For this project, I wanted to work with ICPSR and OpenRefine. This is my first time using research data and a program to refine it in order to answer a research question.
My process is documented below.
Research: explore the surveys of State Library Association Lobbying and Political Advocacy Practices, collected from 2017-2018.
The survey summary:
“The data contained in this study relates to lobbying and political advocacy by state library associations in the United States. Each state has a library association that works to advance the profession, the interests of its members, and library services. To fill a gap in the literature, we conducted an exploratory survey of state library associations. Specifically, we surveyed the legislative chairs of state library associations and Chief Officers of State Library Association representatives. We collected data via Qualtrics during February 2019 and received thirty-five responses representing thirty-one states, including the District of Columbia. The survey contained quantitative and qualitative questions that were organized into six areas: how advocacy is carried out, perceived differences between advocacy and political advocacy, agenda-setting, the use of lobbyists, political partisanship, and education for advocacy in library and information science.”
Step 1:
Upload dataset to OpenRefine
Step 2:
After reviewing the survey results, I noticed that my home state of Michigan was not included. Therefore, I will focus my research questions on my former state, Illinois. I am particularly interested in how Illinois approaches advocacy in library and information science.
Step 3:
Next, I changed the date layout style. This made it easier for me to see the dates of the dataset more clearly.
Step 4:
I renamed the project: Project 4 Survey of State Library Association Lobbying and Political Advocacy Practices.
Step 5:
I parsed the dataset to condense the information into columns. This gave me a view of the survey answers stacked in the column instead of read out horizontally.
Step 6:
I stared the Illinois information row and used facet by star, filing my data based on the rows marked with a star. Again, this is my first time using this program and it was important for me to try the many options.
Step 7:
I removed extra rows that did not contain any data.
Step 8:
I tried the null values options to fill areas in my dataset that were missing data.
Step 9:
Another option I tried was the trim leading white space. Again, this is trial and error to see what I can do within the program.
Step 10:
I used the text facet feature to narrow my dataset to display only data from the State of Illinois. This was a challenging process for me, as I had to rely on several YouTube tutorials and OpenRefine user manuals for guidance. In hindsight, I believe my difficulty stemmed from not asking the right question during my answer search. My goal at this stage was simply to view data specific to Illinois. To clarify my process, I’ve included two screenshots to show the steps in detail, although these might differ slightly for those focusing on a single row of data.
Step 11:
The State of Illinois data is available for view without the distraction of other state data.
Step 12:
The State of Illinois data is available for view with the survey questions included.
Step 13:
Finalizing my question, “how Illinois approaches advocacy in library and information science.”
“The Illinois Library Association’s Advocacy Committee works hand-in-hand with the Public Policy Committee to keep track of legislation that affects libraries and to then advocate with professional members and legislators for the benefit of the profession.”
Reference:
Million, A.J., and Jenny Bossaller. “Lobbying and Political Advocacy: A Review of the Literature and Exploratory Survey of State Library Associations.” The Political Librarian 4, no. 2 (2020). https://openscholarship.wustl.edu/pollib/vol4/iss2/8/.1
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