An Open Data Academic Portal: A Preliminary Study

Abstract

The use of appropriate data in education is crucial and the current deluge of Open data portals provide numerous opportunities to marry the right datasets with relevant research and teaching. However, for academics finding the right datasets can be challenging, this is the gap that the Open Data Academic Portal (ODAP) looks to bridge. A data portal that points to numerous datasets available in various Open data portals whilst also classifying and grouping them into datasets based on discipline areas and research type categories. For instance, categories such as machine learning, data analytics and further subcategories under these (such as collaborative filtering under machine learning) would be provided. The grouping and matching of datasets from various portals will be done using algorithms developed to harvest meta data from data portals and categorise and classify them using information available in these files. For instance, for systems running CKAN (the standard open source software for Open Data Portals) the algorithm will make use of the tags and group fields in the meta data for the various datasets. The expected outcomes are the provision of an application that provides a means of easy access to relevant data for use in academia for effective teaching and research using real world data. This would also facilitate results that are of benefit not just in the academic sphere but also in society as a whole.