Zur agentenbasierten und qualitätsbewussten Integration von Daten aus geo-sozialen Netzwerken - Datenintegration als gemeinschaftlicher Verhandlungsprozess
Humangeographie
Zusammenfassung der Projektergebnisse
With the success of the Web 2.0 paradigm and the associated increase in the use of smartphones (equipped with position sensors), citizens are increasingly actively and passively producing valuable geographic information about places, here referred as POIs, in volunteered geographic information platforms and geo-social networks. The information contained in these platforms offer significant potential for leveraging existing and new geospatial applications relevant to society. However, because this geographic information is dispersed across different sources, each with its purposes, group of contributors, data characteristics, etc., approaches need to be developed for integrating this heterogeneous information and accounting for the issue of data quality. This project has set this as its goal contributing to covering this research gap. Furthermore, it attempted to relate the aspects of data integration and quality as dependent on the contributors’ profile (background, interests, expertise, etc.) and model this interplay through simulations based on empirical data. Different approaches based on graph-theory principles for integrating data from VGI and social media platforms were conceived, implemented and tested. However, due to persisting and imposed limitations on the access to the users’ profile information, we were obliged to adapt early approaches and, instead, estimate the reliability of geographic data from social media from the consistency of the user community and user-defined concepts (i.e. tags) associated to the posts, which has proven to be successful. The graph-based geo-data integration approach developed during this project found direct application in the system for the generation of pleasant pedestrian routes. In accordance with the open data principle and for the sake of reproducibility, our geo-data integration approach is available at a code sharing platform.
Projektbezogene Publikationen (Auswahl)
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(2016) Defining fitness-for-use for crowdsourced points of interest (POI). ISPRS International Journal of Geo-Information. Vol. 5, p. 149–149
Jonietz, D. and Zipf, A.
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(2017) Graph-based strategies for matching points-of-interests from different VGI sources. In: Proceedings of the 20th AGILE Conference. Wageningen (Holland)
Novack, T., Peters, R., Zipf, A.
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(2017): Highlighting Current Trends in Volunteered Geographic Information. International Journal of Geo-Information. 2017, 6(7), 202
Jonietz, D., Antonio, V., See, L., Zipf, A.
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(2018) Coupling maximum entropy modeling with geotagged social media data to determine the geographic distribution of tourists. International Journal of Geographical Information Science (IJGIS)
Yan, Y. C.-L. Kuo, C.-C. Feng, W. Huang, H. Fan & A. Zipf
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(2018): A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data. Sensors, Vol. 18, 3794
Novack, T., Wang, Z., Zipf, A.
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(2018): Efficient Method for POI/ROI Discovery Using Flickr Geotagged Photos. ISPRS Int. J. Geo-Inf. 2018, 7(3), 121
Kuo, C.-L., T.C. Chan, I.-C. Fan, A. Zipf
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(2018): Graph-Based Matching of Points-of-Interest from Collaborative Geo-Datasets. International Journal of Geo-Information, Vol. 7 (3), pp. 117-134
Novack, T., Peters, R., Zipf, A.
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(2019) Open-data-driven embeddable quality management services for map-based web applications. Big Earth Data, 2:4, 395-422, 2019
Noskov, A. and Zipf, A.
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(2019). Exploring the effects of Pokémon Go vandalism on OpenStreetMap. In: Proceedings of the Academic Track at the State of the Map 2019. Heidelberg (Germany)
Juhász, L., Hochmair, H.H., Qiao, S., Novack, T.
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(2019). The geographical and cultural aspects of geo-information: an introduction. In: Proceedings of the GeoCultGIS - Geographical and Cultural Aspects of Geo-Information: Issues and Solutions. Limassol (Cyprus)
Novack, T., Grinberger, A.Y., Schultz, M., Zipf, A., Mooney, P.
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(2019): An exploratory analysis of usability of Flickr tags for land use/land cover attribution, Geo-spatial Information Science (GSIS)
Yan, Y., Schultz, M., Zipf, A.
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(2019): Towards Detecting Building Facades With Graffiti Artwork Based on Street View Imagery. International Journal of Geo-Information, 9, 98
Novack, T., Vorbeck, L., Lorei, H., Zipf, A.
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(2020): Towards Detecting Building Facades With Graffiti Artwork Based on Street View Imagery. Int. Journal of Geo-Information, 9, 98
Novack, T., Vorbeck, L., Lorei, H., Zipf, A.
