Creating an Introduction to Data Course (or, perhaps, Data Translation for Workin g on Data Science Teams "Digital Literacy with a Maker Spirit") Proposal for THATCamp Florida 2014: http:/ /florida2014.thatcamp.org/2014/02/11/creating an introduction to data course or perhaps data translation for working on data science teams digital literacy with a maker spirit/ Proposal by: Laurie N. Taylor, firstname.lastname@example.org Proposal Overview : Many places have great introductory data science courses and resources like this course from Columbia, http://columbiadatascience.com/about the class/ a 3 course sequence at UF (each ( http://dh101.humanities.ucla.edu ). cepts, t ells me is needed. on data with folks from all fields and all levels where there are gaps that could be best supported with more on concepts. Other findings support this need: After coding and analysis, several major themes emerged from the faculty's observations of graduate students' deficiencies in data management. These themes are metadata, standardizing documentation processes, maintaining relationships among data, ethics, q uality assurance, basic database skills, and preservation. ( http://muse.jhu.edu/journals/portal_libraries_and_the_academy/v011/11.2.carlson.html ) The full article for the quote above lists core competencies and more completely explains their findings. My reading of the article indicate s a need for greater emphasis on concepts (as well as being applied to specific data needs). best model for work for such a course, with the understanding that there would be many guest lecturers and teachers, including: How is the need covered already? What existing models/examples should be used? ve without? What elements would be essential for the course? (Scale, unit operations, procedural rhetoric, provenance, metadata as "constructed, constructive, and actionable" http://alatechsource.metapress.com/content/p3022442071g7655/fulltext.html ) How should the course be organized? (How much time on project management and working in tea ms?)
How to ensure practical/applied learning as well as emphasizing concepts over mechanics http://docs. lib.purdue.edu/cgi/viewcontent.cgi?article=1012&context=lib_fspr es )? Is this a data course, informatics course, DH course? How does this relate to what Cathy ( http://www.hastac.org/blogs/cathy davidson/2013/11/17/syllabus history and future higher education ) ? How would this course look as a 1 week work shop, perhaps with days on lectures and days on applied? How would this course look as a DOCC (Distributed Online Collaborative Course, http://adanewmedia.org/2012/11/issue1 juhasz/ )?