Research directions in data wrangling: visuatizations and transformations for usable and credible data

  • Authors:

  • Sean Kandel;Jeffrey Heer;Catherine Plaisant;Jessie Kennedy;Frank van Ham;Nathalie Henry Riche;Chris Weaver;Bongshin Lee;Dominique Brodbeck;Paolo Buono

  • Affiliations:

  • Computer Science Department, Stanford University;Computer Science Department, Stanford University;Human-Computer Interaction Lab, University of Maryland;Institute for Informatics & Digital Innovation, Edinburgh Napier University, UK;Center for Advanced Studies, IBM France;Microsoft Research, Redmond;School of Computer Science, University of Oklahoma;Microsoft Research, Redmond;University of Applied Sciences Northwestern Switzerland, CH;Dipartimento di Informatica, Università degli Studi di Bari Aldo Moro, Italy

  • Venue:
  • Information Visualization - Special issue on State of the Field and New Research Directions
  • Year:
  • 2011

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Abstract

In spite of advances in technologies for working with data, analysts still spend an inordinate amount of time diagnosing data quality issues and manipulating data into a usable form. This process of 'data wrangling' often constitutes the most tedious and time-consuming aspect of analysis. Though data cleaning and integration are longstanding issues in the database community, relatively little research has explored how interactive visualization can advance the state of the art. In this article, we review the challenges and opportunities associated with addressing data quality issues. We argue that analysts might more effectively wrangle data through new interactive systems that integrate data verification, transformation, and visualization. We identify a number of outstanding research questions, including how appropriate visual encodings can facilitate apprehension of missing data, discrepant values, and uncertainty; how interactive visualizations might facilitate data transform specification; and how recorded provenance and social interaction might enable wider reuse, verification, and modification of data transformations.