Monthly Archives: February 2019

It’s over but I’m not done

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What I seem to have come up with from these readings this week are a set of classification schemes and controlled vocabularies that have been used over the years to augment or replace DDC, LCC, and LCSH to make collections in libraries and archives more inclusive and combat bias – the racism and sexism and exclusionary “norm” view that is part of these “mainstream” systems.

I’m trying to figure out what to do next. I will be working with a student this summer and before that I will be discussing bias in metadata in a brown bag presentation. I want to understand the landscape for the brown bag and I think I am getting there. I also want to have something concrete for the student to work on. The list of classification schemes and controlled vocabularies is incomplete and there are a couple of meta-lists I have found (LOC has one and Bartoc is another) so those need to be reviewed. I don’t think these meta-lists cover everything in terms of controlled vocabularies representing communities, especially from that community’s point of view, but having that as an output could prove to be really useful more generally in the library community.

Beyond that is this concept I have of trying out something to see if bias can be combatted through the front end search interface in addition to the backend where the metadata is created. There seem to be some possibilities with this using Homosaurus. It is a Linked Data source and the example of its use in IHLIA’s search interface is intriguing to me.

I’m also interested in Olson’s work to connect a controlled vocabulary like that in A Women’s Thesaurus to a “mainstream” source like DDC. If Homosaurus can be connected in some way to LCSH terms (and that is a big if that still needs to be investigated), is there utility in offering that as an entryway resource for searching, to help users connect to items that already have records using only LCSH terms? Olson and Ward created the standalone search application for seeing connections between those 2 sources but I haven’t seen anything about if it was ever implemented for research use in an online system. If there isn’t an equivalent or close term in the mainstream source, then there isn’t much point in connecting a controlled vocab term since it would end up lumping into a mainstream category that is too broad or not connecting to anything. But if there are connections, are they helpful to provide as a different view into a collection?

I’m ending this research leave with a lot of questions and I knew I would, but I think I do have a better handle on how to talk about the problem of non-inclusive or exclusionary online research tools and collections. Additionally and more importantly for the topic of bias in metadata, I have a better sense of what has occurred already in efforts to combat that marginalization and make the research process more inclusive through constructing new or modifying current classification schemes and controlled vocabularies.

A joke and thesauri reviewed

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There wasn’t necessarily any logic to what I went through on Day 4 other than they were mostly things in print sitting on my table. I’m pretty sure I’ve heard this one before but one of my readings actually began with a joke: 

How many librarians does it take to change a light bulb? LC doesn’t change light bulbs. They have INCANDESCENT LAMPS, not light bulbs.

Heh. I think I might modify that punch line for my topic to say LCSH can’t change light bulbs because they already have incandescent lamps. It takes a lot for LC to make changes and I haven’t even read the Sanford Berman book that started the major call to update biased terminology about groups of people. (I have the book but I figured out that for research leave it was better to focus on shorter pieces to get through more. I think I’m a slow book reader too.) And LCSH has both light bulbs (http://id.loc.gov/authorities/subjects/sh90003210) and incandescent lamps (http://id.loc.gov/authorities/subjects/sh85041761) so maybe the joke is now they don’t have to change anything at all.

From there I explored more about different thesauri. For instance, I’m pretty sure now that A Women’s Thesaurus from 1987 is not connected to the Women’s Thesaurus that is the basis for the online thesaurus at Atria: Institute on gender equality and women’s history in the Netherlands. That seems to have been an international effort within Europe and published in the Netherlands in the early 1990s where the one I have in print is from the late 1980s and talks about being very U.S.-focused for that first edition but wanting to expand to be international. The chronology might show there could be a connection and there is some overlap in the highest level categories but I don’t have enough info yet to say for sure.

I also reviewed more about the only Linked Data vocabulary I’ve encountered so far, Homosaurus.org. There are no connections to LCSH or any other controlled vocabulary. A Women’s Thesaurus also has no connections to LCSH but it did say in the front matter that when an LCSH term worked, that term was used. They talked about doing that to maintain compatibility with LCSH but there’s no indication in this print version where terms match with LCSH so I’m not sure if you’re just supposed to know that or do that work on your own. And there was also an indication that this thesaurus is set up for electronic use but there is no indication of the format or how to get it (and my guess is that in the late 1980s, it was still pretty local and probably involved floppy disks). Possibilities with both to consider, though, depending on what I want to try doing.

