It is well known that a great proportion of the time devoted to data mining and, especially, data science projects is devoted to data acquisition, integration, transformation, cleansing and other highly tedious tasks. These tasks are tedious basically because they are repetitive and, hence, automatable. As a consequence, progress in the automation of this process can lead to a dramatic reduction of the cost and duration of data-oriented projects. Recently, inductive programming in general (and the learning of declarative rules and programs from a few user interaction examples in particular) has shown a large potential for this automation. The release of FlashFill as a plug-in inductive programming tool for Microsoft Excel and ConvertFrom-String as a Powershell command on Windows 10 are impressive demonstrations that inductive programming research has matured in such a way that commercial applications become feasible.
The aim of this workshop is to gather practitioners and researchers around the use of inductive programming techniques, programming by example and other learning techniques to automate the data wrangling process. It is well known that a great proportion of the time devoted to data mining and, especially, data science projects is devoted to data acquisition, integration, transformation, cleansing and other highly tedious tasks. These tasks are tedious basically because they are repetitive and, hence, automatable. As a consequence, progress in the automation of this process can lead to a dramatic reduction of the cost and duration of data-oriented projects.