Towns conquer: a gamified application to collect geographical names (vernacular names/toponyms)

The traditional model for geospatial crowd sourcing asks the public to use their free time collecting geospatial data for no obvious reward. This model has shown to work very well on projects such as Open Street Map, but comes with some clear disadvantages such as reliance on small communities of ‘Neo-geographers’ and variability in quality and content of collected data. This project aims at tackling these problems by providing alternative motivation specifically a smartphone based computer game service. Geographical names (vernacular names/ toponyms) have been identified as potential targets as they are difficult to collect on a large scale and easy to collect locally, thus ideal for crowd sourcing. The data set will be a toponyms database provided by the Spanish National Geographic Institute (IGN Spain). A location based game is targeted as it is easy to guide data collection with in-game rewards (prizes, points, badges etc.). Android is chosen for its accessible API and wide use

Geoinformatics in Citizen Science

The book features contributions that report original research in the theoretical, technological, and social aspects of geoinformation methods, as applied to supporting citizen science. Specifically, the book focuses on the technological aspects of the field and their application toward the recruitment of volunteers and the collection, management, and analysis of geotagged information to support volunteer involvement in scientific projects. Internationally renowned research groups share research in three areas: First, the key methods of geoinformatics within citizen science initiatives to support scientists in discovering new knowledge in specific application domains or in performing relevant activities, such as reliable geodata filtering, management, analysis, synthesis, sharing, and visualization; second, the critical aspects of citizen science initiatives that call for emerging or novel approaches of geoinformatics to acquire and handle geoinformation; and third, novel geoinformatics research that could serve in support of citizen science

Citizen Science and Geospatial Capacity Building

This book is a collection of the articles published the Special Issue of ISPRS International Journal of Geo-Information on “Citizen Science and Geospatial Capacity Building”. The articles cover a wide range of topics regarding the applications of citizen science from a geospatial technology perspective. Several applications show the importance of Citizen Science (CitSci) and volunteered geographic information (VGI) in various stages of geodata collection, processing, analysis and visualization; and for demonstrating the capabilities, which are covered in the book. Particular emphasis is given to various problems encountered in the CitSci and VGI projects with a geospatial aspect, such as platform, tool and interface design, ontology development, spatial analysis and data quality assessment. The book also points out the needs and future research directions in these subjects, such as; (a) data quality issues especially in the light of big data; (b) ontology studies for geospatial data suited for diverse user backgrounds, data integration, and sharing; (c) development of machine learning and artificial intelligence based online tools for pattern recognition and object identification using existing repositories of CitSci and VGI projects; and (d) open science and open data practices for increasing the efficiency, decreasing the redundancy, and acknowledgement of all stakeholders

Citizen science characterization of meanings of toponyms of Kenya: a shared heritage

This paper examines the toponymic heritage used in Kenya’s Authoritative Geographic Information (AGI) toponyms database of 26,600 gazetteer records through documentation and characterization of meanings of place names in topographic mapping. A comparison was carried out between AGI and GeoNames and between AGI and OpenStreetMap (OSM) volunteered records. A total of 15,000 toponymic matchings were found. Out of these, 1567 toponyms were then extracted for further scrutiny using AGI data in the historical records and from respondents on toponyms’ meanings. Experts in toponymy assisted in verifying these data. From the questionnaire responses, 235 names occurred in more than one place while AGI data had 284. The elements used to characterize the toponyms included historical perceptions of heritage evident in toponyms in their localities, ethnographic, toponymical and morphology studies on Kenya's dialects. There was no significant relationship established between the same place name usages among dialects as indicated by a positive weak correlation r (438), = 0.166, p < 0.001 based on the effect of using the related places and the distance between related places. The weak correlation implies that the one name one place principle does not apply due to diverse language boundaries, strong bonds associated with historical toponyms in the form of heritage and significant variations on how names resist changes to preserve their heritage

Describing and comparing landscapes using tags, texts, and free lists : an interdisciplinary approach

Peer reviewedPublisher PD

Identifying success factors in crowdsourced geographic information use in government