I also got into more details about the work of Hope A. Olson and Dennis B. Ward to link up A Women’s Thesaurus and DDC classification. That project happened in the 1990s and tells me there probably was an electronic version of the thesaurus available somehow. I have another article to review from them that goes into even more detail and I’m kind of thinking there’s going to be something cool there that they figured out.

Gathering and connecting

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Wow, today. I found the best Venn diagram from Hope A. Olson comparing the “mainstream core” perspective offered through classifications like DDC and LCC and controlled vocabs like LCSH to what that “core” actually represents. Its a smaller set within the entirety of Everyone and limited to the following Boolean combination:

white AND male AND straight AND European AND Christian AND middle-class AND able-bodied AND Anglo

The result is a very tiny splotch within all of those concentric circles. It’s pretty awesome and I have needed this in my life before now.

I also got my hands on two separate thesauri for women’s issues (On Equal Terms: A Thesaurus for Nonsexist Indexing and Cataloging from 1977 compiled by Joan K. Marshall and The Women’s Thesaurus from 1987 edited by Mary Ellen S. Capek). I’m interested to see what the differences are between them. They are both in print but The Women’s Thesaurus might have been adapted for online use at Atria from the Institute on gender equality and women’s history in the Netherlands. I’m still figuring that out for sure.

I also sorted out various LGBTQ thesaurus sources from my readings (and in my head). There’s a classification scheme by Dee Michel and David Moore (International Gay and Lesbian Archives Classification System) and there’s another thesaurus from the Netherlands (A Queer Thesaurus: An International Thesaurus of Gay and Lesbian Index Terms) that has become a Linked Data vocabulary called Homosaurus.org. The College of the Holy Cross is now hosting that Linked Data vocabulary online and I still need to check it out some more but IHLIA in Amsterdam is using it to support online searching. I like their concept of supplying Broader Terms, Related Topics, Narrower Terms, and Used For in that visual way. I don’t think there’s a way to activate that without conducting a search first so you don’t start off with that help, but it is an example implementation of controlled vocabulary help.

I am also seeing that some controlled vocabularies are supplying connections to LCSH. The BC First Nations Subject Headings from the Xwi7xwa Library at the University of British Columbia is in PDF format online but identifies connected terms from LCSH. And the Lavender Library, Archives and Cultural Exchange in Sacramento, California has finding aids that include LC subject headings along with their own subject headings. The only reason I know anything about the Lavender Library is because the LGBTQ+ Library at Indiana University uses a classification system based on the one used at Lavender Library (called the LLACE Classification Scheme after the full name of the library) and they were awesome and shared it with me.

I’ve also encountered some vocabularies that are discussed but don’t seem to be available (at least not to me). EBSCO has a thesaurus for its LGBT Life resource but I cannot come up with the thesaurus no matter what I try so I don’t think we have access to that through my institution (we have access to the contents of LGBT Life but not the thesaurus). It was mentioned in one of my readings and would be good to see but it doesn’t look like an option for now.

My list of classification systems and controlled vocabularies is growing and getting a little more organized but I have more to review and learn about and a lot more to understand.

Reading, listing, and still learning

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Today involved digging into details about different classification schemes and controlled vocabularies and I realized I have enough to start a list! I’m interested to see how this list grows and what meta-characteristics they have in common. So far I’m tracking if the classification scheme or controlled vocabulary is available online, if it is in Linked Data format, and where I am finding it (online resource, in a book, in print some other way, etc).

