A review of volunteered geographic information quality assessment methods
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paper_title: Exploring place through user-generated content: Using Flickr to describe city cores

paper_content:

Terms used to describe city centers, such as Downtown, are key concepts in everyday or vernacular language. Here, we explore such language by harvesting georeferenced and tagged metadata associated with 8 million Flickr images and thus consider how large numbers of people name city core areas. The nature of errors and imprecision in tagging and georeferencing are quantified, and automatically generated precision measures appear to mirror errors in the positioning of images. Users seek to ascribe appropriate semantics to images, though bulk-uploading and bulk-tagging may introduce bias. Between 0.5–2% of tags associated with georeferenced images analyzed describe city core areas generically, while 70% of all georeferenced images analyzed include specific place name tags, with place names at the granularity of city names being by far the most common. Using Flickr metadata, it is possible not only to describe the use of the term Downtown across the USA, but also to explore the borders of city center neighborhoods at the level of individual cities, whilst accounting for bias by the use of tag profiles.
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paper_title: SensePlace2: GeoTwitter analytics support for situational awareness

paper_content:

Geographically-grounded situational awareness (SA) is critical to crisis management and is essential in many other decision making domains that range from infectious disease monitoring, through regional planning, to political campaigning. Social media are becoming an important information input to support situational assessment (to produce awareness) in all domains. Here, we present a geovisual analytics approach to supporting SA for crisis events using one source of social media, Twitter. Specifically, we focus on leveraging explicit and implicit geographic information for tweets, on developing place-time-theme indexing schemes that support overview+detail methods and that scale analytical capabilities to relatively large tweet volumes, and on providing visual interface methods to enable understanding of place, time, and theme components of evolving situations. Our approach is user-centered, using scenario-based design methods that include formal scenarios to guide design and validate implementation as well as a systematic claims analysis to justify design choices and provide a framework for future testing. The work is informed by a structured survey of practitioners and the end product of Phase-I development is demonstrated / validated through implementation in SensePlace2, a map-based, web application initially focused on tweets but extensible to other media.
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paper_title: Social and News Media Enable Estimation of Epidemiological Patterns Early in the 2010 Haitian Cholera Outbreak

paper_content:

During infectious disease outbreaks, data collected through health institutions and official reporting structures may not be available for weeks, hindering early epidemiologic assessment. By contrast, data from informal media are typically available in near real-time and could provide earlier estimates of epidemic dynamics. We assessed correlation of volume of cholera-related HealthMap news media reports, Twitter postings, and government cholera cases reported in the first 100 days of the 2010 Haitian cholera outbreak. Trends in volume of informal sources significantly correlated in time with official case data and was available up to 2 weeks earlier. Estimates of the reproductive number ranged from 1.54 to 6.89 (informal sources) and 1.27 to 3.72 (official sources) during the initial outbreak growth period, and 1.04 to 1.51 (informal) and 1.06 to 1.73 (official) when Hurricane Tomas afflicted Haiti. Informal data can be used complementarily with official data in an outbreak setting to get timely estimates of disease dynamics.
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paper_title: Citizens as Sensors: The World of Volunteered Geography

paper_content:

In recent months there has been an explosion of interest in using the Web to create, assemble, and disseminate geographic information provided voluntarily by individuals. Sites such as Wikimapia and OpenStreetMap are empowering citizens to create a global patchwork of geographic information, while Google Earth and other virtual globes are encouraging volunteers to develop interesting applications using their own data. I review this phenomenon, and examine associated issues: what drives people to do this, how accurate are the results, will they threaten individual privacy, and how can they augment more conventional sources? I compare this new phenomenon to more traditional citizen science and the role of the amateur in geographic observation.
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paper_title: Campus Guidance System for International Conferences Based on OpenStreetMap

paper_content:

We present a web-based, multi-lingual, campus guidance system with emphasis on pedestrian navigation aimed at providing support for delegates attending International Conferences at the National University of Ireland Maynooth (NUIM) campus. A special campus guidance system could improve the logistics of the conference and potentially attract more delegates to the conference. The Cloudmade Web Map Lite API which uses OpenStreetMap has been used for creating this interface. The system generates shortest pedestrian paths using both outdoor pavements and indoor corridors between various buildings and points of interests (POI). For visual assistance in pedestrian navigation geotagged images are used along the path at certain points in the route, such as road intersections, when the user needs to get their orientation correct. The interface is currently available in both English and Chinese language.
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paper_title: Where’s downtown? behavioral methods for determining referents of vague spatial queries

paper_content:

Humans think and talk about regions and spatial relations imprecisely, in terms of vague concepts that are fuzzy or probabilistic (e.g., downtown, near). The functionality of geographic information systems will be increased if they can interpret vague queries. We discuss traditional and newer approaches to defining and modeling spatial queries. Most of the research on vague concepts in information systems has focussed on mathematical and computational implementation. To complement this, we discuss behavioral-science methods for determining the referents of vague spatial terms, particularly vague regions. We present a study of the empirical determination of downtown Santa Barbara. We conclude with a discussion of prospects and problems for integrating vague concepts into geographic information systems.
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paper_title: Web 2.0 geotagged photos: Assessing the spatial dimension of the phenomenon

paper_content:

Among popular Web 2.0 applications are the social networking, photo-sharing websites like Flickr, Panoramio, Picasa Web, and Geograph. The phenomenon of user-generated content and the increased presence of geographic information in such applications have motivated researchers to consider them as a source of geographic information. In this paper we question whether such web applications can serve as reliable sources of spatial content. We differentiate between spatially explicit and implicit applications, in accordance to their declared aims, and evaluate if they have an impact on the spatial distribution of geotagged photos for Great Britain. We also compare the spatial distribution of the photos submitted with population data, and the patterns of contribution to these sources over a period of 18 months. Finally, at a larger scale, we examine the spatial distribution of photos and their spatial density for 15 test areas and look into issues such as data currency and user behaviour. Our findings show that only web applications that urge users to interact directly with spatial entities can serve as reliable, universal sources of spatial content.
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paper_title: Earthquake shakes Twitter users: real-time event detection by social sensors

paper_content:

Twitter, a popular microblogging service, has received much attention recently. An important characteristic of Twitter is its real-time nature. For example, when an earthquake occurs, people make many Twitter posts (tweets) related to the earthquake, which enables detection of earthquake occurrence promptly, simply by observing the tweets. As described in this paper, we investigate the real-time interaction of events such as earthquakes in Twitter and propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features such as the keywords in a tweet, the number of words, and their context. Subsequently, we produce a probabilistic spatiotemporal model for the target event that can find the center and the trajectory of the event location. We consider each Twitter user as a sensor and apply Kalman filtering and particle filtering, which are widely used for location estimation in ubiquitous/pervasive computing. The particle filter works better than other comparable methods for estimating the centers of earthquakes and the trajectories of typhoons. As an application, we construct an earthquake reporting system in Japan. Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earthquake with high probability (96% of earthquakes of Japan Meteorological Agency (JMA) seismic intensity scale 3 or more are detected) merely by monitoring tweets. Our system detects earthquakes promptly and sends e-mails to registered users. Notification is delivered much faster than the announcements that are broadcast by the JMA.
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paper_title: Tracing the German centennial flood in the stream of tweets: first lessons learned

paper_content:

