Literature review
在地理信息系统（GIS）领域，它描述了整体数据是否适合特定目的或用途来表示没有错误和其他问题的资料。 “（海伍德等人，2011，地理信息系统，310-311的介绍）。数据质量是生产的核心，这是相关的数据的可靠性和系统可靠性的重要问题（朗利等人，2005）。这部分文献回顾将指示数据质量的轮廓，以及为什么数据质量事关用户。
Assessing map data quality (why the data quality important)
In Geographic Information System (GIS) area, "data quality is used to give an indication of how good data are. It describes the overall fitness or suitability of data for a specific purpose or is use to indicate data free from errors and other problems." (Heywood et al., 2011, An Introduction of Geographic Information system, pp 310-311). Data quality is the core of production and it is related to the data reliability and system reliability important issues (Longley et al., 2005). This section of the literature review will indicate an outline of the data quality in GIS and why the data quality does matter to users.
As data quality in the construction of digital earth plays an increasingly vital role, GIS data quality directly not only influences the applications in the reliability of the results of the analysis and application of the actual implementation, but also affect the healthy development of the GIS industry. However, if the quality and accuracy of data can not be taken seriously enough by the re-calculation of these data and combined data generated is not the final desired result, it may lead to the final decision errors (Heywood et al., 2011). In other words, poor quality data might cause some terrible consequences. For instance, if a patient has a heart attack at home, but the ambulance was sent to a different location. Or a fish farm is inadvertently built near the wastewater discharge facilities.
Furthermore in recent years GIS data accuracy and quality control get more and more attention. According to Heyhood et al. (2011) that GIS data quality issues involving a wide range, it is related to spatial location, symbol of the project characteristics and time information recorded. The data is the quality of spatial data in the expression the three basic elements can achieve the accuracy, consistency, integrity. Because of the complexity of the real world, fuzziness, and the limitations of human understanding and expression ability, spatial data is not possible for us to completely true value in the expression, only to a certain extent, close to the true value. Especially for the VGI geographic productions, although the recent rapid evolution of the network and GIS to promote the development of volunteering like OSM map, its quality and reliability are also more concerned by the user (Flanagin and Metzer, 2008), because the data are updated by volunteers freely, some of them may not be trained. This will be explained in following section. Therefore, the quality assessment of the OSM data set would be necessary. Such as government departments actively formulated laws and regulations to ensure data quality. The data as a product uses the method of product quality to manage data quality; the series of geographical data quality standards was taken shape like USA-SDTS (Chrisman 1987, Moellering 1988) and ISO for geographic information 19113 (ISO 2003a). Moreover, Coote and Rackham(2008) represent the quality can be evaluated two elements in terms of subjective and quantitative elements. The subjective element means the specific data will need to provide a specific purpose. They listed three headings used to assess:
- Purpose: the rational for creating the dataset
- Usage: the application to which the dataset has been put
- Lineage: the history of the dataset
The quality evaluation of quantitative elements includes the measurement and subject result. They described the following aspects like positional accuracy, temporal accuracy, thematic accuracy, Non-quantitative attribute correctness, and Completeness and Logical consistency. Also, van Oort (2006) defined the classification more carefully into the following eight aspects:
- Lineage: this is the brief history of the dataset. Desc
