Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap
Department of Research, Innovation & Consultancy, I.K. Gujral Punjab Technical University, Kapurthala, Punjab 144603, India
Department of Computer Science & Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab 141006, India
School of Computer Sciences, Chitkara University, Patiala, Punjab 140401, India
Department of Civil Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab 141006, India
Author to whom correspondence should be addressed.
Academic Editors: Bernd Resch, Linda See and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2017, 6(7), 195; https://doi.org/10.3390/ijgi6070195
Received: 13 May 2017 / Revised: 28 June 2017 / Accepted: 28 June 2017 / Published: 1 July 2017
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.