Social microblogging services such as Twitter result in massive streams of georeferenced messages and geolocated status updates. This real-time source of information is invaluable for many application areas, in particular for disaster detection and response scenarios. Consequently, a considerable number of works has dealt with issues of their acquisition, analysis and visualization. Most of these works not only assume an appropriate percentage of georeferenced messages that allows for detecting relevant events for a specific region and time frame, but also that these geolocations are reasonably correct in representing places and times of the underlying spatio-temporal situation. In this paper, we review these two key assumption based on the results of applying a visual analytics approach to a dataset of georeferenced Tweets from Germany over eight months witnessing several large-scale flooding situations throughout the country. Our results confirm the potential of Twitter as a distributed 'social sensor' but at the same time highlight some caveats in interpreting immediate results. To overcome these limits we explore incorporating evidence from other data sources including further social media and mobile phone network metrics to detect, confirm and refine events with respect to location and time. We summarize the lessons learned from our initial analysis by proposing recommendations and outline possible future work directions.
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paper_title: Assuring the quality of volunteered geographic information

paper_content:

Abstract Volunteered geographic information (VGI) is a phenomenon of recent years, offering an alternative mechanism for the acquisition and compilation of geographic information. As such it offers substantial advantages, but suffers from a general lack of quality assurance. We discuss the issues involved in the determination of quality for geospatial data, and trace the history of research on VGI quality. We describe three approaches to quality assurance, which we term the crowd-sourcing, social, and geographic approaches respectively. We discuss the advantages and limitations of each, and the research that will be needed to operationalize the geographic approach.
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paper_title: Digital Earth from vision to practice: making sense of citizen-generated content

paper_content:

Abstract The vision of Digital Earth (DE) put recently forward under the auspices of the International Society for DE extends the paradigm of spatial data infrastructures by advocating an interactive and dynamic framework based on near-to-real time information from sensors and citizens. This paper contributes to developing that vision and reports the results of a two-year research project exploring the extent to which it is possible to extract information useful for policy and science from the large volumes of messages and photos being posted daily through social networks. Given the noted concerns about the quality of such data in relation to that provided by authoritative sources, the research has developed a semi-automatic workflow to assess the fitness for purpose of data extracted from Twitter and Flickr, and compared them to that coming from official sources, using forest fires as a case study. The findings indicate that we were able to detect accurately six of eight major fires in France in the summer of 2011, with another four detected by the social networks but not reported by our official source, the European Forest Fire Information Service. These findings and the lessons learned in handling the very large volumes of unstructured data in multiple languages discussed in this study provide useful insights into the value of social network data for policy and science, and contribute to advancing the vision of DE.
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paper_title: Do users ignore spatial data quality? A decision-theoretic perspective

paper_content:

Risk analysis (RA) has been proposed as a means of assessing fitness for use of spatial data but is only rarely adopted. The proposal is that better decisions can be made by accounting for risks due to errors in spatial data. Why is RA so rarely adopted? Most geographical information science (GISc) literature stresses educational and technical constraints. In this article we propose, based on decision theory, a number of hypotheses for why the user would be more or less willing to spend resources on RA. The hypotheses were tested with a questionnaire, which showed that the willingness to spend resources on RA depends on the presence of feedback mechanisms in the decision-making process, on how much is at stake, and to a minor extent on how well the decision-making process can be modeled.
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paper_title: Communication and Persuasion: Psychological Studies of Opinion Change

paper_content:

This is a report of a program of coordinated systematic research on variables determining the effects of persuasive communication.
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paper_title: Provenance and Volunteered Geographic Information

paper_content:

Provenance (also called lineage) is metadata about an object's origin and history (Bose and Frew, 2005.) The term is conventionally applied to works of art, whose provenance is the documented chain of custody of the object, from creator to current custodian. Reliable provenance (assurance that the object has never been without reliable custody) is a necessary precondition for establishing an artwork's authenticity. For information, the notion of provenance broadens to include the transformations applied between information's origins and its current form. (One can think of artwork provenance as special case where a change in custody equates to an identity transformation.) In my own work in data-intensive Earth science, a typical processing sequence includes: data acquisition by a satellite remote sensing system, formatting, calibration, projection, subsetting, re-projection, and analysis; the end product being a quantized field representing some Earth surface phenomenon such as snow cover or ocean color. The provenance of the end products is conceptually a directed acyclic graph leading back through transformations and intermediate data to the original satellite and ancillary data. Note that this graph can be traversed in either direction; i.e., one can determine both the "ancestors" and the "descendants" of any particular data object (e.g., file) or transformation instance (e.g., program invocation.) The provenance of scientific information can be exploited to answer common, non-trivial questions. For example, forward (descendant) provenance can identify data products that were derived, however indirectly from suspect (e.g., miscalibrated) source data. Backward (ancestor) provenance can be used to help identify the source(s) of observed anomalies in a data product. I assume that provenance will be useful, perhaps even critical, for the broader acceptance and utilization of volunteered geographic information (VGI), for three reasons. First, geographic information collected or manipulated by nonspecialists is more likely to contain unnoticed errors or biases. If and when these errors or biases are discovered, provenance can document (and thus help mitigate the consequences of) their propagation. Second, provenance can substitute for other missing or incorrect metadata, by identifying antecedent objects from which such metadata may be inherited. And finally, provenance can identify the humans or institutions involved in the information's creation and manipulation, and thus provide the foundations for judgments about quality and trust. Supplying provenance manually is tedious, and like most human-created metadata, it is usually distinguished by its absence. A conspicuous, if partial, exception to this rule is, of course, article citations, which constitute a weak form of provenance in that it can usually be assumed that the references are all in some way ancestral to the referring document. The twin motivations of scientific integrity and professional advancement help ensure that this particular form of metadata is consistently supplied. The exception is partial, however, since the nature of the transformation is not explicitly specified; all we can state
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paper_title: Addressing Vagueness in Volunteered Geographic Information (VGI) - A Case Study

paper_content:

The stakeholders that are directly affected by the climate change might become an invaluable source of information if their perceptions are shared with the general public and the scientific community. Such Volunteered Geographic Information (VGI) about environmental phenomena have however a certain degree of vagueness, as they describe only a spatiotemporal and thematic snapshot of the entire phenomenon. To reconcile vagueness of stakeholder’s perception of environmental phenomenon with the ‘crisp objects’ vision of current VGI, we propose a hybrid strategy, combining an Open Gazetteer approach, and the concept of Degree of Truth. On this basis, we describe eVGI, an innovative web application based on a service-oriented architecture. We implemented eVGI as a prototype, addressing a real-world case study implying stakeholders from forestry, fishing and reindeer husbandry sectors in the Barents region.
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paper_title: Gazetiki: automatic creation of a geographical gazetteer

paper_content:

Geolocalized databases are becoming necessary in a wide variety of application domains. Thus far, the creation of such databases has been a costly, manual process. This drawback has stimulated interest in automating their construction, for example, by mining geographical information from the Web. Here we present and evaluate a new automated technique for creating and enriching a geographical gazetteer, called Gazetiki. Our technique merges disparate information from Wikipedia, Panoramio, and web search engines in order to identify geographical names, categorize these names, find their geographical coordinates and rank them. The information produced in Gazetiki enhances and complements the Geonames database, using a similar domain model. We show that our method provides a richer structure and an improved coverage compared to another known attempt at automatically building a geographic database and, where possible, we compare our Gazetiki to Geonames.
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paper_title: Usage patterns of collaborative tagging systems

paper_content:

Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamic aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given URL. We also present a dynamic model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge.
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paper_title: Tracing the German centennial flood in the stream of tweets: first lessons learned

paper_content:

