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Data processing workflows in the social sciences

机译:社会科学中的数据处理工作流

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Much of the work of social scientists and government practitioners is consumed by accessing, collating, and analyzing data. This is particularly true in the planning and economic modeling agencies. Unfortunately, there is a severe lack of tools to facilitate this process and much of the integration is done manually by ad-hoc methods. Moreover, raw data are of limited utility. Usually these data are the input to models of more complex phenomena that produce additional data of interest. For example, in our commodity flow domain, we derive truck traffic along specific highway links within a metropolitan area, based on quite far-removed raw (source) data such as employment, imports into and exports out of the region, etc, by using a complex workflow of operations.
机译:社会科学家和政府从业人员的大部分工作都是通过访问,整理和分析数据来完成的。在计划和经济建模机构中尤其如此。不幸的是,严重缺乏促进该过程的工具,并且许多集成是通过临时方法手动完成的。此外,原始数据的用途有限。通常,这些数据是产生更多感兴趣数据的更复杂现象模型的输入。例如,在我们的商品流动领域中,我们根据使用范围很广的原始(源)数据(例如,就业,进出该区域的进出口数据等),得出了大城市区域内特定高速公路上的卡车运输量,方法是:复杂的操作流程。

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