Open Linked Statistical Data (OLSD): prospects and issues

Purpose With the progressive trends in Open Data, this paper aims to underscore the significance of Open Linked Statistical Data (OLSD) and identifies the trajectory of development of OLSD besides underlining the prospects and challenges underlying OLSD. Design/methodology/approach Being exploratory in nature, this viewpoint seeks to present a trajectory of OLSD which seeks to emphasize upon the futuristic trend in the development of OLSD. Findings Eight stages have been identified in the OLSD trajectory. The opening of more and more data results in new possibilities for combining data and gaining new insights. In the future, data will automatically be opened and streamed and could be used in using OLSD algorithms. Algorithms will mention the shortcomings and limitations of data and help to interpret the data in such a way that the user is in the driver’s seat. Research limitations/implications While the paper follows an exploratory approach, there are a couple of implications for the practitioners and academicians. For instance, government may become more accountable with the adoption of advanced OLSD algorithms. Further research on OLSD may be required in appreciating the impact of OLSD in different settings, and this would be helpful in providing novel insights to the concerned stakeholders. Originality/value While Big and Open Linked Data (BOLD) has gained prominence in academic research, the focus on OLSD has remained scanty. This paper seeks to underline the futuristic trends in OLSD.