Extracting value out of the vast amounts of open data available today is difficult and expensive. One of the main reasons is that open data sets do not connect easily with each other nor with the data sets owned by the user. To connect these datasets, one needs to understand the various data identification schemas used by the government agencies and industry bodies that publish open data and figure out how to interconnect entities and locations of interest to the information available in open datasets. In addition, given the ever-changing nature of the world, maintaining the interconnects between data sources is a continuous effort of change monitoring and adjustments. These problems make the construction and keeping of fit-for-purpose data to support data science needs expensive and time-consuming effectively.