Kicking-Off: 2 new projects in DFG priority programme “VGIscience”

Recently we attended the Kick-Off Meeting of the DFG Priority Programme “VGiscience” in Würzburg, in which we are involved through two projects. René Westerholt presented these projects to the audience of all interdisciplinary collaborators. The principal aim of this very first meeting was to explore potential cross-project collaborations, and to outline an envisaged upcoming summer school that will take place in autumn 2017.

GIScience Heidelberg contributes to the priority programme with two VGI related projects that are now starting:

A framework for measuring the fitness for purpose of OpenStreetMap data based on intrinsic quality indicators

The contribution of this project is the systematic identification and connection among intrinsic and extrinsic quality indicators and measurements, across a number of application domains.

Spatial Correlations in Social Media Data: Identification and Quantification of Spatial Correlation Structures in Georeferenced Twitter Feeds

In this project we aim to explore novel ways to derive spatial correlation structures within social media feeds. Our work builds upon the mature theory of spatial autocorrelation, which is the traditional way of measuring spatial structure and combines this with stochastic geometry and related concepts.

These two projects complement other (also VGI-related) projects that have recently started:

  • An agent-based and quality-aware integration of geo-social networks data data integration as a collaborative negotiation process (DFG)
  • LandSense – A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring (EU Horizon 2020)
  • WeGovNow – Towards We Government: Collective and participative approaches for addressing local policy challenges (EU Horizon 2020)
  • Crowd FDA – Crowdsourcing for Forensic Disaster Analysis (DFG)
  • Interested readers find more information about all kinds of related topics in the following publications:

    Barron, C., Neis, P. & Zipf, A. (2013): A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis. , Transactions in GIS, DOI: 10.1111/tgis.12073

    Ballatore, A. and Zipf, A. (2015): A Conceptual Quality Framework for Volunteered Geographic Information. COSIT – CONFERENCE ON SPATIAL INFORMATION THEORY XII. October 12-16, 2015. Santa Fe, New Mexico, USA. Lecture Notes in Computer Science, pp. 1-20

    Fan, H., Zipf, A., Fu, Q. & Neis, P. (2014): Quality assessment for building footprints data on OpenStreetMap. International Journal of Geographical Information Science (IJGIS). DOI: 10.1080/13658816.2013.867495.

    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.

    Steiger, E., Westerholt, R., Resch, B. and Zipf, A. (2015): Twitter as an indicator for whereabouts of people? Correlating Twitter with UK census data. Computers, Environment and Urban Systems, 54, 255 – 265. DOI: 10.1016/j.compenvurbsys.2015.09.007.

    Westerholt, R., Steiger, E., Resch, B. and Zipf, A. (2016): Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis. PLOS ONE, 11 (9), e0162360. DOI: 10.1371/journal.pone.0162360.

    Westerholt, R., Resch, B. and Zipf, A. (2015): A local scale-sensitive indicator of spatial autocorrelation for assessing high- and low-value clusters in multi-scale datasets. International Journal of Geographical Information Science, 29 (5), 868-887. DOI: 10.1080/13658816.2014.1002499.
    You can find a preprint (“as accepted”) here.