Reliability extracted from the history file as an intrinsic indicator for assessing the quality of OpenStreetMap
Tóm tắt
Volunteered geographic information (VGI) is a large and up-to-date data source, which is available to the public easily. VGI enables public participation by leveraging scientific research and ease of data entry. OpenStreetMap (OSM) is one of the most popular examples of a volunteered geographic information project that has turned into a major source as the substitution of geographical data over the past years. Because OSM data quality is very variable, its various aspects have been investigated in previous studies. Assessing the reliability of volunteered geographic data has been a topic of interest to researchers during recent years. The objective of this study is to introduce an approach for computing the reliability indicators as tools for assessing OSM data quality using the history of data. To prepare the data required, the history file of the OSM dataset for the study region was extracted. Then, historical data cleaning was carried out by identifying and eliminating the outlier data. Afterward, the reliability indicator was calculated through criteria such as the number of versions, the number of user participation, temporal variations, and the number of tags editing. In the last step, to evaluate the proposed approach in calculating the reliability indicator, the level of feature reliability was compared with their spatial accuracy calculated via feature matching of the OSM and official data. The results show among 7478 reliability features of the OSM, approximately 4338 feature involves reliability of above 50%, containing 58.01% of the datasets, and among 5659 matching features of the OSM dataset, 4429 features have a similarity percentage of above 70%, containing 78.26% of the datasets. Increasing the number of versions, the number of users, and the temporal variation range of a route increased the reliability. Contrastingly, tag editing reduces reliability. Moreover, according to the results, a correlation coefficient of 0.695 between the reliability and spatial accuracy indicates a direct relationship of reliability in the quality of the OSM dataset.
Tài liệu tham khảo
Chehreghan A, Ali Abbaspour R (2018) A geometric-based approach for road matching on multiscale dataset using a genetic algorithm. Cartogr Geogr Inf Sci 45(3):255–269
Antoniou V, Touya G, Raimond A-M (2016) Quality analysis of the Parisian OSM toponyms evolution.
Aragó P, Díaz L, Huerta J A quality approach to volunteer geographic information. In: 7th International Symposium on Spatial Data Quality (ISSDQ 2011). Raising awareness of Spatial Data Quality, 2011. pp 12–14
Arsanjani JJ, Vaz E (2015) An assessment of a collaborative mapping approach for exploring land use patterns for several European metropolises. Int J Appl Earth Obs Geoinf 35:329–337
Bégin D, Devillers R, Roche S (2013) Assessing volunteered geographic information (VGI) quality based on contributors’ mapping behaviours Int Arch Photogramm Remote Sens Spat Inf Sci 2013:149–154
Bishr M, Janowicz K Can we trust information?-the case of volunteered geographic information. In: Towards Digital Earth Search Discover and Share Geospatial Data Workshop at Future Internet Symposium, volume, 2010.
Bishr M, Mantelas L (2008) A trust and reputation model for filtering and classifying knowledge about urban growth. GeoJournal 72:229–237
Brovelli MA, Minghini M, Molinari M, Mooney P (2017) Towards an automated comparison of OpenStreetMap with authoritative road datasets. Trans GIS 21:191–206
Chehreghan A, Ali Abbaspour R (2017a) An assessment of spatial similarity degree between polylines on multi-scale, multi-source maps Geocarto International 32:471–487
Chehreghan AR, Ali Abbaspour R (2017b) Improvement of geometric-based roads matching on multi-scale data structures. Journal of Geomatics Science and Technology 6:89–102
Coleman D, Georgiadou Y, Labonte J (2009) Volunteered geographic information: the nature and motivation of produsers. Int J Spatial Data Infrastruct Res 4:332–358
D’Antonio F, Fogliaroni P, Kauppinen T (2014) VGI edit history reveals data trustworthiness and user reputation
De Leeuw J, Said M, Ortegah L, Nagda S, Georgiadou Y, DeBlois M (2011) An assessment of the accuracy of volunteered road map production in Western Kenya. Remote Sens 3:247–256
De Longueville B, Ostländer N, Keskitalo C (2010) Addressing vagueness in Volunteered Geographic Information (VGI)–A case study. Int J Spatial Data Infrastruct Res 5:1725–0463
