Crowdsourcing for Forensic Disaster Analysis - Kick-Off Meeting
Mar 18th, 2016 by ea3
This week the Kick-Off Meeting of a recently started collaboarative project on “Crowdsourcing for Forensic Disaster Analysis” (CrowdFDA) took place at GIScience Heidelberg University together with partners from the Geophysical Institute of Karlsruhe Institute of Technology (KIT) (Dr. Bijan Khazai) as member in the Center for Disaster Management and Risk Reduction Technology (CEDIM, KIT) and experts from Cambridge.
Crowdsourcing and Volunteered Geographic Information (VGI) such as OpenStreetMap (OSM) have shown to be useful to complete official information for decision makers and emergency responders in crisis situations. This, however, raises the question of how such often poorly structured information can be incorporated into response and revocery plans in a disaster event. This faces a major problem: „What is lacking in the field of crisis informatics is a conceptual scientific framework to integrate and operationalize crisis crowdsourcing into the official emergency management environment.” (Liu, 2014). To solve this problem the partners at KIT and GIScience Heidelberg together seek to develop a Crowdsourcing for Forensic Disaster Analysis (Crowd FDA) scientific framework that covers and maps the information needs and the potential contributions by the crowd, as well as novel methods for VGI data quality assessment for disaster management.
This builds on our earlier work on disaster related microtasking such as http://crowdmap.geog.uni-heidelberg.de/
and on further methods and tools for VGI quality assessment, e.g. iOSMAnalyser etc. (see example refs below)
related earlier references:
Barron, C., Neis, P. & Zipf, A. (2014): A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis. Transactions in GIS, Volume 18, Issue 6, pp 877–895.
A. Ballatore & A. Zipf (2015): A Conceptual Quality Framework for Volunteered Geographic Information, Spatial Information Theory (COSIT), Santa Fé, NM, pp. 89–107.
Porto de Albuquerque, J., B. Herfort, A. Brenning, A. Zipf (2015): A Geographic Approach for Combining Social Media and Authoritative Data towards Improving Information Extraction for Disaster Management. International Journal of Geographical Information Science. IJGIS, Vol. 19, Issue 4. pp. 667-689. Taylor & Francis.
Horita, F., Degrossi, L.C., Gomes de Assis, L.F., Zipf, A. & de Albuquerque, J.P. (2013): The use of Volunteered Geographic Information (VGI) and Crowdsourcing in Disaster Management: a Systematic Literature Review. 19th Americas Conference on Information Systems (AMCIS 2013). Chicago. US.
Bakillah, M., Liang, S. H. L., Mobasheri, A., Jokar Arsanjani, J. & Zipf, A. (2014): Fine resolution population mapping using OpenStreetMap points-of-interest. International Journal of Geographical Information Science (IJGIS). Vol 28, Issue 9, pp. 1940-1963. Taylor & Francis.
Jokar Arsanjani, J., Mooney, P., Helbich, M., Zipf, A., (2015): An exploration of future patterns of the contributions to OpenStreetMap and development of a Contribution Index, Transactions in GIS, John Wiley & Sons. DOI: 10.1111/tgis.12139.
Eckle, M., Herfort, B., Alberquerque, J. P., Zipf, A. (2016): Leveraging OpenStreetMap to support flood risk management: A prototype decision support system for the identification of critical infrastructure. 13th International Conference on Information Systems for Crisis Response and Management. ISCRAM 2016. Rio de Janeiro, Brazil.
Jokar Arsanjani, J., Mooney, P., Zipf, A., Schauss, A., (2015): Quality assessment of the contributed land use information from OpenStreetMap versus authoritative datasets. In: Jokar Arsanjani, J., Zipf, A., Mooney, P., Helbich, M., (eds) OpenStreetMap in GIScience: experiences, research, applications. Springer. pp 37-58
Dorn, H., Törnros, T. & Zipf, A. (2015): Quality Evaluation of VGI using Authoritative Data – A Comparison with Land Use Data in Southern Germany. ISPRS International Journal of Geo-Information. Vol 4(3), pp. 1657-1671.
Fan, H., Zipf, A., Fu, Q. & Neis, P. (2014): Quality assessment for building footprints data on OpenStreetMap. International Journal of Geographical Information Science (IJGIS). Vol 26. Issue 14.
Roick, O., Hagenauer, J. & Zipf, A. (2011): OSMatrix – Grid based analysis and visualization of OpenStreetMap. SOTM-EU 2011. State of the Map EU. Scientific Track. Wien.