Hi Class, welcome to the week where we begin to discuss browsing and searching databases.
This week we have one reading: Chapter 10 from our book by Cheryl Knott.
In addition to this lecture, I'll post a short demonstration video about how to apply some of what we learn here to online database search.
We all browse -- online, in stores, as we page through books, and so on -- but when it comes to searching, browsing can become a highly useful tool when applied systematically and strategically. The result is not simply a way to surf the web or scan through some search results. Rather, the result of intentional browsing -- reading or skimming a list of titles and abstracts -- can be the accumulation of highly relevant source material -- relevant to our information needs and queries.
Browsing becomes even more powerful when we take advantage of the lists that various databases provide. We've already discussed some of these lists in the previous week (like thesauri) -- today we'll look into how to use these lists to aid our browsing.
Although we make a distinction between browsing and searching, it is oftentimes helpful to begin a browsing session with a keyword search, and then use something from the search results, something like an author's name or subject term, to begin building a collection of documents that will satisfy our information needs.
We call this type of browsing pearl growing because each of the individual documents that we collect are like pieces of sand, and as we accumulate these pieces, we turn them into a pearl. This is an important metaphor -- it's not simply the individual, but useful, documents that we're interested in having -- it's the entire collection of documents we can curate and build that becomes the pearl.
In this slide, you see a screen shot of the ERIC Database. ERIC stands for Education Resources Information Center. It's an online digital library or database that's provided by the U.S. Department of Education and is an important access point for millions of bibliographic records to journal articles, books, research reports, white papers, government and other organizational reports, and more.
ERIC, like other databases, offers a thesaurus of controlled terms to help aid in information retrieval. For example, let's say I'm interested in research on academic libraries. In this screen shot, I'm looking at the page that describes the thesaurus descriptor for academic libraries, and as is usual with thesauri, it not only describes how the term is defined in the database, but it also links to related terms, including terms that are broader than academic libraries, narrower than academic libraries, or to terms that are related to academic libraries. I can click on any of these terms, and then click on the link that says to Search collection using this descriptor. And in doing so, I engage in subject browsing.
I can certainly browse using other access points, like author names. Here's a small screen shot from ERIC of authors who have written on the topic of academic libraries. Knowing that authors tend to write and research on a limited range of topics is helpful -- it allows me browse by author and subject topic.
There are only a handful of databases that are true citation databases. Two useful ones available to use are Web of Science and Google Scholar. A citation database is a database that shows you who has cited an article and provides a link to all those articles that have cited an article. Citation theory says that when two any two articles (or books, or other documents) are cited in this way, they are more likely to be about the same thing. In fact, this is how Google works---Google's original Page Rank Algorithm posited that if a web page links to another web page, then the two pages pages are likely to be about the same topic. Because of this theory, we can follow citations to find more relevant articles.
Pictured here is paper on information literacy. To the far right you can see that it's been cited 97 times. If we click on that 97, we can begin to browse those 97 articles or documents that cited this. It's highly probably that all 97 of those citing documents are about information literacy too -- and thus, browsing them would be of considerable help in if we were interested in reading more about information literacy.
Here's a screen shot of how Google Scholar employs citation browsing. Instead of Times Cited, it says Cited by. If we click on that link, we'll be taken to a page that begins to list the sources that cited this article.
Like with most other searches, we can combine terms and use those combinations to help focus our browsing sessions. The available combinations are dependent on the databases we use. Here's a screen shot of an item from the ERIC database along with the search term I used. The search term indicates that I'm interested in sources about academic libraries that include the term 'regression' in the abstract. If it contains regression in the abstract, then the source likely used a statistical technique called linear regression, logistic regression, or some other type of regression. Once I have this initial query, I can begin browsing the 32 titles and abstracts that are a result.
All searches are Boolean searches because all searches in some way assume that we mean a Boolean AND. E.g., if we search for 'cats dogs', Google will assume we mean 'cats AND dogs', and so forth. But there are times when we'll want to get specific with Boolean. In this screenshot, I started off in ERIC with a search for 'academic libraries' as a descriptor. The first item in this search happens to be an article by me. I can see that it has a descriptor called 'library automation' next to it. Say I don't want any articles about library automation in my results. I can add a minus sign to this and re-initiate my query to remove all those sources. This is an example of the Boolean NOT, and we can see that it resulted in around 1300 fewer results.
When we browse, therefore, we are attempting to locate key qualities from our results or our initial lists (e.g., authors, subjects, etc.). These lists include the titles, the abstracts, the thesauri, and so forth. And these key terms will help capture what our search is about.
Many databases will offer a way to create, save, and export lists or individual records based on browsing and searching. This helps us easily manage the documents that we highlight as initially important and curate this list as it grows and our search becomes more focused. I'll demonstrate this in a separate video and we'll get more into managing personal information and knowledge in a future module.
Stay tuned for an additional video to show some of this in action.