Conceptual Modeling and Testing for Open Data Platform Services

近年来，大多数公共组织将其原始数据发布在互联网上的开放数据平台下，旨在为公众免费提供可用的、可访问的和可重复使用的数据。开放的数据点可以从公共投资中获得巨大的回报。然而，为了使这些平台受益，数据应该随时可用。不幸的是，目前的平台大多包含种类繁多的数据集，但几乎没有帮助获得更高层次的见解(例如，在卡尔加里市中心的什么地方可以开一家咖啡店)。为了填补这一空白，本地英特尔公司等公司在开放数据平台上提供分析服务。为了帮助本地英特尔扩展其产品范围，以便与数据和用例格式不同的各种规模的市政当局合作，该项目提出了a)将任何市政当局数据转换为标准格式的预处理阶段，以及b)自动验证新的数据集并验证软件对输入数据的更改。

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.