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by Selene Arrazolo

Last week Information Evolution paid a visit to the University of Texas at Austin School of Information (UT iSchool). As an alumna of the UT iSchool, I was excited and proud to be back on campus with the IEI team. Our own Kevin Dodds was a guest speaker in Dr. Matt Lease‘s class, Human Computation & Crowdsourcing, which focuses on the computational aspects of how people use mathematical equations, statistics, and computer algorithms, exploring issues of human factors design. Lease is an Assistant Professor at the UT iSchool and the Director of the UT Austin Information Retrieval Crowdsourcing Lab. He specializes in crowdsourcing, natural language processing, and information retrieval. Kevin Dodds is a Senior Project Manager at IEI, and is our resident crowdsourcing guru.

Information Evolution has included crowdsourcing in its array of solutions for a few years now, and we enjoyed discussing our first-hand experience with the students. We talked about the ethics of crowdsourcing, its cost effectiveness, crowdsourcing scams, and current academic research on crowdsourcing. Kevin touched on all these issues, focusing on our experience with IEI partner Amazon Mechanical Turk, past crowdsourcing successes, and, of course, potential pitfalls. Kevin’s examples of how IEI has integrated crowdsourcing into our client solutions spurred an interesting discussion with the students.

IEI is continuing to develop its relationship with the UT iSchool, whose work is important to the future of the information science community. Look for more in next week’s post, Kevin’s own summary of his presentation and experience.

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posted by Shyamali Ghosh on February 6, 2014

by Shyamali Ghosh

“Using your proprietary data in news stories is the best possible kind of promotion for your paid data products because it shows clearly how valuable and useful your datasets are.” Words of wisdom from Infocommerce Group. Data visualizations, particularly maps displaying data, are the latest fashion. These maps are only really interesting, though, when the underlying data is unique or compelling.

The good news is that unique, useful data sets are increasingly common. Publishers from Springer to USA Today have their own APIs that let programmers incorporate data into products, giving end users access to volumes of data on an array of subjects. Other types of companies—for example Trulia real estate analytics and TomTom GPS software—are following suit, gathering data that can offer uncommon insight into their particular niches. This data is most often presented in graphic form, on a map or in another type of visualization, to allow the end user to understand it easily.

The Lead411 data we used to create the map for last year’s Data on Fire post is a good example of this growing data trend. The data is unique, including all funding events nationwide, not just public data. This type of data ecosystem enriches not just the end-users of data-driven products, but also the data providers.

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posted by Shyamali Ghosh on January 27, 2014