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This week you still have the chance to meet colleagues from HeiGIT team at CeBIT 2017 in Hannover.
We present Smart GeoServices for Smart Cities in Halle 7 at the Smart City Forum booth together with our colleagues from heidelberg mobil.

in case you are this week not at CeBIT in the north of Germany, but rather at FOSSGIS in the south, you have the chance meet us also there and listen to several presentations on OSM work at HeiGIT and GIScience HD by our team member Martin Raifer.
The main talk will be on OSM-History-Analysis based on Big-Data-Technology on 22.03. 15.00pm Room AM HS 10.
Further there will be some lightning talks (stepping in for other colleagues) on the following topics:

And in case you really can’t make it to Passau, just visit the Smart City Booth at CeBIT Hannover…

Fig: deepVGI Concept

Several urban studies have been increasingly relying on spatial data provided by Volunteered Geographic Information (VGI) sources. The matching of features across different VGI projects may serve to assess and improve the reliability and completeness of VGI data. In a recent study, we first provide a short discussion on the similarity measures often used for matching points-of-interests (POIs). This discussion leads to the argument that no single measure is completely effective when dealing with VGI data and that a reasonable aggregation of these measures is necessary. We then propose a matching strategy based on a graph whose nodes and edges represent the POIs and their possible matching pairs, respectively. Each edge has a ‘final weight’ that can be an aggregation of the different similarities or simply the value of one of them. The matching consists in extracting all possible subsets of edges from the graph in which no node occurs more than once. It than selects the subset with the highest sum of final weights. As a first evaluation of this strategy, we conducted an experiment with food-related POIs from OpenStreetMap and Foursquare. We tested different similarity measures and linear combinations of them as final weights from the graph edges. The results show that: (1) spatial and semantic similarities perform poorly, (2) string similarities are just above 90% accurate and (3) the highest matching accuracy was achieved when considering string and spatial similarities together.
More details and results will be given in the paper accepted for the AGILE 2017 conference in Wageningen.

Novack, T., Peters R. and A. Zipf (2017 accepted): A graph-based strategy for matching points-of-interests from different VGI sources. AGILE 2017, International Conference on Geographic Information Science. May 9-12. Wageningen, NL.

DFG Project http://www.geog.uni-heidelberg.de/gis/dfg_en.html

How can we combine technology and digitalisation with doing good? That is the main focus for the 2017 Impact Night series organized by and at the Impact Hub Bergen. Last evenings Impact Night was about Tech for Change and disaster response. Therefore the Impact Hub team invited Per Aarvik, President of the StandbyTaskForce, Sam Applebee, the founder of Super Global, and Melanie Eckle of our HeiGIT disaster mapping and management team to share their experiences and to discuss how to use technology and digitalisation, like crowdsourcing and mapping, as useful tools to improve humanitarian response during natural disasters and other crises.

Melanie Eckle presented the work of the Missing Maps project and Humanitarian OpenStreetMap team (HOT) and shared her experiences about working in and with the Missing Maps and HOT community.

VGI-Analytics offers two formats for paper submission:

  1. Workshop Short Paper (2000 to 3000-word manuscript)
    New Submission Deadline 28th March 2017.
    Authors are requested to follow the formatting guidelines for short paper submissions on the AGILE 2017 call for papers page and use the  Word .doc template or the  Word .docx template provided. Short papers should be submitted directly via e-mail to Dr. Peter Mooney at Peter.Mooney@nuim.ie. Accepted short papers will be published here on the workshop Website.
  2. Special Issue Journal Full Paper (maximum 20 pages)
    Extended Final Submission Deadline 9th June 2017
    Full paper submissions will be considered for presentation at the workshop as well as for inclusion in a special issue of the Geo-spatial Information Science (GSIS) journal to appear in late 2017. To submit a full paper please follow the manuscript preparation and submission guidelines of the Special Issue Call for Papers.
    Authors are requested to also notify Dr. Peter Mooney at Peter.Mooney@nuim.ie that you submitted a full paper.
    PLEASE NOTE: When you submit your paper there is no specific option for the special issue on the web interface. Please take careful note of the Submission ID when you submit. Please communicate this ID to us in your correspondence.

GSIS is now an Open Access journal! All article publishing charges (APC) will be covered, so authors will have the benefits of open access at no cost. Perspective authors are recommended to prepare their manuscript by following the author instructions of the journal GSIS (Also see www.tandfonline.com/tgsi ).

The VGI-Analytics 2017 workshop will be organised and co-chaired by:

  • Peter Mooney: Maynooth University, Ireland; Email: Peter.Mooney@nuim.ie
  • Alexander Zipf: University of Heidelberg, Germany; Email: zipf@uni-heidelberg.de
  • Jamal Jokar: Aalborg University Copenhagen, Denmark; Email: jja@plan.aau.dk
  • Hartwig H. Hochmair: University of Florida, United States; Email: hhhochmair@ufl.edu

They are also the special issue guest editors of the special issue at GSIS.