Fan H, Zipf A, Fu Q (2014) Estimation of building types on OpenStreetMap based on urban morphology analysis. In: Connecting a Digital Europe Through Location and Place. Springer, pp 19–35
Flanagin AJ, Metzger MJ (2008) The credibility of volunteered geographic information. GeoJournal 72:137–148
Foody GM, See L, Fritz S, Van der Velde M, Perger C, Schill C, Boyd DS (2013) Assessing the accuracy of volunteered geographic information arising from multiple contributors to an internet based collaborative project. Trans GIS 17:847–860
Forati AM, Ghose R (2020) Volunteered Geographic Information Users Contributions Pattern and its Impact on Information Quality
Forghani M, Delavar MR (2014) A quality study of the OpenStreetMap dataset for Tehran ISPRS. Int J Geo-Inform 3:750–763
Girres JF, Touya G (2010) Quality assessment of the French OpenStreetMap dataset. Trans GIS 14:435–459
Golbeck J (2006) Trust on the world wide web: a survey Foundations and Trends in Web. Science 1:131–197
Golbeck J, Hendler J Inferring reputation on the semantic web. In: Proceedings of the 13th International World Wide Web Conference, 2004. Citeseer,
Goodchild MF (2007) Citizens as voluntary sensors: spatial data infrastructure in the world of Web 2.0 International journal of spatial data infrastructures research 2:24–32
Guptill SC, Morrison JL (2013) Elements of spatial data quality. Elsevier
Haklay M (2010) How good is volunteered geographical information? A comparative study of OpenStreetMap and ordnance survey datasets environment and planning b: Planning and Design 37:682–703
Haklay M, Basiouka S, Antoniou V, Ather A (2010) How many volunteers does it take to map an area well? The Validity of Linus’ Law to Volunteered Geographic Information the Cartographic Journal 47:315–322
Hashemi P, Abbaspour RA (2015) Assessment of logical consistency in OpenStreetMap based on the spatial similarity concept. In: Openstreetmap in giscience. Springer, pp 19–36
Jackson SP, Mullen W, Agouris P, Crooks A, Croitoru A, Stefanidis A (2013) Assessing completeness and spatial error of features in volunteered geographic information ISPRS. Int J Geo-Inform 2:507–530
Kainz W (1995) Logical consistency Elements of spatial data quality 202:109-137
Keßler C, De Groot RTA (2013) Trust as a proxy measure for the quality of volunteered geographic information in the case of OpenStreetMap. In: Geographic information science at the heart of Europe. Springer, pp 21–37
Keßler C, Trame J, Kauppinen T Tracking editing processes in volunteered geographic information: The case of OpenStreetMap. In: Identifying objects, processes and events in spatio-temporally distributed data (IOPE), workshop at conference on spatial information theory, 2011. pp 6–8
Mooney P, Corcoran P (2012) Characteristics of heavily edited objects in OpenStreetMap. Future Internet 4:285–305
Nasiri A, Ali Abbaspour R, Chehreghan A, Jokar Arsanjani J (2018) Improving the quality of citizen contributed geodata through their historical contributions: the case of the road network in OpenStreetMap ISPRS. Int J Geo-Inform 7:253
Neis P, Zipf A (2012) Analyzing the contributor activity of a volunteered geographic information project—The case of OpenStreetMap ISPRS International Journal of Geo-Information 1:146–165
Sehra SS, Singh J, Rai HS (2017) Assessing OpenStreetMap data using intrinsic quality indicators: an extension to the QGIS processing toolbox. Future Internet 9:15
Vahidi H, Klinkenberg B, Yan W (2018) Trust as a proxy indicator for intrinsic quality of Volunteered Geographic Information in biodiversity monitoring programs. Giscience & Remote Sensing 55:502–538
Veregin H (2000) Quantifying positional error induced by line simplification. Int J Geogr Inf Sci 14:113–130
Yamashita J, Seto T, Nishimura Y, Iwasaki N (2019) VGI contributors’ awareness of geographic information quality and its effect on data quality: a case study from Japan . Int J Cartogr 5:214–224
Zhang H, Malczewski J (2019) Quality evaluation of volunteered geographic information: The case of OpenStreetMap. In: Crowdsourcing: Concepts, Methodologies, Tools, and Applications. IGI Global, pp 1173–1201
Zhao Y, Zhou X, Li G, Xing H (2016) A spatio-temporal VGI model considering trust-related information ISPRS. Int J Geo-Inform 5:10
Zheng S, Zheng J (2014) Assessing the completeness and positional accuracy of OpenStreetMap in China. In: Thematic cartography for the society. Springer, pp 171–189