title: "Proactive Wrangling: Mixed-Initiative End-User Programming of Data Transformation Scripts"
authors: Philip J. Guo, Sean Kandel, Joseph M. Hellerstein, Jeffrey Heer
venue: ACM Symposium on User Interface Software and Technology (UIST)
year: 2011

tweet: A data wrangling UI uses proactive suggestions to help users transform data into relational formats

abstract: >
  Analysts regularly wrangle data into a form suitable for computational
  tools through a tedious process that delays more substantive analysis.
  While interactive tools can assist data transformation, analysts must
  still conceptualize the desired output state, formulate a transformation
  strategy, and specify complex transforms. We present a model to
  proactively suggest data transforms which map input data to a relational
  format expected by analysis tools. To guide search through the space of
  transforms, we propose a metric that scores tables according to type
  homogeneity, sparsity and the presence of delimiters. When compared to
  "ideal" hand-crafted transformations, our model suggests over half of
  the needed steps; in these cases the top-ranked suggestion is preferred
  77% of the time. User study results indicate that suggestions produced
  by our model can assist analysts' transformation tasks, but that users
  do not always value proactive assistance, instead preferring to maintain
  the initiative. We discuss some implications of these results for
  mixed-initiative interfaces.

bibtex: >
  @inproceedings{GuoProWrangler2011,
   author = {Guo, Philip J. and Kandel, Sean and Hellerstein, Joseph M. and Heer, Jeffrey},
   title = {Proactive Wrangling: Mixed-initiative End-user Programming of Data Transformation Scripts},
   booktitle = {Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology},
   series = {UIST '11},
   year = {2011},
   isbn = {978-1-4503-0716-1},
   location = {Santa Barbara, California, USA},
   pages = {65--74},
   numpages = {10},
   url = {http://doi.acm.org/10.1145/2047196.2047205},
   doi = {10.1145/2047196.2047205},
   acmid = {2047205},
   publisher = {ACM},
   address = {New York, NY, USA},
   keywords = {data analysis, data cleaning, data transformation, end-user programming, mixed-initiative interfaces},
  }