OpenStreetMap (OSM) is a recent emerging area in computational science. There are several unexplored issues in the quality assessment of OSM. Firstly, researchers are using various established assessment methods by comparing OSM with authoritative dataset. However, these methods are unsuitable to assess OSM data quality in the case of the non-availability of authoritative data. In such a scenario, the intrinsic quality indicators can be used to assess the quality. Secondly, a framework for data assessment specific to different geographic information system (GIS) domains is not available. In this light, the current study presents an extension of the Quantum GIS (QGIS) processing toolbox by using existing functionalities and writing new scripts to handle spatial data. This would enable researchers to assess the completeness of spatial data using intrinsic indicators. The study also proposed a heuristic approach to test the road navigability of OSM data. The developed models are applied on Punjab (India) OSM data. The results suggest that the OSM project in Punjab (India) is progressing at a slow peace, and contributors' motivation is required to enhance the fitness of data. It is concluded that the scripts developed to provide an intuitive method to assess the OSM data based on quality indicators can be easily utilized for evaluating the fitness-of-use of the data of any region.

OpenStreetMap (OSM), based on collaborative mapping, has become a subject of great interest to the academic community, resulting in a considerable body of literature produced by many researchers. In this paper, we use Latent Semantic Analysis (LSA) to help identify the emerging research trends in OSM. An extensive corpus of 485 academic abstracts of papers published during the period 2007-2016 was used. Five core research areas and fifty research trends were identified in this study. In addition, potential future research directions have been provided to aid geospatial information scientists, technologists and researchers in undertaking future OSM research.

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The meaning and purposes of web has been changing and evolving day by day. Web 2.0 encouraged more contribution by the end users. This movement provided revolutionary methods of sharing and computing data by crowdsourcing such as OpenStreetmap, also called "the wikification of maps" by some researchers. When crowdsourcing collects huge data with help of general public with varying level of mapping experience, the focus of researcher should be on analysing the data rather than collecting it. Researchers have assessed the quality of OpenStreetMap data by comparing it with proprietary data or data of governmental map agencies. This study reviews the research work for assessment of OpenStreetMap Data and also discusses about the future directions. General Terms:Assessment, OpenStreetMap