Data Literacy

It has been almost a year since the great IATUL conference on Data, probably one of the best conferences I have ever attended. I was thinking about DiRT today, and remembered that the brilliant Lisa Johnston had done a write-up of E-Science tools for Research in the column that she writes for SLA’s SciTech News.

One of my favorite science librarians, Michael Fosmire, has given some talks about the importance of information fluency in an e-science context. These are some of the competencies he identifies as required of e-scientists:

  • Discovery and application of data in repositories, and the ability to import and convert it to a suitable format for further processing,
  • Data management and organization: understanding the life cycle of data and creation of standard operating procedures for processing it,
  • Understanding metadata and the structure and purpose of ontologies to facilitate better sharing,
  • Data curation and re-use: recognizing that data may have purposes other than the original one for which it was intended and understanding that data curation is a complex and often costly process,
  • Cultures of practice:  recognition of the practices, values, and norms of one’s chosen field as well as relevant data standards,
  • Data preservation:  recognition of the benefits and costs,
  • Data analysis:  becomes familiar with the basic analysis tools of the discipline,
  • Data visualization:  understanding the advantages of different types of visualizations, and
  • Ethics:  develops an understanding of intellectual property, privacy, and confidentiality issues and appropriately acknowledges external sources.

A recent paper, Carlson, Jacob, Michael Fosmire, C.C. Miller, and Megan Sapp Nelson. “Determining Data Information Literacy Needs: A Study of Students and Research Faculty.” 2011 points out the need to use ethnographic research to inform decisions based around data literacy. Great stuff!

About effervescentlibrarian

UX Librarian at Rice University, Houston, Texas.
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