Visualisation of quality information for geospatial and remote sensing data:providing the GIS community with the decision support tools for geospatial dataset quality evaluation (original) (raw)
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IFIP Advances in Information and Communication Technology, 2018
The evaluation of geospatial data quality and trustworthiness presents a major challenge to geospatial data users when making a dataset selection decision. Part of the problem arises from the inconsistent and patchy nature of data quality information, which makes intercomparison very difficult. Over recent years, the production and availability of geospatial data has significantly increased, facilitated by the recent explosion of Web-based catalogues, portals, standards and services, and by initiatives such as INSPIRE and GEOSS. Despite this significant growth in availability of geospatial data and the fact that geospatial datasets can, in many respects, be considered commercial products that are available for purchase online, consumer trust has to date received relatively little attention in the GIS domain. In this paper, we discuss how concepts of trust, trust models, and trust indicators (largely derived from B2C e-Commerce) apply to the GIS domain and to geospatial data selection and use. Our research aim is to support data users in more efficient and effective geospatial dataset selection on the basis of quality, trustworthiness and fitness for purpose. To achieve this, we propose a GEO label a decision support mechanism that visually summarises availability of key geospatial data informational aspects. We also present a Web service that was developed to support generation of dynamic GEO label representations for datasets by combining producer metadata (from standard catalogues or other published locations) with structured user feedback.
Geospatial data quality indicators
2012
Indicators which summarise the characteristics of spatiotemporal data coverages significantly simplify quality evaluation, decision making and justification processes by providing a number of quality cues that are easy to manage and avoiding information overflow. Criteria which are commonly prioritised in evaluating spatial data quality and assessing a dataset's fitness for use include lineage, completeness, logical consistency, positional accuracy, temporal and attribute accuracy. However, user requirements may go far beyond these broadlyaccepted spatial quality metrics, to incorporate specific and complex factors which are less easily measured. This paper discusses the results of a study of high level user requirements in geospatial data selection and data quality evaluation. It reports on the geospatial data quality indicators which were identified as user priorities, and which can potentially be standardised to enable intercomparison of datasets against user requirements. We briefly describe the implications for tools and standards to support the communication and intercomparison of data quality, and the ways in which these can contribute to the generation of a GEO label.
Spatial data quality: From metadata to quality indicators and contextual end-user manual
The context within which geospatial data are used has changed significantly during the past ten years. Users have now easier access to geospatial data but typically have less knowledge in the geographical information domain, so have limited knowledge of the risk related to the use of geospatial data. This sometimes leads to faulty decision-making that may have significant consequences. In order to reduce these risks, geospatial data producers provide metadata to help users to assess the fitness for use of the data they are using within the context of their application. However, experience shows that these metadata have several limitations and do not reach their information goal for this new group of non-expert users. In addition, geospatial data are becoming a mass product that has to follow legal requirements related to this class of products. Metadata, as currently defined, do not reach these obligations, especially concerning the requirements for easily understood information abo...
Visualizing the Quality of Spatial Information
2000
Technology currently allows us to process and display large volumes of information very quickly. Effective use of this information for analysis and decision making presupposes that the information is correct or reasonably reliable. Information on the quality of data is essential for effective use of GIS data: it affects the fitness of use of data for a particular application, the credibility of data representation and interpretation, and the evaluation of decision alternatives. The credibility of spatial decision support using GIS may indeed depend on the incorporation of quality information within the database and the display. As Goodchild (1990) states the best insurance will be to sensitize the GIS user community to accuracy issues and to develop tools which allow spatial data handling systems to be sensitive to error propagation. Visualization should be explored as a method for capturing, interpreting and communicating quality information to users of GIS. Clearly, the quality of information varies spatially, and visual tools for display of data quality will improve and facilitate use of GIS. At present, those tools are either unavailable (in existing GIS packages) or not-well developed (error models and the process of visualization are only recently beginning to be addressed directly as research topics).
User-focused metadata for spatial data, geographical information and data quality assessments
2007
This paper suggest a number of ways that metadata for spatial data could be expanded and activated to make it more user relevant. We review current metadata standards and specifications and show that they are grounded in data production. They do not provide information to help users assess the relative uncertainties associated with using data for their application. As a result of the recent EU REVIGIS project and a metadata workshop at the National Institute for Environmental eScience, we suggest ways in which metadata could be re-focussed towards the operational use of data. These include: -Socio-political context of data creation, actors and their influence; -Critiques of the data such as academic papers; -Data producers opinions of class separability; -Expert opinions of relations to other datasets; -Experiential metadata; -Free text descriptions from producers; -Tools for mining free text metadata. The objective of activating and expanding metadata in this way two-fold. First, to close the gap between users and producers that are emerging as a result of spatial data infrastructure initiatives like the INSPIRE which eliminate the need for dialogue between the user and data producer. Second, to provide metadata and tools for users so that they are able to assess the spatial data quality relative to their intended application.
User perspective on geospatial data quality. Case study of the Polish Topographic Database
The 9th International Conference "Environmental Engineering 2014", 2014
The aim of the paper is to analyze the quality of geospatial data from the user perspective, which is application oriented and differs from that of the data provider due to the performance of specific tasks. Generally the overall description of data quality, reported in metadata, comprises characteristics of the data set parameters such as completeness, accuracy, and consistency of data. However, this information is very important it shows data conformance with its specification but for most of the users is not sufficient. The authors present innovative method for assessment data quality on the level of object classes focusing on spatial location of missing objects and their attributes as well as the information whether some attributes assume null reason values. The results are obtained automatically, on the basis of elaborated algorithm and reported in the form of choropleth map which should be displayed as one of the layer in a geoportal. The method was tested on land cover dataset, stored in the Database of Topographic Objects for Olsztyn.
Multidimensional Management of Geospatial Data Quality Information for its Dynamic Use Within GIS
Photogrammetric Engineering & Remote Sensing, 2005
Metadata should help users to assess the quality (fitness for use) of geospatial data, thus reducing the risk of data misuse. However, metadata presents limitations and remain largely unused. There still exists a need to provide information to users about data quality in a more meaningful way. This research aims to dynamically communicate quality information to the users in a rapid and intuitive way in order to reduce user meta-uncertainty related to geospatial data quality, and then reduce the risks of data misuses. Such a solution requires a data model able to support heterogeneous data quality information at different levels of analysis. Using a multidimensional database approach, this paper proposes a conceptual framework named the Quality Information Management Model (QIMM) relying on quality dimensions and measures. This allows a user to easily and rapidly navigate into the quality information using a Spatial On-Line Analytical Processing (SOLAP) client-tied to its GIS application. QIMM potential is illustrated by examples, and then a prototype and ways to communicate data quality to users are explored.
Automatic evaluation of geospatial data quality using web services
Revista Cartográfica, 2019
El sector geomático vive un escenario de sobrecarga de datos donde casi todos los días se generan nuevas bases de datos geoespaciales (BDG). Sin embargo, hay poca o ninguna información sobre la calidad de estas BDG. En este contexto proponemos una solución para la evaluación automática de la calidad de los datos geoespaciales utilizando servicios web. Este enfoque está compuesto por procedimientos de evaluación automática para el control de calidad de la consistencia topológica, comple- ción y exactitud posicional según se especifican en el estándar brasileño. Algunos procedimientos de control requieren datos externos para fines de comparación. Por ello, en este trabajo, proporcionamos un conjunto de datos sintéticos generados según un diseño de experimentos con el objetivo de seleccionar los métodos más adecuados para encontrar correspondencias entre las BDG. La solución desarrollada tiene un capa de interoperabilidad que vincula usuarios y procedimientos automáticos utilizando la ...