Secretariat 5 October 2013
Notas do Editor
- Template image composed from images by Jamie Brelsford (United Kingdom) and anant12 (India), obtained trhough stock.xchng (http://www.sxc.hu/photo/604932, http://www.sxc.hu/photo/1426670)
- On these points: The data does not exist: the data required by the user has never been collected by anyone. Lack of access: The data exists but it is not accessible by the user. It may not exist in digital form. It may be accessible to only certain people. It may be protected by technical means. Wrong format: The data is digital, but it is not in a format that the user can use directly or with a reasonable effort. Data exists, but user unaware: the data is digital and accessible, but the user does not know that. Lack of capacity: the user does not know how to work with that kind of data to produce products if his/her interest. Lack of will: the user simply does not want to use that data. Do not comply with user’s requirements: all the data quality issues are included here. The level of detail, the completeness, the density of data… is not what the user needs. License too restrictive: the products that user would like to obtain are not compatible with the license under with the data is released. Lack of infrastructure: The user does not have access to the infrastructure needed to perform the kind of analysis that (s)he needs.
- On these points: Challenge perceived data quality concerns: Some data quality concerns are based on real gaps, lack of enough density, etc that need to be tackled by targeted digitization strategies. In other cases the potential users may have a perception of data quality that is from several years ago, or not from their direct experience. Promotion among target communities: After an study of the potential audiences (of all types: scientific, policy, practitioners…), perform activities targeting specific communities. Promotion of existing data use cases: promote the relevant use cases that appear through journal articles, reports, media, etc This may be a challenge for non-scientific communities, as we have got better to follow up scientific use through journal articles, there is still very few mechanisms for other type of use, grey literature, etc. and in particular use for direct policy support. Capacity enhancement and training. Demonstrate potential savings: Using existing data instead of recapturing the information can reduce the execution time and financial costs of any project. Show the benefit for their scientific careers: using new technologies, etc. Peer pressure: other colleagues are already producing research, reports, etc. using digital data and using digital technologies. Start / support programmes to increase access to infrastructure: start collaboration programmes that make possible that national researchers access the infrastructure needed for the analysis inside or outside of the country.
- Template image composed from images by Jamie Brelsford (United Kingdom) and anant12 (India), obtained trhough stock.xchng (http://www.sxc.hu/photo/604932, http://www.sxc.hu/photo/1426670)