1 / 14

Harnessing Open Data for Agriculture: Interactive Solutions and Collaborations

This showcase presents innovative applications of open data in agriculture, emphasizing an interactive platform powered by data. By utilizing trusted sources, the project aims to provide timely information on key agricultural topics such as climate change, market prices, and new research achievements. Participating organizations, like Stevia Coop and Venus Coop, are collaborating to refine data components and delivery methods. The initiative seeks to transform how agricultural data is accessed and analyzed, creating user-friendly queries and fostering partnerships for enhanced agricultural practices.

uriah
Télécharger la présentation

Harnessing Open Data for Agriculture: Interactive Solutions and Collaborations

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. Open Data Working Group:Showcases from agricultural domain Giannis Stoitsis, Agro-Know Technologies Open Data Working Group Meeting, MTSR, 20/11/2013

  2. Agricultural Showcase Concept • High level pitch: • Open data powered iGoogle for agricultural • Not single mash up but interactive approach e.g. user can enter a query term, he can expand queries etc. • Trusted sources • Cases • Stevia Coop • Venus Coop • Public bodies?

  3. How it can look like? Export/Import news Climate change Pests info Research achievements Seed/Varieties/Genetic New fertilizers Weather info and forecasts for local area ….

  4. data sourcesTo start with

  5. Publications

  6. Demographic and financial

  7. Statisticaland Maps

  8. Food Safety http://data.ifpri.org/sparql

  9. data sourcesand continue with

  10. Focus only on agricultural publications

  11. Statistical at national level

  12. Geo at national level

  13. Market prices stream Problem with the vegetables

  14. Collaboration • Finalize the data components in the wireframe • Check the end points and bring ideas on combining data • JS client for SPARQL • Federated search over sparql end point • feasible? • does it make sense?

More Related