VGI-Analytics 2017 Topics and Themes

VGI-Analytics 2017 will discuss, but not be limited to, the following topics and themes:

  • Joint analysis of crowd-sourced VGI/social media data originating from different data sources
  • Technical aspects of crowd-sourced data fusion
  • Spatio-temporal analysis of activity patterns for individual users across multiple VGI and/or social media platforms
  • Quality assessment of VGI/social media data through analysis of data from different platforms
  • Analysis of cross-linked data and cross-link editing methods in VGI and social media platforms and its applications
  • New sources of VGI and social media data
  • VGI across different regions and cultures
  • Semantic issues arising from the conflation or cross-linkage of several different sources of VGI
  • Tailoring VGI for different applications

    Timeline journal papers:

  • June 9 2017: CFP of final journal papers ends
  • June 30 2017: Finalized journal papers due
  • September/October 2017: Special Issue in GSIS published.

The set of interactive visualizations “OSMvis” from our GIScience HD team member Franz-Benjamin are now online at: http://osm-vis.geog.uni-heidelberg.de.
Nice work Franz-Benjamin!

OSMvis is a collection of visualizations related to OpenStreetMap (OSM), in particular the OSM database, the OSM wiki, and the use of OSM data in general. OSMvis aims at exploring the generation, modification, and use of OSM by the methods of information visualization.

The visualizations are now updated automatically (in different intervalls depending on the data source).

Enjoy exploring!

Some visualizations are somewhat inspired by work on VGI conceptual data quality like Ballatore & Zipf (2015):

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,

Zusammen mit Heidelberg Mobil International (HDMI) wird das neue „Heidelberg Institute for Geoinformation Technology“ (HeiGIT) dieses Jahr erstmalig auf der CeBIT in Hannover auf dem Smart City Forum vertreten sein.

Dabei stehen ortsbasierte Dienste zur Navigation unter Berücksichtigung vielfältiger Anforderungen im Fokus. Wir zeigen das Potenzial nutzer-generierter OpenStreetMap-Daten und innovativer Geoinformationstechnologien für Smart City-Anwendungen, und stellen dazu neue und innovative Funktionen der Online Routing API OpenRouteService vor.

Die überarbeitete API mit umfangreichen neuen Funktionen und leistungsstärkeren Berechnungen ermöglicht es uns für Ihre Anforderungen schnellere Ergebnisse zu liefern. Die neue Isochronen API wird verwendet um die Erreichbarkeit von Orten zu bestimmen. Außerdem haben wir die Nutzeroberfläche überarbeitet oder die Möglichkeit eingeführt, Erreichbarkeiten von mehreren Orten gleichzeitig berechnen zu lassen. So können überlappende Regionen, die von mehreren Orten gleichermaßen zugänglich sind, identifiziert werden.


Darüber hinaus werden wir einen neuen OpenRouteService.org für Katastrophen vorstellen. Die Daten in diesem Service werden innerhalb sehr kurzer Zeit aktualisiert, da Freiwillige bei Katastrophen in hoher Frequenz relevante Informationen zu OpenStreetMap beitragen und hochaktuelle Informationen dringend für die Logistik im Katastrophenmanagement benötigt werden.

Neben den Navigationsdiensten stellen wir zwei weitere Anwendungen vor, die spezielle Daten aus OpenStreetMap aufbereiten und als WebGIS zur Verfügung stellen: OSM LanduseLandcover bietet speziell in Bezug auf Landnutzungs- und Landbedeckung aufbereitete Daten aus OSM an, die z.B. für Planungszecke genutzt werden können. HistOSM.org visualisiert historisch relevante Objekte aus OpenStreetMap für Anwendungen in den Bereichen Kultur und Tourismus. Bei beiden unterstützen dynamische Statistiken zu den am häufigsten verwendeten Objektkategorien im aktuellen Kartenausschnitt die visuelle Exploration der Daten.

Da unsere Dienste auf nutzergenerierten Geodaten basieren, arbeiten wir ebenfalls aktiv an Werkzeugen zur Qualitätsbewertung dieser Daten. Hierzu zählt zum Beispiel Data Mining unter Nutzung der Datenhistorie. Gerne bieten wir Ihnen Dienstleistungen zur Analyse der Datenqualität von OpenStreetMap an.

Wir laden Sie herzlich ein, uns im Smart City Forum (Halle 7) auf der CeBIT in Hannover vom 20.-24.03.2017 zu besuchen. Wenn Sie daran interessiert sind, uns in Hannover zu treffen, kontaktieren Sie uns gerne im Vorfeld (marx@uni-heidelberg.de), da wir Ihnen kostenlose Eintrittskarten zur Verfügung stellen können.

