Ist africa2012 habitats_2

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Ist africa2012 habitats_2

  1. 1. Habitats Community building experiences within the framework of Living Lab approach: A key for supporting future EU-African Research Cooperation Karel Charvat, Ota Cerba Help Service Remote Sensing Czech Republic Ana Saez NEXT STEP srlSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  2. 2. INSPIRE & Social Validation • “Open Innovation” Has demonstrated that better ideas come from outside of the organizations. • Standards adoption needs long period of time and clear citizens and research community acceptance for success. • Interoperability and its benefits for cooperation are a second priority for many researchers and policy makers dealing with environment.Session 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  3. 3. INSPIRE & Social Validation • Environment needs sustainability and clear synergies between involved communities • Citizens and users aims to have real and useful services available in their daily lifeSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  4. 4. Issues for INSPIRE • Integrated community’s environmental policy- making - Habitats-related data normally managed by different and distinct entities • Top-down consensus-building processes across Member States - Weak bottom-up feedback slows adoption • Spatial Data contained in Annexes I-II-IIISession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  5. 5. Social Spaces for Research and Innovation PEOPLE-LED INNOVATION SOCIAL SPACES FOR RESEARCH AND INNOVATIONSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  6. 6. HABITATS Social networks Goals: • Create a social network to consolidate the HABITATS user communities and structure the discussions • Engage stakeholders and related networks in the communication process • Develop usage scenarios, capture use requirements, assess the potential impactSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  7. 7. HABITATS Social networks Aggregated Interested communities Communities Communities linked to HABITATS HABITATS Core Community Other Communities HABITATS Learning Community SpaceSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  8. 8. HABITATS Social networks HABITATS core community on NING www.inspiredhabitats.ning.com www.habitats.czSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  9. 9. Lessons learn from user communities NATURAL RESOURCE MGMT LA PALMA ECO- WILD SALMON NAT’L MARINE TOURISM MONITORING POLICY RESERVE HIKING TRIP PLANNER CZECH NAT’L FOREST PROGRAMME SORIA NATURAL RESERVE SHEEP & GOAT ECON ACTIVITY HERD AT COASTAL MANAGEMENT BENTHIC HAB. ECONOMIC ACTIVITIESSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  10. 10. Lessons learn from user communities • Analysis of use cases • Generalization • How communities request could influence architecture design, data models and metadata requirementsSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  11. 11. Analysis of use cases – data usage • Regional data used regionally • Global data used regionally • Regional data used cross regionally • Regional data used globally • Global data used globallySession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  12. 12. Regional data used regionally There is not direct requirement for INSPIRE data models - Local data models could be wider - Local data models reflect regional needs and also regional decision processes - If data are not shared outside of region (but in many cases it is necessary), in principle global standards are not needed - Standards are needed in case of more data suppliers, to guarantee data consistenceSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  13. 13. Regional data used regionallySession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  14. 14. Global data used regionally • Global data are in some content something like de facto standards • In some cases it is necessary to be possible transform data into such models, which is required by regional decision processes • The global model has to cover regional decision needs (GMES case for example) • Question is, if this transformation will be done on fly or offline • Language problemSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  15. 15. Example FMI data used locallySession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  16. 16. Example FMI data used locallySession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  17. 17. Regional data used cross regionally • There is already very visible problem of data harmonization, this problem is higher, in the case of cross boarder regions • In many cases, like tourism we need deal not with one or more separate data theme, but with complex mixture of themes related to INSPIRE • In some application cases model could be broader then INSPIRE definition • Language problemSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  18. 18. Tourist exampleSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  19. 19. Regional data used globally • Probably most relevant cases for INSPIRE data model • The idea is to combine local data sets into one data set • The regional data has to be transformed (in many cases simplified) into global model • Relevant cases are tourism, transport, education, research, environment protection, risk management, strategic decision • Language problemSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  20. 20. Regional data used globallySession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  21. 21. Regional data used globallySession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  22. 22. Global data used globally • Global data are standard or de facto standard. • It is expected, that in the case of data of public sector, this data will be already in INSPIRE models • It could happened, that this models has to be transformed on the base of needs of concrete application area. Transformation could be based also on Feature Encoding or SLDSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  23. 23. Global data used globallySession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  24. 24. Session 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  25. 25. Where you can find results? www.habitats.cz www.inspiredhabitats.ning.com http://www.linkedin.com/e/-ehsedk-grw4ca1o-4p/vgc/3374609/emSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  26. 26. SPATIAL DATA HARMONIZATION: EAST AFRICA CASESession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  27. 27. Task • Integrate geodata In Burundi, Kenya, Rwanda, Tanzania and Uganda • Use free data sets as well as free (mostly open- source) softwareSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  28. 28. Data sources • OpenStreetMap • Land cover/Land use data (GlobCover, AfriCover) • VMap • TM World Borders • Global Lakes and Wetlands Database • World Wildlife Federation ECOSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  29. 29. Data formats • ESRI Shapefile • Talend Open Studio enables to process another spatial data formats (e.g. OSM or connection to database)Session 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  30. 30. Technologies • Harmonization: ETL Tool – Talend Open Studio + Spatial Data Integrator • Data preparation & viewing: GIS – OpenJUMP, Quantum GISSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  31. 31. Harmonization processSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  32. 32. Result mapSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  33. 33. Harmonization processSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  34. 34. Result mapSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  35. 35. Relation to Ontologies • Ontologies describe data sets and their properties • Processing of ontologies derives new information focused on necessary harmonization stepsSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  36. 36. Relation to OntologiesSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  37. 37. Questions – OSM & databases  Harmonization tools are able to connect OSM files and databases.  Weve tested OSM original files as well as these files converted to database, but...  ...the geometry of original files was corrupted → therefore the processing was stopped.  ...the files were very large → therefore the processing was very slow.Session 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  38. 38. Questions – Forests in Burundi Harmonization of forest in Burundi from four different sources OSM VMap WWF ECO GlobCoverSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS
  39. 39. Results www.geoportal4everybody.eu http://www.linkedin.com/e/-ehsedk-gs0f7h88-70/vgc/3516067/emSession 9f, 11 May 2012 IST-Africa 2012 Copyright 2012 HSRS

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