SMU Libraries will host Drop-in with Data on Tuesday and Thursday. Drop in and see us and bring your questions about using data and datasets. We’ll have experts in GIS, data visualizations and Tableau, business, humanities, and social sciences.
November 14 (registration recommended), 1 p.m. in Fondren Library
November 16 (registration required), 12 p.m. online
Before you drop in, check out these tips to make navigating data a breeze.
1. Our online guides will help you navigate data, databases, and datasets.
“How Do I…?” guides cover several topics related to conducting research. You can learn how to search for data and get tips on evaluating it. Browse our database list of data by subject or learn more about text data mining.
2. You may find what you need in an unexpected place.
Sometimes, you might not find the dataset you’re looking for where you expect to find it. This doesn’t mean we don’t have it. Try searching databases in a related subject. For example, a movie box office sales dataset may be located with financial and industry information in a business database.
3. We have access to several text-mining databases.
SMU Libraries have databases that allow large downloads of text data. Some of these databases have built-in text analysis tools.
4. If you don’t see an option for mass download, you shouldn’t “scrape” the database without permission.
Web scraping is the automated process of extracting data from websites, typically using specialized software or scripts to gather information. This violates database licensing agreements and is often a waste of time since we may be able to get you the data more quickly (and without breaking any laws). If you don’t see an option for mass downloading in the database, contact your librarian to find out if there is an Application Programming Interface (API) or other download option available through the database vendor.
This post was written by Tamia Jackson in collaboration with Rafia Mirza. Tamia is a reference and instruction intern who answers your questions on Ask Us. Rafia is the digital scholarship librarian, and our expert on collaborative projects, text data mining, and more.