Heidelberg Institute for Geoinformation Technology (HeiGIT)
Ein Projekt mit Core-Funding der Klaus Tschira Stiftung, Heidelberg
Universität Heidelberg
Berliner Str. 48 (Mathematikon)
69120 Heidelberg

http://openrouteservice.org http://osmlanduse.org/ http://histosm.org https://www.facebook.com/GIScienceHeidelberg

Three talks from GIScience Heidelberg were given at the Annual Meeting 2017 of the DGPF (German Society for Photogrammetry, Remote Sensing and Geoinformation) on 9 March 2017. Thanks a lot to Benni, Tomás and Sebastian for the very nice talks. More technical infos on the presented research can be found in the previous blog post - here you find some visual impressions of the keynote by Prof. Doneus and the Geoinformatics sessions:

Crowdsourced Geographic Information (CGI) has emerged as a potential source of geographic information for different domains. Despite advantages associated with it, such information lacks quality assurance, since it is provided by different individuals. Several authors have investigated different approaches to assess CGI quality. Some of the existing methods have been summarized in different classification schemas. However, there are little works that propose a framework of the methods used to assess the quality of CGI in absence of authoritative data, yet some deal with specific cases e.g. for intrinsic OSM quality analysis (Barron et al. 2013) or for conceptual VGI (Ballatore & Zipf 2015). Based on a systematic literature review (similar to the approach of Steiger et al. 2015 for Twitter Analytics), in a recently accepted paper (Degrossi et al. 2017) we propose a framework of methods for assessing the quality of CGI without authoritative data. We identified 8 types of methods that can be used to assess the quality of different VGI sources. These are:
- Geographic context,
- Redundancy of volunteered contribution,
- Scoring volunteers’ contribution,
- Automatic location checking,
- Spatiotemporal clustering,
- Volunteer’s profile & reputation,
- Identify/correct by crowd and
- Historical data analysis
In our framework, we categorize the methods according to
(i) the CGI source,
(ii) the type of reference data,
(iii) the approach employed and
(iv) the temporality of the method.
Unlike the works in the literature, here we provide a basis of methods that can be employed in each CGI source. By developing this framework, we aim at assisting the quality assessment in new and existing crowdsourcing-based platforms. The assessment is an important step in all CGI sources since the information comes from unknown sources and with unknown quality. In order to use the framework, three factors should be consider, i.e. the CGI source, the approach chosen, the reference data available, and the characteristics of the dataset. Besides this, the scientific community can also benefit from the results of our framework because it provides an overview of existing methods, but also possibilities for future research directions.

Degrossi, L.C.; Albuquerque, J.P.d.; Rocha, R.d.S; Zipf, A. (2017): A Framework of Quality Assessment Methods for Crowdsourced Geographic Information: a Systematic Literature Review. ISCRAM 2017. 14th International Conference on Information Systems for Crisis Response And Management. Albi, France. (accepted)

Ballatore, A. and Zipf, A. (2015): A Conceptual Quality Framework for Volunteered Geographic Information. COSIT 2015 - CONFERENCE ON SPATIAL INFORMATION THEORY XII, Santa Fe, NM, USA, October 12-16, 2015, Proceedings (pp. 89–107). Springer International Publishing. http://doi.org/10.1007/978-3-319-23374-1_5

Barron, C., Neis, P. & Zipf, A. (2013): A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis. , Transactions in GIS, 18(6), 877–895. DOI: 10.1111/tgis.12073.

Steiger, E., de Albuquerque, J. P., & Zipf, A. (2015). An Advanced Systematic Literature Review on Spatiotemporal Analyses of Twitter Data. Transactions in GIS, 19(6), 809–834. http://doi.org/10.1111/tgis.12132

Crowd assisted sensing and crowdsourcing, as well as their underlying pervasive systems and communications are a fast growing research area and one of the enabling technologies of smart cities and smart infrastructures, as well as important building blocks in healthcare monitoring and vehicular technologies. Crowd assisted sensing (often called participatory sensing) opens new ways for data collection which can enable the development of highly scalable and successful pervasive applications and services.
These are topics of the 4th International Workshop on Crowd Assisted Sensing, Pervasive Systems and Communications (CASPer 2017). This workshop is held in conjunction with the 15th IEEE International Conference on Pervasive Computing and Communications, PerCom 2017, in Kona, Hawaii, March 13-17 , sponsored among others by the IEEE Computer Society and the National Science Foundation NSF. IEEE PerCom is dealing with a range of topics such as mobile and distributed computing, sensor systems, ambient intelligence, and smart devices and has distinguished keynote speakers like John Krumm (Microsoft Research) and Hui Lei (IBM, Watson Cloud).
Alexander Zipf (GIScience Heidelberg/ HeiGIT) is invited Panel Member at the panel session of CASPer 2017. The panel will discuss questions related to the issue of processing unstructured Big Data, as this is currently one of the most challenging problems facing Data Scientists. In this panel we will explore how crowdsourcing can help big data by leveraging the power of the crowd to make sense of the data. Examples from Heidelberg include VGI Quality Analytics and deriving new information from VGI/OSM the Social Web and Geo-Microtasking (e.g. MapSwipe) for example through Deep Learning.

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