Social microblogging services such as Twitter result in massive streams of georeferenced messages and geolocated status updates. This real-time source of information is invaluable for many application areas, in particular for disaster detection and response scenarios. Consequently, a considerable number of works has dealt with issues of their acquisition, analysis and visualization. Most of these works not only assume an appropriate percentage of georeferenced messages that allows for detecting relevant events for a specific region and time frame, but also that these geolocations are reasonably correct in representing places and times of the underlying spatio-temporal situation. In this paper, we review these two key assumption based on the results of applying a visual analytics approach to a dataset of georeferenced Tweets from Germany over eight months witnessing several large-scale flooding situations throughout the country. Our results confirm the potential of Twitter as a distributed 'social sensor' but at the same time highlight some caveats in interpreting immediate results. To overcome these limits we explore incorporating evidence from other data sources including further social media and mobile phone network metrics to detect, confirm and refine events with respect to location and time. We summarize the lessons learned from our initial analysis by proposing recommendations and outline possible future work directions.
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paper_title: Geotagging Where Cyberspace Comes to Your Place

paper_content:

The combination of GPS services and information technology is increasing with the use of geotagging now occurring as a default action in many commodity based devices functionality for example mobile phones and cameras. The camera in suitably enabled phones takes the picture and embeds GPS co-ordinates of the location into the metadata of the resulting image file. Furthermore there are now online services such as foursquare that are targeted at the geotagging or geocaching community. In addition to this overtly designed service other social online services such Flickr, Twitter are providing a means of geotagging users. This enablement of technology has significant and profound effects on bpersonal security and also extending into corporate
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paper_title: The San Francisco public art map application: using VGI and social media to complement institutional data sources

paper_content:

The City of San Francisco is endowed with a rich variety of art in public spaces. The San Francisco Arts Commission (SFAC) alone curates over 800 pieces of public art. In addition to the SFAC holdings, there are colorful murals, landscaped parks, art monuments, street art of mysterious origin, and pieces curated by other organizations. People taking public transportation, playing in parks, reading in libraries, or performing daily tasks that take them into San Francisco's built environment see art. There is no one place to learn about all the different art freely available. Existing mobile and web applications that map art locations silo information by covering only certain categories of art such as publicly funded pieces, murals, or street art. No application uses social media as a source of art data. In contrast, the San Francisco Public Art Map presented in this paper (SFPAM at www.sfpublicart.com) is a web application that aggregates location-based publicly accessible art data in San Francisco. SFPAM addresses the gap identified in other applications. The application has three levels of art data curation: organizational, administrative, and volunteered. The project compiles art location information from disparate institutional sources that fund and curate public art. Administrative scraping of web sites and local knowledge create additional layers. Volunteered Geographic Information (VGI) creates a dynamic layer of pictures and comments on public art through social media streams such as Flickr, Panoramio, Instagram, and YouTube from contributors who unknowingly take on the role of curator through posting and tagging images. Combining data from multiple curators creates a richer set of art data points for visitors and residents in San Francisco interested in public art. Assessment of SFAC's art location data reveals quality issues with positional accuracy. Some points are located miles from their actual location and multiple points are collocated. Comparison of sample points from the SFAC dataset and peer reviewed VGI suggests that VGI can improve the quality of the application dataset.
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paper_title: Social networks that matter: Twitter under the microscope

paper_content:

Scholars, advertisers and political activists see massive online social networks as a representation of social interactions that can be used to study the propagation of ideas, social bond dynamics and viral marketing, among others. But the linked structures of social networks do not reveal actual interactions among people. Scarcity of attention and the daily rythms of life and work makes people default to interacting with those few that matter and that reciprocate their attention. A study of social interactions within Twitter reveals that the driver of usage is a sparse and hidden network of connections underlying the “declared” set of friends and followers.
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paper_title: Information credibility on twitter

paper_content:

We analyze the information credibility of news propagated through Twitter, a popular microblogging service. Previous research has shown that most of the messages posted on Twitter are truthful, but the service is also used to spread misinformation and false rumors, often unintentionally. On this paper we focus on automatic methods for assessing the credibility of a given set of tweets. Specifically, we analyze microblog postings related to "trending" topics, and classify them as credible or not credible, based on features extracted from them. We use features from users' posting and re-posting ("re-tweeting") behavior, from the text of the posts, and from citations to external sources. We evaluate our methods using a significant number of human assessments about the credibility of items on a recent sample of Twitter postings. Our results shows that there are measurable differences in the way messages propagate, that can be used to classify them automatically as credible or not credible, with precision and recall in the range of 70% to 80%.
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paper_title: ScatterBlogs2: Real-Time Monitoring of Microblog Messages through User-Guided Filtering

paper_content:

The number of microblog posts published daily has reached a level that hampers the effective retrieval of relevant messages, and the amount of information conveyed through services such as Twitter is still increasing. Analysts require new methods for monitoring their topic of interest, dealing with the data volume and its dynamic nature. It is of particular importance to provide situational awareness for decision making in time-critical tasks. Current tools for monitoring microblogs typically filter messages based on user-defined keyword queries and metadata restrictions. Used on their own, such methods can have drawbacks with respect to filter accuracy and adaptability to changes in trends and topic structure. We suggest ScatterBlogs2, a new approach to let analysts build task-tailored message filters in an interactive and visual manner based on recorded messages of well-understood previous events. These message filters include supervised classification and query creation backed by the statistical distribution of terms and their co-occurrences. The created filter methods can be orchestrated and adapted afterwards for interactive, visual real-time monitoring and analysis of microblog feeds. We demonstrate the feasibility of our approach for analyzing the Twitter stream in emergency management scenarios.
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paper_title: Thematic Patterns in Georeferenced Tweets through Space-Time Visual Analytics

paper_content:

An exploratory study of the potential of georeferenced Twitter data (using tweets from Seattle-area residents over a two-month period) extracts knowledge about people's everyday life.
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paper_title: SensePlace2: GeoTwitter analytics support for situational awareness

paper_content:

Geographically-grounded situational awareness (SA) is critical to crisis management and is essential in many other decision making domains that range from infectious disease monitoring, through regional planning, to political campaigning. Social media are becoming an important information input to support situational assessment (to produce awareness) in all domains. Here, we present a geovisual analytics approach to supporting SA for crisis events using one source of social media, Twitter. Specifically, we focus on leveraging explicit and implicit geographic information for tweets, on developing place-time-theme indexing schemes that support overview+detail methods and that scale analytical capabilities to relatively large tweet volumes, and on providing visual interface methods to enable understanding of place, time, and theme components of evolving situations. Our approach is user-centered, using scenario-based design methods that include formal scenarios to guide design and validate implementation as well as a systematic claims analysis to justify design choices and provide a framework for future testing. The work is informed by a structured survey of practitioners and the end product of Phase-I development is demonstrated / validated through implementation in SensePlace2, a map-based, web application initially focused on tweets but extensible to other media.
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paper_title: Social and News Media Enable Estimation of Epidemiological Patterns Early in the 2010 Haitian Cholera Outbreak

paper_content:

