Conceptual Modeling and Testing for Open Data Platform Services

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In recent years, most public organizations publish their raw data on the Internet under "open data platforms",which aim to provide available, accessible, and reusable data for the public, free of charge. The open datapotentially can provide great return from public investment. However, to make such platforms beneficial, thedata should be readily consumable. Unfortunately, the current platforms mostly contain a vast variety ofdatasets, but with little help to get higher-level insights (e.g., where in downtown Calgary would be a goodlocation to open up a coffee shop). To fill this gap companies such as LocalIntel Inc. provide analytics serviceson top of open data platforms. To help LocalIntel expand their products range to work with municipalities ofall sizes with diffident formats of data and use cases, this project proposes a) a preprocessing phase thatconverts any municipality data to a standard format and b) to automatically validate the new datasets and verifythe software with respect to the changes the input data.