My readings today were about American Indian classification and subject heading issues in Dewey Decimal Classification, Library of Congress Classification, and Library of Congress Subject Headings as well as more information about Dorothy B. Porter and her work to organize, increase, and provide access to the African and African American collections that became the Moorland-Spingarn Research Center at Howard University. Practices for classifying American Indian resources have placed much of this content in the historic past under sections of the catalog about the history of North America (in both DDC and LCC) as if American Indians don’t even exist anymore. And Porter recalled a time when many libraries grouped anything by an African American author under a DDC heading for colonization (and migration). There are clunky ways to somewhat work within these classification systems but only to a point and only for some material. Limitations of DDC to expand and the slow pace of change in LC just seems to allow these problems to languish. So new classification schemes and controlled vocabularies have been developed and I’m learning how they have been used and how they can be applied to aid in the research process. This is where my thoughts turn to Linked Data possibilities but they aren’t well-formed thoughts yet.

And just to make sure I have some warning lights going off in my head regarding Linked Data, I also read about issues of bias in Knowledge Graphs related to the Semantic Web:

  • data bias (Linked Data from sources being mostly about Europe, Japan, Australia, and the US)
  • schema bias (depending on the ontology you can get very different results for a concept like the article’s example, theater)
  • inferential bias (taking data from a source like DBPedia and running inference results in high confidence assumptions from the graph that say things like: “if X is a US president, X is male”).

That graph could use some more learning. 

This brings up something that is coming across in other readings. Bias on its own isn’t necessarily a problem. Everyone has implicit biases. It’s when that implicit bias becomes systemic and reflects out as the appropriate or authorized way to organize and interpret classifications and subject matter – bias without recognition or documentation, without transparency, is a problem. Or in the case of this knowledge graph example, results without context show bias.

Reading and Learning

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Today I read more from Safiya Noble’s book Algorithms of Oppression and then Jessie Daniels’ article from 2013 on “Race and Racism in Internet Studies: A Review and Critique.” I am seeing more how the racism that underlies the United States as a country is reflected and even magnified on the Internet through commercial search engines, the pornography industry online, and the capitalistic way the Internet has developed over time, supporting a dominant color-blind “norm” (aka white and male). Noble shows this through her study of Google search results and Daniels shows this through her critique of Internet studies’ unwillingness to center race or the history of racism as it is manifested in online spaces.

I was also made aware of my own complicity in supporting racist narratives through a meme I had included in a previous blog post. I thought I knew the story behind the meme but I didn’t. I removed it from the blog post and have to accept the fact that I am part of the problem. It was a learning moment to see that what I had shared had a source based on a racist Internet meme, but that is what it is. And I am learning. 

The United States is race-based in how we function. Racial divisions are defined by those in power, a group also defined by race (White), and all other groups are kept in an Other category that exists still today online. Acknowledging this racism (but not accepting it) is one way to figure out strategies to counteract it.

Within the academic library, we have to serve our researchers in a more inclusive way. I think part of this is by being more transparent about the deficiencies of our description, not because we are bad at describing things but because we are part of the aforementioned society and that is reflected in the metadata choices we make and the controlled vocabularies we use. I’m not sure yet how that transparency can be best expressed, but I do think there are ways. 

New Research Leave About Bias in Metadata

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I am starting a new research leave! I am using this leave time to learn about bias in metadata and how that impacts inclusivity in the research process. I have a lot to learn.

I have already encountered excellent classification schemes and controlled vocabularies outside of Library of Congress and Dewey systems that provide better representation and definition for marginalized and underrepresented communities and I expect I will learn about more. I am also, however, taking some steps back and considering who I am in the larger societal system as it is currently functioning. That is a big undertaking and, at the same time, so completely necessary as to be a fundamental underpinning to all of this research.

I have library system and information retrieval specific readings that will inform my specific research topic. I also have readings that I hope are helping me understand more about myself and my experience, the mix of social constructs and facts about who I am (race, gender, sexual orientation, able-bodiedness, where and when I am from) that describe my experience in the world. My experience makes a difference in how I understand issues such as racism and sexism that support the power structures that create the current system where researchers are not able to find the resources they need or engage with collections effectively due to biased metadata and far too limited controlled vocabularies.

If I can recognize and understand where I am positioned in this system and what that means, I am hopeful I will find that I can amplify the work that has already been done and challenge academic libraries and the systems they use to be more inclusive in support of researcher needs.

That’s a lot to understand, learn about, and find the words to express well. I don’t think I have the best capacity for expression right now but I aim to improve my ability to write and speak clearly about how vital it is that information retrieval becomes more inclusive.