During infectious disease outbreaks, data collected through health institutions and official reporting structures may not be available for weeks, hindering early epidemiologic assessment. By contrast, data from informal media are typically available in near real-time and could provide earlier estimates of epidemic dynamics. We assessed correlation of volume of cholera-related HealthMap news media reports, Twitter postings, and government cholera cases reported in the first 100 days of the 2010 Haitian cholera outbreak. Trends in volume of informal sources significantly correlated in time with official case data and was available up to 2 weeks earlier. Estimates of the reproductive number ranged from 1.54 to 6.89 (informal sources) and 1.27 to 3.72 (official sources) during the initial outbreak growth period, and 1.04 to 1.51 (informal) and 1.06 to 1.73 (official) when Hurricane Tomas afflicted Haiti. Informal data can be used complementarily with official data in an outbreak setting to get timely estimates of disease dynamics.
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paper_title: Credibility ranking of tweets during high impact events

paper_content:

Twitter has evolved from being a conversation or opinion sharing medium among friends into a platform to share and disseminate information about current events. Events in the real world create a corresponding spur of posts (tweets) on Twitter. Not all content posted on Twitter is trustworthy or useful in providing information about the event. In this paper, we analyzed the credibility of information in tweets corresponding to fourteen high impact news events of 2011 around the globe. From the data we analyzed, on average 30% of total tweets posted about an event contained situational information about the event while 14% was spam. Only 17% of the total tweets posted about the event contained situational awareness information that was credible. Using regression analysis, we identified the important content and sourced based features, which can predict the credibility of information in a tweet. Prominent content based features were number of unique characters, swear words, pronouns, and emoticons in a tweet, and user based features like the number of followers and length of username. We adopted a supervised machine learning and relevance feedback approach using the above features, to rank tweets according to their credibility score. The performance of our ranking algorithm significantly enhanced when we applied re-ranking strategy. Results show that extraction of credible information from Twitter can be automated with high confidence.
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paper_title: Moving on Twitter: using episodic hotspot and drift analysis to detect and characterise spatial trajectories

paper_content:

Today, a tremendous source of spatio-temporal data is user generated, so-called volunteered geographic information (VGI). Among the many VGI sources, microblogged services, such as Twitter, are extensively used to disseminate information on a near real-time basis. Interest in analysis of microblogged data has been motivated to date by many applications ranging from trend detection, early disaster warning, to urban management and marketing. One important analysis perspective in understanding microblogged data is based on the notion of drift, considering a gradual change of real world phenomena observed across space, time, content, or a combination thereof. The scientific contribution provided by this paper is the presentation of a systematic framework that utilises on the one hand a Kernel Density Estimation (KDE) to detect hotspot clusters of Tweeter activities, which are episodically sequential in nature. These clusters help to derive spatial trajectories. On the other hand we introduce the concept of drift that characterises these trajectories by looking into changes of sentiment and topics to derive meaningful information. We apply our approach to a Twitter dataset comprising 26,000 tweets. We demonstrate how phenomena of interest can be detected by our approach. As an example, we use our approach to detect the locations of Lady Gaga's concert tour in 2013. A set of visualisations allows to analyse the identified trajectories in space, enhanced by optional overlays for sentiment or other parameters of interest.
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paper_title: Quality in User Generated Spatial Content: A Matter of Specifications

paper_content:

In the last decade, the burst of the Web 2.0 has rapidly increased the amount of user generated content (UGC) on the Internet. Most of Web 2.0 applications allow users to interact with other users and edit website content. This collaborative edition is supposed to improve the content. Nowadays, the amount of people generating online content has dramatically increased. For instance, in the U.S., recent studies show that 35% of Internet users have created content (Flanagin, 2008). A widespread example is the online encyclopedia Wikipedia. It is a valuable source of information though it is not intended to users searching for verified information because it is often anonymous.
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paper_title: Quality Assessment of the French OpenStreetMap Dataset

paper_content:

The concept of Volunteered Geographic Information (VGI) has recently emerged from the new Web 2.0 technologies. The OpenStreetMap project is currently the most significant example of a system based on VGI. It aims at producing free vector geographic databases using contributions from Internet users. Spatial data quality becomes a key consideration in this context of freely downloadable geographic databases. This article studies the quality of French OpenStreetMap data. It extends the work of Haklay to France, provides a larger set of spatial data quality element assessments (i.e. geometric, attribute, semantic and temporal accuracy, logical consistency, completeness, lineage, and usage), and uses different methods of quality control. The outcome of the study raises questions such as the heterogeneity of processes, scales of production, and the compliance to standardized and accepted specifications. In order to improve data quality, a balance has to be struck between the contributors' freedom and their respect of specifications. The development of appropriate solutions to provide this balance is an important research issue in the domain of user-generated content.
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paper_title: A typology for visualizing uncertainty

paper_content:

Information analysts must rapidly assess information to determine its usefulness in supporting and informing decision makers. In addition to assessing the content, the analyst must be confident about the quality and veracity of the information. Visualizations can concisely represent vast quantities of information, thus aiding the analyst to examine larger quantities of material; however, visualization programs are challenged to incorporate a notion of confidence or certainty because the factors that influence the certainty or uncertainty of information vary with the type of information and the type of decisions being made. For example, the assessment of potentially subjective human-reported data leads to a large set of uncertainty concerns in fields such as national security, law enforcement (witness reports), and even scientific analysis where data is collected from a variety of individual observers. What’s needed is a formal model or framework for describing uncertainty as it relates to information analysis, to provide a consistent basis for constructing visualizations of uncertainty. This paper proposes an expanded typology for uncertainty, drawing from past frameworks targeted at scientific computing. The typology provides general categories for analytic uncertainty, a framework for creating task-specific refinements to those categories, and examples drawn from the national security field.
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paper_title: Assuring the quality of volunteered geographic information

paper_content:

Abstract Volunteered geographic information (VGI) is a phenomenon of recent years, offering an alternative mechanism for the acquisition and compilation of geographic information. As such it offers substantial advantages, but suffers from a general lack of quality assurance. We discuss the issues involved in the determination of quality for geospatial data, and trace the history of research on VGI quality. We describe three approaches to quality assurance, which we term the crowd-sourcing, social, and geographic approaches respectively. We discuss the advantages and limitations of each, and the research that will be needed to operationalize the geographic approach.
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paper_title: Measuring Completeness of Building Footprints in OpenStreetMap over Space and Time

paper_content:

Due to financial or administrative constraints, access to official spatial base data is currently limited to a small subset of all potential users in the field of spatial planning and research. This increases the usefulness of Volunteered Geographic Information (VGI), in particular OpenStreetMap (OSM), as supplementary datasets or, in some cases, alternative sources of primary data. In contrast to the OSM street network, which has already been thoroughly investigated and found to be practically complete in many areas, the degree of completeness of OSM data on buildings is still unclear. In this paper we describe methods to analyze building completeness and apply these to various test areas in Germany. Official data from national mapping and cadastral agencies is used as a basis for comparison. The results show that unit-based completeness measurements (e.g., total number or area of buildings) are highly sensitive to disparities in modeling between official data and VGI. Therefore, we recommend object-based methods to study the completeness of OSM building footprint data. An analysis from November 2011 in Germany indicated a completeness of 25% in the federal states of North Rhine-Westphalia and 15% in Saxony. Although further analyses from 2012 confirm that data completeness in Saxony has risen to 23%, the rate of new data input was slowing in the year 2012.
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paper_title: Quality assessment for building footprints data on OpenStreetMap

paper_content:

In the past two years, several applications of generating three-dimensional 3D buildings from OpenStreetMap OSM have been made available, for instance, OSM-3D, OSM2World, OSM Building, etc. In these projects, 3D buildings are reconstructed using the buildings’ footprints and information about their attributes, which are documented as tags in OSM. Therefore, the quality of 3D buildings relies strongly on the quality of the building footprints data in OSM. This article is dedicated to a quality assessment of building footprints data in OSM for the German city of Munich, which is one of the most developed cities in OSM. The data are evaluated in terms of completeness, semantic accuracy, position accuracy, and shape accuracy by using building footprints in ATKIS German Authority Topographic–Cartographic Information System as reference data. The process contains three steps: finding correspondence between OSM and ATKIS data, calculating parameters of the four quality criteria, and statistical analysis. The results show that OSM footprint data in Munich have a high completeness and semantic accuracy. There is an offset of about four meters on average in terms of position accuracy. With respect to shape, OSM building footprints have a high similarity to those in ATKIS data. However, some architectural details are missing; hence, the OSM footprints can be regarded as a simplified version of those in ATKIS data.
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paper_title: Assessment of Logical Consistency in OpenStreetMap Based on the Spatial Similarity Concept

paper_content:

The growth in the number of users and the volume of information in OpenStreetMap (OSM) indicate the success of this VGI-based project in attracting diverse sets of people from all over the world. A huge amount of information is generated daily by non-professional users and OSM faces the challenge of ensuring data quality. Spatial data quality comprises several basic elements; among them, logical consistency concerns the existence of logical contradictions within a dataset. It is one of the most important elements, but has not been studied much in VGI despite the key role in quality assurance. Because of the participatory nature of data collection and entry in OSM, the common consistency checking routines for spatial data should be revised. Since contributors have different views about objects, data integration in OSM may be considered as a form of multi-representation data combination. In this article, the concept of spatial similarity in multi-representation considering three elements, i.e. directional relationships, topological relationships, and metric distance relationships, is used to build a framework to determine the probable inconsistencies in OSM.
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paper_title: Assessing Data Completeness of VGI through an Automated Matching Procedure for Linear Data

paper_content:

New, free and fast growing spatial data sources have appeared online, based on VolunteeredGeographic Information (VGI). OpenStreetMap (OSM) is maybe the most representative project of this trend. Its increasing popularity and density urges researchers on studying its data quality. When this includes comparison with a reference dataset, data matching is necessary for the comparison to be meaningful, usually performed manually at data preparation stage. We propose an automated matching method specifically designed for VGI, based on a multi-stage approach that combines geometric and attribute constraints. We apply it on OSM dataset to compare it against official data from Ordnance Survey. We then show how the results can be used to evaluate data completeness of OSM.
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paper_title: Improving Volunteered Geographic Information Quality Using a Tag Recommender System: The Case of OpenStreetMap

paper_content:

Studies have analyzed the quality of volunteered geographic information (VGI) datasets, assessing the positional accuracy of features and the semantic accuracy of the attributes. While it has been shown that VGI can, in some contexts, reach a high positional accuracy, these studies have also highlighted a large spatial heterogeneity in positional accuracy and completeness, but also concerning the semantics of the objects. Such high semantic heterogeneity of VGI datasets becomes a significant obstacle to a number of possible uses that could be made of the data. This paper proposes an approach for both improving the semantic quality and reducing the semantic heterogeneity of VGI datasets. The improvement of the semantic quality is achieved by using a tag recommender system, called OSMantic, which automatically suggests relevant tags to contributors during the editing process. Such an approach helps contributors find the most appropriate tags for a given object, hence reducing the overall dataset semantic heterogeneity. The approach was implemented into a plugin for the Java OpenStreetMap editor (JOSM) and different examples illustrate how this plugin can be used to improve the quality of VGI data. This plugin has been tested by OSM contributors and evaluated using an online questionnaire. Results of the evaluation suggest a high level of satisfaction from users and are discussed.
---
paper_title: Quality Assessment of the French OpenStreetMap Dataset

paper_content:

The concept of Volunteered Geographic Information (VGI) has recently emerged from the new Web 2.0 technologies. The OpenStreetMap project is currently the most significant example of a system based on VGI. It aims at producing free vector geographic databases using contributions from Internet users. Spatial data quality becomes a key consideration in this context of freely downloadable geographic databases. This article studies the quality of French OpenStreetMap data. It extends the work of Haklay to France, provides a larger set of spatial data quality element assessments (i.e. geometric, attribute, semantic and temporal accuracy, logical consistency, completeness, lineage, and usage), and uses different methods of quality control. The outcome of the study raises questions such as the heterogeneity of processes, scales of production, and the compliance to standardized and accepted specifications. In order to improve data quality, a balance has to be struck between the contributors' freedom and their respect of specifications. The development of appropriate solutions to provide this balance is an important research issue in the domain of user-generated content.
---
paper_title: A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis

paper_content:

OpenStreetMap (OSM) is one of the most popular examples of a Volunteered Geographic Information (VGI) project. In the past years it has become a serious alternative source for geodata. Since the quality of OSM data can vary strongly, different aspects have been investigated in several scientific studies. In most cases the data is compared with commercial or administrative datasets which, however, are not always accessible due to the lack of availability, contradictory licensing restrictions or high procurement costs. In this investigation a framework containing more than 25 methods and indicators is presented, allowing OSM quality assessments based solely on the data's history. Without the usage of a reference data set, approximate statements on OSM data quality are possible. For this purpose existing methods are taken up, developed further, and integrated into an extensible open source framework. This enables arbitrarily repeatable intrinsic OSM quality analyses for any part of the world.
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paper_title: Using Semantic Techology for Consistency Checking of Road Signs

paper_content:

With the cities ever growing and evolving much faster than before, effectively managing road signs is a major problem, in particular checking the positioning and contents of road signs in compliance with related road sign regulations (RSRs) and validating if the newly built road signs are consistent with existing road signs according to RSRs. In this paper, we discuss challenges in developing road sign management system and propose a data integration solution which provides a basis for intelligent road sign management based upon the LarKC platform. We then present methods for automatically verifying road signs according to RSRs and simulating the process of generating new road signs when new roads are to be built. The proposed system can bring much convinence to decision makers and greatly decrease fees of the city operation.
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paper_title: Topological Consistent Generalization of OpenStreetMap

paper_content:

Since its introduction in 2004, OpenStreetMap (OSM) has become an important source of geospatial information. The spatial data displayed by OSM represents the finest level of detail available. For web-based and mobile mapping applications it is often desirable to reduce the representation of such spatial data using generalization. There are two main reasons for this. Firstly, the spatial size and detail of OSM data is ever increasing and the bandwidth required to transmit this can be significant. Any device which attempts to obtain such data over a network will have finite bandwidth and this may prevent the map being transmitted in its original form. Secondly, many mobile devices used to display OSM data have limited screen resolution and processing power, and can only display a finite amount of detail. One class of generalization algorithm known as simplification methods, attempt to generalize polygon and line features by reducing the number of points or vertices used to represent them. Any simplification technique can be classified as a decomposition or reconstruction technique. Decomposition techniques produce a generalized result by iteratively removing points from the original polygon or line feature in question until a desired scale is reached. Reconstruction techniques produce a generalized result by initially representing the feature in its simplest form; subsequently, points are added in an iterative manner until a desired scale is achieved.
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paper_title: Consistent Handling of Linear Features in Polyline Simplification

paper_content:

Polyline simplification is one of most thoroughly studied subjects in map generalization. It consists in reducing the number of vertices of a polygonal chain in order to represent them at a smaller scale without unnecessary details. Besides its main application in generalization, it is also considerably employed in Geographic Information Systems (GIS) to reduce digital map data for speeding up processing and visualization and to homogenize different data sets in the process of data integration. A variety of techniques has been presented by researchers in different contexts [14, 7, 12, 16].
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paper_title: Exploring place through user-generated content: Using Flickr to describe city cores

paper_content:

Terms used to describe city centers, such as Downtown, are key concepts in everyday or vernacular language. Here, we explore such language by harvesting georeferenced and tagged metadata associated with 8 million Flickr images and thus consider how large numbers of people name city core areas. The nature of errors and imprecision in tagging and georeferencing are quantified, and automatically generated precision measures appear to mirror errors in the positioning of images. Users seek to ascribe appropriate semantics to images, though bulk-uploading and bulk-tagging may introduce bias. Between 0.5–2% of tags associated with georeferenced images analyzed describe city core areas generically, while 70% of all georeferenced images analyzed include specific place name tags, with place names at the granularity of city names being by far the most common. Using Flickr metadata, it is possible not only to describe the use of the term Downtown across the USA, but also to explore the borders of city center neighborhoods at the level of individual cities, whilst accounting for bias by the use of tag profiles.
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paper_title: Accurate Attribute Mapping from Volunteered Geographic Information: Issues of Volunteer Quantity and Quality

paper_content:

Crowdsourcing is a popular means of acquiring data, but the use of such data is limited by concerns with its quality. This is evident within cartography and geographical sciences more generally, with the quality of volunteered geographic information (VGI) recognized as a major challenge to address if the full potential of citizen sensing in mapping applications is to be realized. Here, a means to characterize the quality of volunteers, based only on the data they contribute, was used to explore issues connected with the quantity and quality of volunteers for attribute mapping. The focus was on data in the form of annotations or class labels provided by volunteers who visually interpreted an attribute, land cover, from a series of satellite sensor images. A latent class model was found to be able to provide accurate characterisations of the quality of volunteers in terms of the accuracy of their labelling, irrespective of the number of cases that they labelled. The accuracy with which a volunteer could be ...
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paper_title: Geolocating Static Cameras

paper_content:

A key problem in widely distributed camera networks is locating the cameras. This paper considers three scenarios for camera localization: localizing a camera in an unknown environment, adding a new camera in a region with many other cameras, and localizing a camera by finding correlations with satellite imagery. We find that simple summary statistics (the time course of principal component coefficients) are sufficient to geolocate cameras without determining correspondences between cameras or explicitly reasoning about weather in the scene. We present results from a database of images from 538 cameras collected over the course of a year. We find that for cameras that remain stationary and for which we have accurate image times- tamps, we can localize most cameras to within 50 miles of the known location. In addition, we demonstrate the use of a distributed camera network in the construction a map of weather conditions.
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paper_title: Positional accuracy analysis of Flickr and Panoramio images for selected world regions

paper_content:

Flickr and Panoramio are fast-growing photo-sharing services that contain millions of geotagged images contributed by Web users from all over the world. This study analyses the positional accuracy of 1433 images for 45 areas in four selected world regions by comparing the geotagged position of photos to the manually corrected camera position based on the image content. The analysis reveals a better positional accuracy for Panoramio than for Flickr images, and some effects of image category and world region on positional accuracy. These findings can be helpful when considering Flickr and Panoramio images as data sources for future geo-applications and services.
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paper_title: Using Reverse Viewshed Analysis to Assess the Location Correctness of Visually Generated VGI

paper_content:

With the increased availability of user generated data, assessing the quality and credibility of such data becomes important. In this article, we propose to assess the location correctness of visually generated Vol- unteered Geographic Information (VGI) as a quality reference measure. The location correctness is deter- mined by checking the visibility of the point of interest from the position of the visually generated VGI (observer point); as an example we utilize Flickr photographs. Therefore we first collect all Flickr photo- graphs that conform to a certain point of interest through their textual labelling. Then we conduct a reverse viewshed analysis for the point of interest to determine if it lies within the area of visibility of the observer points. If the point of interest lies outside the visibility of a given observer point, the respective geotagged image is considered to be incorrectly geotagged. In this way, we analyze sample datasets of photographs and make observations regarding the dependency of certain user/photo metadata and (in)correct geotags and labels. In future the dependency relationship between the location correctness and user/photo metadata can be used to automatically infer user credibility. In other words, attributes such as profile completeness, together with location correctness, can serve as a weighted score to assess credibility.
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paper_title: Image Based Localization in Urban Environments

paper_content:

In this paper we present a prototype system for image based localization in urban environments. Given a database of views of city street scenes tagged by GPS locations, the system computes the GPS location of a novel query view. We first use a wide-baseline matching technique based on SIFT features to select the closest views in the database. Often due to a large change of viewpoint and presence of repetitive structures, a large percentage of matches (> 50%) are not correct correspondences. The subsequent motion estimation between the query view and the reference view, is then handled by a novel and efficient robust estimation technique capable of dealing with large percentage of outliers. This stage is also accompanied by a model selection step among the fundamental matrix and the homography. Once the motion between the closest reference views is estimated, the location of the query view is then obtained by triangulation of translation directions. Approximate solutions for cases when triangulation cannot be obtained reliably are also described. The presented system is tested on the dataset used in ICCV 2005 Computer Vision Contest and is shown to have higher accuracy than previous reported results.
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paper_title: Scale Invariant Feature Transform

paper_content:

Scale Invariant Feature Transform (SIFT) is an image descriptor for image-based matching developed by David Lowe (1999,2004). This descriptor as well as related image descriptors are used for a large number of purposes in computer vision related to point matching between different views of a 3-D scene and view-based object recognition. The SIFT descriptor is invariant to translations, rotations and scaling transformations in the image domain and robust to moderate perspective transformations and illumination variations. Experimentally, the SIFT descriptor has been proven to be very useful in practice for robust image matching and object recognition under real-world conditions.In its original formulation, the SIFT descriptor comprised a method for detecting interest points from a grey-level image at which statistics of local gradient directions of image intensities were accumulated to give a summarizing description of the local image structures in a local neighbourhood around each interest point, with the intention that this descriptor should be used for matching corresponding interest points between different images. Later, the SIFT descriptor has also been applied at dense grids (dense SIFT) which have been shown to lead to better performance for tasks such as object categorization and texture classification. The SIFT descriptor has also been extended from grey-level to colour images and from 2-D spatial images to 2+1-D spatio-temporal video.
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paper_title: Information credibility on twitter

paper_content:

We analyze the information credibility of news propagated through Twitter, a popular microblogging service. Previous research has shown that most of the messages posted on Twitter are truthful, but the service is also used to spread misinformation and false rumors, often unintentionally. On this paper we focus on automatic methods for assessing the credibility of a given set of tweets. Specifically, we analyze microblog postings related to "trending" topics, and classify them as credible or not credible, based on features extracted from them. We use features from users' posting and re-posting ("re-tweeting") behavior, from the text of the posts, and from citations to external sources. We evaluate our methods using a significant number of human assessments about the credibility of items on a recent sample of Twitter postings. Our results shows that there are measurable differences in the way messages propagate, that can be used to classify them automatically as credible or not credible, with precision and recall in the range of 70% to 80%.
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paper_title: Credibility ranking of tweets during high impact events

paper_content:

