A framework for measuring the fitness for purpose of OpenStreetMap data based on intrinsic quality indicators
The OpenStreetMap data in selected regions is normally evaluated by comparing with commercial or authority data, before it will be used for in a project in different application domains. However, there are three problems with this kind of so-called extrinsic quality assessment. Firstly, the results cannot directly answer the question about whether the OSM data is good enough for a certain purpose, because the extrinsic quality indicators are designed as standard to indicate an overall level of the quality. Secondly, the results may not be able to reflect the true quality of OSM data, because the existing tools (as those described by ISO) are not inclusive enough or appropriate to eloquently evaluate OSM data, because the nature of OSM, as a project of VGI, is fundamentally different to what geospatial experts have dealt with so far. Thirdly, the reference data is often not available due to contradictory licensing restrictions or high procurement costs.
In this project, we attempt to develop a framework that provides in a systematic way the methods and measures to evaluate the fitness for purpose of OSM data. A main objective is that this shall also be usable when there is no (authority) reference data for comparison is available, in order to make it applicable in a wide range of situations and extending the traditional approaches on spatial data quality evaluations based on comparison with other data sets. For this one sub-objective is to define systematically a taxonomy for different types of usage of OSM data in different application domains that includes the relevant indications and advises of: (i) what kind of information is required? (ii) what is the data quality requirements? (iii) which quality indicators can be used to evaluate the OSM data to be used? (iv) how can the quality indicators be calculated without using reference data? and (v) how creditable is the evaluation of the fitness for purpose? The framework is going to serve as procedure guidelines when using OSM data in projects in application domains such as urban planning, routing & navigation, disaster management, marketing, geocoding, map application, etc.
To achieve this, an intensive study in the history data of OSM (OSM-Full-History-Dump) will be carried out based on the existing experiences available in practices and literatures, in order to analyse the nature characteristics of OSM, derive the factors which can influence OSM data quality, and parse them hierarchically and quantitatively. On this base, existing intrinsic quality indicators will be adjusted and improved, and new intrinsic indicators will be introduced.
The main contribution of this project is the so far most exhaustive systematic identification and connection among intrinsic and extrinsic quality indicators and measurements to a large number of application domains. The framework developed in this project shall have wide applicability or be generalizable for using any kind of VGI data in the defined application domains. Moreover, the method of developing the framework can be deployed for further application domains in case similar VGI data is used.
Geographic information crowdsourcing is an increasingly popular approach to derive geographic data about human settlements from remotely sensed imagery. However, crowdsourcing approaches are frequently associated with uncertainty about the quality of the information produced. Although previous studies have found acceptable quality of crowdsourced information in some application domains, there is still lack of research about [...]
Crowdsourced Geographic Information (CGI) has emerged as a potential source of geographic information for different domains. Despite advantages associated with it, such information lacks quality assurance, since it is provided by different individuals. Several authors have investigated different approaches to assess CGI quality. Some of the existing methods have been summarized in different classification schemas. [...]
VGI-Analytics 2017 Volunteered Geographic Information (VGI) and social media data have become part of our everyday lives over the past few years. Whereas in the early beginnings of crowd-sourced data the collection occurred primarily to isolated, individual platforms, contribution patterns are now beginning to be more intertwined between different platforms, both [...]
VGI-Analytics 2017 is the 4th workshop in a series of AGILE pre-conference workshops Volunteered Geographic Information (VGI) and social media data have become part of our everyday lives over the past few years. Whereas in the early beginnings of crowd-sourced data the collection occurred primarily to isolated, individual platforms, contribution patterns are now beginning to be more [...]
On Tuesday 17th January, the CAP4Access/MyAccessible.EU came to a close after three years with the successful completion of the final European Commission review meeting in Brussels. Reviewers were highly pleased with the outcomes of the project, both on the technical and societal fronts. At GIScience in Heidelberg, through the EC FP7 project we have extended the [...]
cfp: VGI-Analytics 2017 Volunteered Geographic Information (VGI): Integration, ANALYsis, applICationS Tuesday, 9th May 2017, Wageningen University, The Netherlands at AGILE 2017 VGI-Analytics 2017 is the [...]
Last week on Monday 12th, we organized a workshop for the CAP4Access project that aimed to discuss ideas and methods on how the developed tools and services within the project would be exploited especially after the project has came to an end. Dr. Emmanuel Sofianopoulos was the expert for the workshop appointed by the European Commission. The workshop [...]
Recently some of our work on intrinsic VGI quality analysis has been published. In this work we propose a framework to assess the quality of OSM building footprints data without using any reference data. More specifically, the OSM history data will be examined regarding the development of attributes, geometries and positions of building footprints. In [...]
Our recent team member Dr. Yingwei YAN successfully defended his PhD thesis this very week. We do congratulate him most cordially! The thesis was conducted at the National University of Singapore at the Department of Geography before he joined the GIScience Heidelberg team. Yingwei worked for example on using fuzzy set theory to assure the [...]
This Friday, Nov 4th, Alexander Zipf from GIScience Heidelberg will give a presentation at the WhereCamp 2016 conference in Berlin about some current activities and developments in the currently being established Heidelberg Institute for Geoinformatics (HeiGIT), core funded by the Klaus Tschira Foundation. This includes latest developments in Routing and Navigation solutions, such as OpenRouteService [...]