DWA 2016 : Data Wrangling Automation

December 12, 2016

Barcelona

Call For Papers

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.

Topics of Interest

• Automation applied to data cleaning, data transformation, and data acquisition.
• Visual interfaces to accelerate the automation of data wrangling.
• Domain-specific languages for data wrangling vs general-purpose languages.
• Explanation of data wrangling rules into natural language.
• Automation in ETL (Extraction/Transformation/Load) tools.
• Learning actionable rules automating other parts of the KDD process: model evaluation and deployment.
• Abstraction mechanisms from inductive programming for metadata creation and handling.
• Data wrangling showcases.

IMPORTANT DATES

Submission deadline: August 12, 2016

Notification Due: September 13, 2016

                       

User Name : jerish
Posted 21-07-2016 on 14:52:31 AEDT

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