Crowdsourcing geographic information in government is focusing on projects that are engaging people who are not government officials and employees in collecting, editing and sharing information with governmental bodies. This type of projects emerged in the past decade, due to technological and societal changes - such as the increased use of smartphones, combined with growing levels of education and technical abilities to use them by citizens. They also flourished due to the need for updated data in relatively quick time when financial resources are low. They range from recording the experience of feeling an earthquake to recording the location of businesses during the summer time. 50 cases of projects in which crowdsourced geographic information was used by governmental bodies across the world are analysed. About 60% of the cases were examined in 2014 and in 2017, to allow for comparison and identification of success and failure. The analysis looked at different aspects and their relationship to success: the drivers to start a project; scope and aims; stakeholders and relationships; inputs into the project; technical and organisational aspect; and problems encountered. The main key factors of the case studies were analysed with the use of Qualitative Comparative Analysis (QCA) which is an analytical method that combines quantitative and qualitative tools in sociological research. From the analysis, we can conclude that there is no “magic bullet” or a perfect methodology for a successful crowdsourcing in government project. Unless the organisation has reached maturity in the area of crowdsourcing, identifying a champion and starting a project that will not address authoritative datasets directly is a good way to ensure early success and start the process of organisational learning on how to run such projects. Governmental support and trust is undisputed. If the choice is to use new technologies, this should be accompanied by an investment of appropriate resources within the organisation to ensure that the investment bear fruits. Alternatively, using an existing technology that was successful elsewhere and investing in training and capacity building is another path for success. We also identified the importance of intermediary Non-Governmental Organizations (NGOs) with the experience and knowledge in working with crowdsourcing within a partnership. These organizations have the knowledge and skills to implement projects at the boundary between government and the crowd, and therefore can offer the experience to ensure better implementation. Changes and improvement of public services, or a focus on environmental monitoring can be a good basis for a project. Capturing base mapping is a good point to start, too. The recommendation of the report address organisational issues, resources, and legal aspects

Alpine Glaciology: An Historical Collaboration between Volunteers and Scientists and the Challenge Presented by an Integrated Approach

European Alpine glaciology has a long tradition of studies and activities, in which researchers have often relied on the field work of some specialized volunteer operators. Despite the remarkable results of this cooperation, some problems in field data harmonization and in covering the whole range of monitored glaciers are still present. Moreover, dynamics of reduction, fragmentation and decline, which in recent decades characterize Alpine glaciers, make more urgent the need to improve spatial and temporal monitoring, still maintaining adequate quality standards. Scientific field monitoring activities on Alpine glaciers run parallel to a number of initiatives by individuals and amateur associations, keepers of alternative, experiential and para-scientific knowledge of the glacial environment. Problems of harmonization, coordination, recruitment and updating can be addressed with the help of a collaborative approach—citizen science-like—in which the scientific coordination guarantees information quality and web 2.0 tools operate as mediators between expert glaciologists and non-expert contributors. This paper gives an overview of glaciological information currently produced in the European Alpine region, representing it in an organized structure, functional to the discussion. An empowering solution is then proposed, both methodological and technological, for the integration of multisource data. Its characteristics, potentials and problems are discussed

Spatial and Temporal Sentiment Analysis of Twitter data

The public have used Twitter world wide for expressing opinions. This study focuses on spatio-temporal variation of georeferenced Tweets’ sentiment polarity, with a view to understanding how opinions evolve on Twitter over space and time and across communities of users. More specifically, the question this study tested is whether sentiment polarity on Twitter exhibits specific time-location patterns. The aim of the study is to investigate the spatial and temporal distribution of georeferenced Twitter sentiment polarity within the area of 1 km buffer around the Curtin Bentley campus boundary in Perth, Western Australia. Tweets posted in campus were assigned into six spatial zones and four time zones. A sentiment analysis was then conducted for each zone using the sentiment analyser tool in the Starlight Visual Information System software. The Feature Manipulation Engine was employed to convert non-spatial files into spatial and temporal feature class. The spatial and temporal distribution of Twitter sentiment polarity patterns over space and time was mapped using Geographic Information Systems (GIS). Some interesting results were identified. For example, the highest percentage of positive Tweets occurred in the social science area, while science and engineering and dormitory areas had the highest percentage of negative postings. The number of negative Tweets increases in the library and science and engineering areas as the end of the semester approaches, reaching a peak around an exam period, while the percentage of negative Tweets drops at the end of the semester in the entertainment and sport and dormitory area. This study will provide some insights into understanding students and staff ’s sentiment variation on Twitter, which could be useful for university teaching and learning management