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Presentation (1.15 MB)

  1. 1. Workshop on Innovative Data Mining Techniques in Support of GEOSS: A summary Roger L. King and Nicolas H. Younan Mississippi State University Mihai Datcu DLR
  2. 2. Workshop logistics <ul><li>August 31, 2009 – September 2, 2009 </li></ul><ul><li>Sinaia, Romania </li></ul><ul><li>Hosted by Romanian Space Agency (ROSA) </li></ul><ul><li>Convened by ROSA (Pisa), MSU (King), DLR (Datcu) </li></ul><ul><li>International audience </li></ul><ul><ul><li>38 participants </li></ul></ul><ul><ul><li>Representing – users, researchers, government </li></ul></ul><ul><ul><li>Denmark, Finland, Germany, Italy, Japan, Romania, Switzerland, Turkey, United States </li></ul></ul><ul><li> </li></ul>
  3. 3. Defining terms <ul><li>Define data mining as: </li></ul><ul><ul><li>A computer process of discovering unknown knowledge from massive data sets. </li></ul></ul><ul><ul><li>Data mining involves massive data sets, high-performance computers, and mining algorithms. </li></ul></ul><ul><li>Earth observations, mainly through remote sensing, have generated huge volumes of geospatial data. </li></ul><ul><ul><li>Vital for scientific research, socio-economic activities, and military missions. </li></ul></ul><ul><li>Those massive data collections contain unknown knowledge about the status of the earth system, functions and interactions of its components. </li></ul>
  4. 4. Flow of this presentation <ul><li>The workshop consisted of 2.5 days of presentations by various experts with focused panel discussions that helped shape outcomes and recommendations </li></ul><ul><li>This summary will not be able to give many of the specifics made in the presentations. However, they will be incorporated into the final report. </li></ul><ul><li>Start with the GEOSS Data Sharing Principles </li></ul><ul><li>Focus will be on workshop panel discussions </li></ul>
  5. 5. Setting the stage <ul><li>Marius-Ioan Pisa, CEO ROSA </li></ul><ul><ul><li>Provided rationale for meeting </li></ul></ul><ul><li>Robert Koopman, GEO Secretariat </li></ul><ul><ul><li>GEOSS: Ongoing Developments and Priorities </li></ul></ul><ul><ul><li>Data sharing is a priority for GEOSS and serves as the “lubrication of the GEOSS engine” </li></ul></ul><ul><ul><li>Data mining is a cross cutting area reaching across all 9 GEOSS societal areas. </li></ul></ul>
  6. 8. Workshop panel discussions <ul><li>This presentation is being given to solicit more discussion among data mining professionals. </li></ul><ul><li>There will be a statement of fact followed by a series of questions for further discussion in the Q&A for this talk and for further discussion amongst participants during this conference. </li></ul><ul><li>The questions will be focused into three areas: </li></ul><ul><ul><li>Outreach </li></ul></ul><ul><ul><li>Technical challenges </li></ul></ul><ul><ul><li>Policy challenges </li></ul></ul>
  7. 9. Panel discussions - Outreach <ul><li>There appear to be many ongoing efforts going on worldwide with data mining and EO data. How do we better communicate amongst ourselves and the GEOSS user communities? </li></ul><ul><li>Should we recommend a community of practice for data mining? </li></ul><ul><ul><li>The concept of a community of practice (often abbreviated as CoP) refers to the process of social learning that occurs and shared socio-cultural practices that emerge and evolve when people who have common goals interact as they strive towards those goals. </li></ul></ul>
  8. 10. Panel discussions - Outreach <ul><li>Should we consider an international conference on data mining in support of the GEOSS societal themes? </li></ul><ul><li>Is there a need for a formalized group for organizing data mining international activities (conferences, contests)? If so, how do we integrate IIMCG? </li></ul>
  9. 11. Panel discussions – Technology Challenges <ul><li>Data mining is an important tool for discovering the knowledge contained in EO data sets. However, there are technological challenges that must be overcome before data mining can become a mainstream application for GEOSS societal benefit areas. </li></ul>
  10. 12. Panel discussions – Technology Challenges <ul><li>How can we use data mining approaches to extract information from radar phase data? </li></ul><ul><li>What impact does speckle have on data mining of radar amplitude and phase data? </li></ul><ul><li>How is data mining achieved using multi-temporal data sets? </li></ul><ul><li>How do we handle gaps in data (spatial, spectral, and temporal)? </li></ul><ul><li>How do we handle problems of scale and resolution in data streams? </li></ul>
  11. 13. Panel discussions – Technology Challenges <ul><li>How do we combine (fusion) data sets for better understanding? </li></ul><ul><li>How do we describe algorithms to the general user community? </li></ul><ul><ul><li>Do we train users a priori so they know of usefulness of data mining for a particular sensor or application? </li></ul></ul><ul><li>The following are some specific technical challenges for high resolution imagery identified by JRC. </li></ul>
  12. 15. Panel discussions – Policy Challenges <ul><li>We need end users interested in pulling data mining technologies to use in their applications. Not the data mining research community producing papers and algorithms and trying to push our approaches into the application areas. </li></ul><ul><li>How do we integrate data mining algorithms into GEOSS community? </li></ul><ul><li>What is the success metric for a data mining algorithm? How is it measured? </li></ul>
  13. 16. Panel discussions – Policy Challenges <ul><li>How does the research community work closer with the user community to better understand the problems they are experiencing? </li></ul><ul><ul><li>Need to engage user community early in the research. </li></ul></ul><ul><ul><li>Need demonstration projects that show use of data mining in user community. </li></ul></ul><ul><li>Is an incremental approach a better way to work because it may be easier to make small changes in an operational community, than radical changes? </li></ul>
  14. 17. Panel discussions – Policy Challenges <ul><li>How should national agencies be better aligned to deal with data streams being made available via the GEOSS data sharing principles? </li></ul><ul><ul><li>The example used in the workshop focused on meteorological data </li></ul></ul><ul><li>Could the GEO Data Sharing Principles deal with the topic of data formats, quality of data, and other issues to benefit the data mining community? </li></ul>
  15. 18. Conclusions <ul><li>We are in the process of writing a report for the GEO Secretariat. </li></ul><ul><li>There are obviously more questions than answers. </li></ul><ul><li>Please send any written thoughts or comments on these questions to Roger King ( </li></ul>