Fording the Data Stream MLA Midwest Chapter 2013 Photo by: Brian (makelessnoise) http://www.flickr.com/photos/makelessnoise/240072417/ Abigail Goben, MLS Rebecca Raszewski, MS, AHIP

What We Will Be Covering Background Data Process Current and Future Applications of Data I’ll be talking about how this project started with our reference desk statistics, the data process, and current and future applications of the data

Background Change in record keeping: print to electronic Loss of staff (20 hrs/week) Save ~10-15 hrs/month compiling Storage Now I will summarize why we ended up moving to collecting reference desk statistics electronically. Prior to August 2011, reference desk statistics were recorded on a paper form. Cumulative data was captured only for monthly and annual reporting. A support staff member would tally up and record the data in a spreadsheet monthly. Our support staff member, who covered almost 20 hours of reference desk hours a week, moved part time into circulation. She could only work the reference desk from 3:30-7 certain nights of the week. Our department head felt this was the time to reconsider how we staffed the reference desk. We were able to get a student worker to cover those hours so we wouldn’t spend as much time as we used to on the reference desk. Another factor in moving to collecting statistics electronically was storage. A new form was used everyday the reference desk was open. Although the paper forms were filed away, Abigail discovered that a few months of previous data had disappeared. Collecting statistics electronically would eliminate storage issues. Photo by:Don Shall/origamidon http://www.flickr.com/photos/donshall/5238620682/

Paper Form This is a screenshot of the paper version of our slides.

Google Form Front End Abigail created the document using Google Forms. This is what it looks like. We record the type of patron, the kind of question and can also add notes. There is also an off desk option.

Google Form Back End This is the Google Forms backend. It looks just like a spreadsheet. It automatically records the time of when the question was recorded. This can also be sorted like any excel file and can be saved in variety of formats. Abigail has also notes here regarding the month and year.

Data Process Identifying Digitizing Cleaning Metadata Storing (short term/long term) Sharing Analysis Rebecca’s Last Slide Now that I’ve shown you the form, Abigail will talk about the majority of how the data process was integrated into this project. Photo by: Yamamoto Tetsuya http://www.flickr.com/photos/66996259@N03/6099042898/

Data Process: Identifying Print Archive 2006-2011 Gaps Electronic Archive 2011-2013 Risks Relevancy Over-extending librarians Rethinking Information Practice

Data Process: Digitizing Student employees Slow process Project documentation http://hedgehoglibrarian.com/2012/05/09/open-access-tenure-slog-slog-slog/

Data Process: Cleaning Open Refine http://openrefine.org/

Data Process: Storing Short Term Long Term If no repository? http://indigo.uic.edu/ Short term—where are our working copies? How clustered (Excel) Long term : Format (CSV), back ups, multiple files, access Options if we didn’t have a repo http://figshare.com/ http://datadryad.org/

Data Process: Sharing Question that ties into data storage Licensing When will the full data set be available? Citation format (DataCite) http://www.datacite.org/

Data Process: Metadata What metadata? Standards? Ontologies? ReadMe File (txt) Was there metadata tied to this? Any standards we could use ReadMe File (txt) Project description Completion date Email address for original authors Photo by: Shira Golding Evergreen http://www.flickr.com/photos/boojee/3743753784/

Data Analysis Open Refine MS Excel SPSS/STATA/R –when to use or not use Data analysis may be depend on the kind of data you have. If you have messy, inconsistent data, you can use Open Refine. Another option is Excel. We did consider using SPSS, STATA, and R, which stands for the R Project for Statistical Computer but decided not to use those because we did not think our data was complex enough for these tools. These may be good for other projects. Google Spreadsheets is another tools. Electronic Resources Stats Photo by: keystricken http://www.flickr.com/photos/keystricken/441232651/

Current Applications of Data Case 1: The Case for More Student Employees This was to move from having one student employee to hiring two.

Types of Questions: 9/11-6/12 This is a duplicate of a Pivot Table Abigail created in Google Forms based on Recorded Desk Data from September 2011-June 2012. This is illustrating the 4 types of questions that we record.

Question Type by Hour: 9/11-6/12 This is another graph that Abigail created from Google Forms for questions by hour. Hours were mostly 8:30-5 or 6

Future Applications of Data Case 2: Weekend/Nights Case 3: Info Service Stats vs. Reference Desk Statistics(different form) Here is what will be done in the future. UIC students had asked for a librarian for evening and weekend reference hours. In May 2013, a visiting librarian was hired to work one night a week until 8pm. In June 2013, an evening/weekend librarian was hired to work from 4-8 Tuesdays and Thursdays, Saturdays from 2-6, and Sundays from 2-8. Future analysis will be done to see if these librarians are getting questions during the evenings and weekends. We also have a separate Google Form that we use for recording chat questions, classes, consultations, and mediated searches. This form started in January 2012. The data from this will be analyzed in the future to see how much time we are spending meeting with students, teaching, etc. to use for hiring additional librarians.

Try it Yourself Data Set Available: 9/1/2011-6/30/2012 Sample Reference Desk Form Both available in Google Forms, please contact us for access Slides 6 months-a year available Clean sample version of form

Contact Information Abigail Goben, MLS Assistant Information Services Librarian & Assistant Professor agoben@uic.edu Rebecca Raszewski, MS, AHIP raszewr1@uic.edu