2013, Kisilevich, Slava, Keim, Daniel A., Andrienko, Natalia, Andrienko, Gennady L.

Due to the pervasiveness of positioning technology combined with the proliferation of socially-oriented web sites, community-contributed spatio-temporal data of people’s historical positions are available today in large amounts. The analysis of these data is valuable to scientists and can provide important information about people’s behavior, their movement, geographical places, and events. In this paper, we develop a conceptual framework and outline a methodology that allows us to analyze events and places using geotagged photo collections shared by people from many countries. These data are often semantically annotated by titles and tags that are useful for learning facts about the geographical places and for detecting events occurring in these places. The knowledge obtained through our analysis carries an additional benefit. For example, it may also be utilized by local authorities, service providers, tourist agencies, in sociological and anthropological studies or for building user centric applications like tour recommender systems. We provide a conceptual foundation for the analysis of spatio-temporal data of places visited by people worldwide using community contributed geotagged photo collections. First, we define several types of spatio-temporal clusters of people’s visits. Second, we discuss methods that can be used for analysis of these clusters. Third, we offer an analysis of tourist activities in Switzerland based on a case study.

2010, Jankowski, Piotr, Andrienko, Natalia, Andrienko, Gennady, Kisilevich, Slava

This article presents a geovisual analytics approach to discovering people's preferences for landmarks and movement patterns from photos posted on the Flickr website. The approach combines an exploratory spatio-temporal analysis of geographic coordinates and dates representing locations and time of taking photos with basic thematic information available through the Google Maps Web mapping service, and interpretation of the analyzed area. The article describes data aggregation and filtering techniques to reduce the size of the dataset and focuses on information addressing research questions. The results of analysis for the Seattle metropolitan area help to distinguish between sites that are occasionally popular among the photographers and can be considered as potential attractions from sites that are regularly visited and already known as city landmarks. The analysis of photographers' movements across the metropolitan area shows that most photographers' itineraries are short and highly localized.

2009, Andrienko, Gennady, Andrienko, Natalia, Bak, Peter, Kisilevich, Slava, Keim, Daniel A.

Space- and time-referenced data published on the Web by general people can be viewed in a dual way: as independent spatio-temporal events and as trajectories of people in the geographical space. These two views suppose different approaches to the analysis, which can yield different kinds of valuable knowledge about places and about people. We present several analysis methods corresponding to these two views. The methods are suited to the large amounts of the data.

2011, Kisilevich, Slava, Keim, Daniel A., Andrienko, Natalia, Andrienko, Gennady

Due to the pervasiveness of positioning technology combined with the pro-liferation of social-oriented web sites, community-contributed spatio-temporal data of people's historical positions are available today in large amounts. The analysis of these data is valuable to scientists and can pro-vide important information about people's behavior, their movement, geo-graphical places, and events. In this paper, we develop a conceptual framework and outline a methodology that allows to analyze events and places using geotagged photo collections shared by people from many countries. These data are often semantically annotated by titles and tags that are useful for learning facts about the geographical places and for de-tecting events occurring in these places. The knowledge obtained through our analysis carries an additional benefit. For example, it may also be uti-lized by local authorities, service providers, tourist agencies, in sociologi-cal and anthropological studies or for building user centric applications like tour recommender systems. We provide a conceptual foundation for the analysis of spatio-temporal data of places visited by people worldwide using community contributed geotagged photo collections. First, we define several types of spatio-temporal clusters of people's visits. Second, we dis-cuss methods that can be used for analysis of these clusters. Third, we of-fer an analysis of tourist activities in Switzerland based on a case study.

2009-10, Andrienko, Gennady, Andrienko, Natalia, Bak, Peter, Kisilevich, Slava, Keim, Daniel A.

Space- and time-referenced data published on the Web by general people can be viewed in a dual way: as independent spatiotemporal events and as trajectories of people in the geographical space. These two views suppose different approaches to the analysis, which can yield different kinds of valuable knowledge about places and about people. We present several analysis methods corresponding to these two views. The methods are suited to the large amounts of the data.

2010-07, Kisilevich, Slava, Krstajic, Milos, Keim, Daniel A., Andrienko, Natalia, Andrienko, Gennady

Photo-sharing websites such as Flickr and Panoramio contain millions of geotagged images contributed by people from all over the world. Characteristics of these data pose new challenges in the domain of spatio-temporal analysis. In this paper, we define several different tasks related to analysis of attractive places, points of interest and comparison of behavioral patterns of different user communities on geotagged photo data. We perform analysis and comparison of temporal events, rankings of sightseeing places in a city, and study mobility of people using geotagged photos. We take a systematic approach to accomplish these tasks by applying scalable computational techniques, using statistical and data mining algorithms, combined with interactive geo-visualization. We provide exploratory visual analysis environment, which allows the analyst to detect spatial and temporal patterns and extract additional knowledge from large geotagged photo collections. We demonstrate our approach by applying the methods to several regions in the world.

2009, Keim, Daniel A., Bak, Peter, Kisilevich, Slava, Andrienko, Natalia, Andrienko, Gennady

Space- and time-referenced data published on the Web by general people can be viewed in a dual way: as independent spatio-temporal events and as trajectories of people in the geographical space. These two views suppose different approaches to the analysis, which can yield different kinds of valuable knowledge about places and about people. We present several analysis methods corresponding to these two views. The methods are suited to the large amounts of the data.