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Data Party Like it’s 2099! How to Throw a Data Party

Posted by on November 20th, 2015 Posted in: Data Analysis, News, Practical Evaluation


two funny birthday dogs celebrating close together as a coupleWhat’s a “data party?” We attended a program by evaluator Kylie Hutchinson entitled “It’s a Data Party!” at the AEA 2015 conference last week in Chicago.  A data party is another name for a kind of participatory data analysis, where you gather stakeholders together, show them some of the data that you have gathered and ask them to help analyze it.

Isn’t analyzing the data part of your job?  Here are some reasons you might want to include stakeholders in the data analysis stage:

  • It allows stakeholders to get to know and engage with the data
  • Stakeholders may bring context to the data that will help explain some of the results
  • When stakeholders participate in analyzing the data, they are more likely to understand it and use it
  • Watching their interactions, you can often find out who is the person with the power to act on your recommendations

So how do you throw a data party? First of all you need to know what you hope to get from the attendees, since you may only be able to hold an event like this one time. There are a number of different ways to organize the event.  You might want to consider using a World Cafe format, where everyone works together to explore a set of questions, or you could use an Open Space system in which attendees create their own agenda about what questions they want to discuss.  Recently the AEA held a very successful online unconference using MIT’s Unhangout that could be used for an online Data Party with people from multiple locations.

The kinds of questions Kylie Hutchinson suggested asking at a data party include:

  • What does this data tell you?
  • How does this align with your expectations?
  • What do you think is occurring here and why?
  • What other information do you need to make this actionable?

At the end of the party it might be time to present some findings and recommendations that you have.  Considering the work that they have done, they may be more willing to listen.  As Kylie Hutchinson said “People support what they helped create.”

 

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This project is funded by the National Library of Medicine (NLM), National Institutes of Health (NIH) under cooperative agreement number UG4LM012343 with the University of Washington.

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