Twitter has evolved from being a conversation or opinion sharing medium among friends into a platform to share and disseminate information about current events. Events in the real world create a corresponding spur of posts (tweets) on Twitter. Not all content posted on Twitter is trustworthy or useful in providing information about the event. In this paper, we analyzed the credibility of information in tweets corresponding to fourteen high impact news events of 2011 around the globe. From the data we analyzed, on average 30% of total tweets posted about an event contained situational information about the event while 14% was spam. Only 17% of the total tweets posted about the event contained situational awareness information that was credible. Using regression analysis, we identified the important content and sourced based features, which can predict the credibility of information in a tweet. Prominent content based features were number of unique characters, swear words, pronouns, and emoticons in a tweet, and user based features like the number of followers and length of username. We adopted a supervised machine learning and relevance feedback approach using the above features, to rank tweets according to their credibility score. The performance of our ranking algorithm significantly enhanced when we applied re-ranking strategy. Results show that extraction of credible information from Twitter can be automated with high confidence.
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paper_title: Tweeting is believing?: understanding microblog credibility perceptions

paper_content:

Twitter is now used to distribute substantive content such as breaking news, increasing the importance of assessing the credibility of tweets. As users increasingly access tweets through search, they have less information on which to base credibility judgments as compared to consuming content from direct social network connections. We present survey results regarding users' perceptions of tweet credibility. We find a disparity between features users consider relevant to credibility assessment and those currently revealed by search engines. We then conducted two experiments in which we systematically manipulated several features of tweets to assess their impact on credibility ratings. We show that users are poor judges of truthfulness based on content alone, and instead are influenced by heuristics such as user name when making credibility assessments. Based on these findings, we discuss strategies tweet authors can use to enhance their credibility with readers (and strategies astute readers should be aware of!). We propose design improvements for displaying social search results so as to better convey credibility.
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paper_title: Finding Credible Information Sources in Social Networks Based on Content and Social Structure

paper_content:

A task of primary importance for social network users is to decide whose updates to subscribe to in order to maximize the relevance, credibility, and quality of the information received. To address this problem, we conducted an experiment designed to measure the extent to which different factors in online social networks affect both explicit and implicit judgments of credibility. The results of the study indicate that both the topical content of information sources and social network structure affect source credibility. Based on these results, we designed a novel method of automatically identifying and ranking social network users according to their relevance and expertise for a given topic. We performed empirical studies to compare a variety of alternative ranking algorithms and a proprietary service provided by a commercial website specifically designed for the same purpose. Our findings show a great potential for automatically identifying and ranking credible users for any given topic.
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paper_title: Modeling topic specific credibility on twitter

paper_content:

This paper presents and evaluates three computational models for recommending credible topic-specific information in Twitter. The first model focuses on credibility at the user level, harnessing various dynamics of information flow in the underlying social graph to compute a rating. The second model applies a content-based strategy to compute a finer-grained credibility score for individual tweets. Lastly, we discuss a third model which combines facets from both models in a hybrid method, using both averaging and filtering hybrid strategies. To evaluate our novel credibility models, we perform an evaluation on 7 topic specific data sets mined from the Twitter streaming API, with specific focus on a data set of 37K users who tweeted about the topic "Libya". Results show that the social model outperfoms hybrid and content-based prediction models in terms of predictive accuracy over a set of manually collected credibility ratings on the "Libya" dataset.
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paper_title: Twitter under crisis: can we trust what we RT?

paper_content:

In this article we explore the behavior of Twitter users under an emergency situation. In particular, we analyze the activity related to the 2010 earthquake in Chile and characterize Twitter in the hours and days following this disaster. Furthermore, we perform a preliminary study of certain social phenomenons, such as the dissemination of false rumors and confirmed news. We analyze how this information propagated through the Twitter network, with the purpose of assessing the reliability of Twitter as an information source under extreme circumstances. Our analysis shows that the propagation of tweets that correspond to rumors differs from tweets that spread news because rumors tend to be questioned more than news by the Twitter community. This result shows that it is posible to detect rumors by using aggregate analysis on tweets.
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paper_title: Finding high-quality content in social media

paper_content:

The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content sites based on user contributions --social media sites -- becomes increasingly important. Social media in general exhibit a rich variety of information sources: in addition to the content itself, there is a wide array of non-content information available, such as links between items and explicit quality ratings from members of the community. In this paper we investigate methods for exploiting such community feedback to automatically identify high quality content. As a test case, we focus on Yahoo! Answers, a large community question/answering portal that is particularly rich in the amount and types of content and social interactions available in it. We introduce a general classification framework for combining the evidence from different sources of information, that can be tuned automatically for a given social media type and quality definition. In particular, for the community question/answering domain, we show that our system is able to separate high-quality items from the rest with an accuracy close to that of humans
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paper_title: Selecting Quality Twitter Content for Events

paper_content:

Social media sites such as Twitter contain large amounts of user contributed messages for a wide variety of real-world events. While some of these "event messages" might contain interesting and useful information (e.g., event time, location, participants, opinions), others might provide little value (e.g., using heavy slang, incomprehensible language) to people interested in learning about an event. Techniques for effective selection of quality event content may therefore help improve applications such as event browsing and search.In this paper, we explore approaches for finding representative messages among a set of Twitter messages that correspond to the same event, with the goal of identifying high quality, relevant messages that provide useful event information. We evaluate our approaches using a large-scale dataset of Twitter messages, and show that we can automatically select event messages that are both relevant and useful.
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paper_title: A linguistic decision making approach to assess the quality of volunteer geographic information for citizen science

paper_content:

The paper analyses the challenges and problems posed by the use of Volunteered Geographic Information (VGI) in citizen science and a proposal is formulated for assessing VGI quality based on a linguistic decision making approach so as to allow its feasible use for scientific purposes. VGI quality is represented by indicators at distinct levels of granularity which take into account the distinct components of the VGI items. The quality indicators represent both the extrinsic quality, depending on the characteristics and reputation of the sources of information; the intrinsic quality, depending on the distinct accuracy and precision of information; and, last but not least, the pragmatic quality, depending on the user needs and intended purposes. In order to assess the pragmatic quality of VGI items, a linguistic decision making approach is defined that allows users to rank and finally filter the VGI items based on the satisfaction of distinct criteria expressed by means of both linguistic terms, defining soft constraints on the distinct quality indicators, and linguistic aggregators, defining fuzzy operators which combine the satisfaction degrees of the soft constraints at distinct hierarchical levels to yield the final satisfaction of the VGI items. Finally, an example of quality assessment in a glaciological citizen science project is discussed.
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paper_title: Automatic quality assessment of content created collaboratively by web communities: a case study of wikipedia

paper_content:

The old dream of a universal repository containing all the human knowledge and culture is becoming possible through the Internet and the Web. Moreover, this is happening with the direct collaborative, participation of people. Wikipedia is a great example. It is an enormous repository of information with free access and edition, created by the community in a collaborative manner. However, this large amount of information, made available democratically and virtually without any control, raises questions about its relative quality. In this work we explore a significant number of quality indicators, some of them proposed by us and used here for the first time, and study their capability to assess the quality of Wikipedia articles. Furthermore, we explore machine learning techniques to combine these quality indicators into one single assessment judgment. Through experiments, we show that the most important quality indicators are the easiest ones to extract, namely, textual features related to length, structure and style. We were also able to determine which indicators did not contribute significantly to the quality assessment. These were, coincidentally, the most complex features, such as those based on link analysis. Finally, we compare our combination method with state-of-the-art solution and show significant improvements in terms of effective quality prediction.
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paper_title: Are you contributing trustworthy data?: the case for a reputation system in participatory sensing

paper_content:

Participatory sensing is a revolutionary new paradigm in which volunteers collect and share information from their local environment using mobile phones. The inherent openness of this platform makes it easy to contribute corrupted data. This paper proposes a novel reputation system that employs the Gompertz function for computing device reputation score as a reflection of the trustworthiness of the contributed data. We implement this system in the context of a participatory noise monitoring application and conduct extensive real-world experiments using Apple iPhones. Experimental results demonstrate that our scheme achieves three-fold improvement in comparison with the state-of-the-art Beta reputation scheme.
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paper_title: A conceptual workflow for automatically assessing the quality of volunteered geographic information for crisis management

paper_content:

In this paper, we aim to present a complete conceptual work flow for the assessment of user generated geographic content, or volunteered geographic information (VGI), for the use in a crisis management context. We provide an example on forest fires, but the modular workflow is adaptable to other types of crisis events.
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paper_title: A Quality Study of the OpenStreetMap Dataset for Tehran

paper_content:

There has been enormous progress in geospatial data acquisition in the last decade. Centralized data collection, mainly by land surveying offices and local government agencies, has changed dramatically to voluntary data provision by citizens. Among a broad list of initiatives dealing with user generated geospatial information, OpenStreetMap (OSM) is one of the most famous crowd-sourced products. It is believed that the quality of collected information remains a valid concern. Therefore, qualitative assessment of OSM data as the most significant instance of volunteered geospatial information (VGI) is a considerable issue in the geospatial information community. One aspect of VGI quality assessment pertains to its comparison with institutionally referenced geospatial databases. This paper proposes a new quality metric for assessment of VGI accuracy and as well as for quality analysis of OSM dataset by evaluating its consistency with that of a reference map produced by Municipality of Tehran, Iran. A gridded map is employed and heuristic metrics such as Minimum Bounding Geometry area and directional distribution (Standard Deviational Ellipse), evaluated for both VGI and referenced data, are separately compared in each grid. Finally, in order to have a specific output as an integrated quality metric for VGI, its consistency with ground-truth data is evaluated using fuzzy logic. The results of this research verify that the quality of OSM maps in the study area is fairly good, although the spatial distribution of uncertainty in VGI varies throughout the dataset.
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paper_title: Addressing Vagueness in Volunteered Geographic Information (VGI) - A Case Study

paper_content:

The stakeholders that are directly affected by the climate change might become an invaluable source of information if their perceptions are shared with the general public and the scientific community. Such Volunteered Geographic Information (VGI) about environmental phenomena have however a certain degree of vagueness, as they describe only a spatiotemporal and thematic snapshot of the entire phenomenon. To reconcile vagueness of stakeholder’s perception of environmental phenomenon with the ‘crisp objects’ vision of current VGI, we propose a hybrid strategy, combining an Open Gazetteer approach, and the concept of Degree of Truth. On this basis, we describe eVGI, an innovative web application based on a service-oriented architecture. We implemented eVGI as a prototype, addressing a real-world case study implying stakeholders from forestry, fishing and reindeer husbandry sectors in the Barents region.
---
paper_title: Quality Assessment of the French OpenStreetMap Dataset

paper_content:

The concept of Volunteered Geographic Information (VGI) has recently emerged from the new Web 2.0 technologies. The OpenStreetMap project is currently the most significant example of a system based on VGI. It aims at producing free vector geographic databases using contributions from Internet users. Spatial data quality becomes a key consideration in this context of freely downloadable geographic databases. This article studies the quality of French OpenStreetMap data. It extends the work of Haklay to France, provides a larger set of spatial data quality element assessments (i.e. geometric, attribute, semantic and temporal accuracy, logical consistency, completeness, lineage, and usage), and uses different methods of quality control. The outcome of the study raises questions such as the heterogeneity of processes, scales of production, and the compliance to standardized and accepted specifications. In order to improve data quality, a balance has to be struck between the contributors' freedom and their respect of specifications. The development of appropriate solutions to provide this balance is an important research issue in the domain of user-generated content.
---
paper_title: Web 2.0 geotagged photos: Assessing the spatial dimension of the phenomenon

paper_content:

Among popular Web 2.0 applications are the social networking, photo-sharing websites like Flickr, Panoramio, Picasa Web, and Geograph. The phenomenon of user-generated content and the increased presence of geographic information in such applications have motivated researchers to consider them as a source of geographic information. In this paper we question whether such web applications can serve as reliable sources of spatial content. We differentiate between spatially explicit and implicit applications, in accordance to their declared aims, and evaluate if they have an impact on the spatial distribution of geotagged photos for Great Britain. We also compare the spatial distribution of the photos submitted with population data, and the patterns of contribution to these sources over a period of 18 months. Finally, at a larger scale, we examine the spatial distribution of photos and their spatial density for 15 test areas and look into issues such as data currency and user behaviour. Our findings show that only web applications that urge users to interact directly with spatial entities can serve as reliable, universal sources of spatial content.
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paper_title: Assuring the quality of volunteered geographic information

paper_content:

Abstract Volunteered geographic information (VGI) is a phenomenon of recent years, offering an alternative mechanism for the acquisition and compilation of geographic information. As such it offers substantial advantages, but suffers from a general lack of quality assurance. We discuss the issues involved in the determination of quality for geospatial data, and trace the history of research on VGI quality. We describe three approaches to quality assurance, which we term the crowd-sourcing, social, and geographic approaches respectively. We discuss the advantages and limitations of each, and the research that will be needed to operationalize the geographic approach.
---
paper_title: Assuring the quality of volunteered geographic information

paper_content:

Abstract Volunteered geographic information (VGI) is a phenomenon of recent years, offering an alternative mechanism for the acquisition and compilation of geographic information. As such it offers substantial advantages, but suffers from a general lack of quality assurance. We discuss the issues involved in the determination of quality for geospatial data, and trace the history of research on VGI quality. We describe three approaches to quality assurance, which we term the crowd-sourcing, social, and geographic approaches respectively. We discuss the advantages and limitations of each, and the research that will be needed to operationalize the geographic approach.
---

Title: A Review of Volunteered Geographic Information Quality Assessment Methods

Section 1: Introduction
Description 1: Introduce the concept of Volunteered Geographic Information (VGI), its importance, and focus on the necessity of quality assessment methods. Set the context and outline the structure of the paper.

Section 2: Measures and indicators for VGI quality
Description 2: Discuss the quality measures and indicators used to assess VGI quality, following the ISO guidelines and other intrinsic methods. 

Section 3: Quality measures for VGI
Description 3: Delve into specific quality measures for VGI, including completeness, consistency, positional accuracy, temporal accuracy, and thematic accuracy.

Section 4: Quality indicators for VGI
Description 4: Expound on qualitative quality indicators, such as purpose, usage, lineage, trustworthiness, credibility, text content quality, vagueness, local knowledge, experience, recognition, and reputation.

Section 5: Map, image, and text-based VGI: definitions and quality issues
Description 5: Define and discuss the specific types of VGI—map, image, and text-based—and their associated quality issues.

Section 6: The literature review methodology
Description 6: Describe the methodology used for selecting and reviewing the literature on VGI quality assessment.

Section 7: Existing methods for assessing the quality of VGI
Description 7: Review and summarize the state-of-the-art methods used to assess various quality measures and indicators of VGI.

Section 8: Discussion and future research perspectives in VGI quality
Description 8: Discuss the findings of the review, current trends, limitations, and propose future research directions in the field of VGI quality assessment.

Section 9: Conclusions
Description 9: Conclude the review by summarizing the main findings and their implications for the assessment of VGI quality.