Ziegler Open Data in Special Collections Libraries
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The document discusses the importance of open data, particularly in special collections libraries, highlighting examples and the transition from historic material to computational data. It emphasizes the need for ethical practices by libraries to avoid the pitfalls of data brokers, including concerns about representation and cultural sensitivity. The author proposes strategies for improvement, such as standardizing feedback processes and collaborating with community groups to ensure responsible data management.
Ziegler Open Data in Special Collections Libraries
- 1. Open Data in Special Collections Libraries; or, How Can We Be Better Than Data Brokers? Scott Ziegler Louisiana State University Libraries -- NISO Virtual Conference: Open Data Projects June 13, 2018
- 2. Open Data Open data is data that can be freely used, re-used and redistributed by anyone - subject only, at most, to the requirement to attribute and sharealike. -Open Data Handbook (http://opendatahandbook.org/guide/en/what-is-open-data/) @ScottLZiegler 2
- 3. Examples of Open Data Civic ● Philadelphia Open Data (https://www.opendataphilly.org/ ) ● Baton Rouge Open Data (https://data.brla.gov/) Weather ● National Weather Service (https://www.weather.gov/) ● Louisiana Office of State Climatology (http://www.losc.lsu.edu/) 3@ScottLZiegler
- 4. Open Historic Data As a subset of open data, open historic data is free for anyone to use for any purpose and is created from historic material. Specifically, I’ll be focusing on data created from historic material held within special collections libraries. 4@ScottLZiegler
- 5. Digitization: From Page to Digital Facsimile 5
- 6. Dataset: From Facsimile to Computational Data 6@ScottLZiegler
- 7. Live Demo: http://bit.ly/NISOdemo (Everyone cross your fingers) 7
- 8. From Data to Product Data Product (This is the part we supply) (Usually, lots of work needs to go here) 8@ScottLZiegler
- 9. We Don’t Open Everything Cultural Sensitivity Libraries and Archives have material that represent groups in ways that are racist, sexist, etc. Privacy Personally identifiable information about living individuals 9@ScottLZiegler
- 10. Meanwhile, Out in the World 10
- 11. Meanwhile, Out in the World Algorithms of Oppression Safiya Noble Automating Inequality Virginia Eubanks Weapons of Math Destruction Cathy O’Neil 11@ScottLZiegler
- 12. Meanwhile, Out in the World Equifax Breach (Reported) Cambridge Analytica (Reported) September 2017 March 2018 Mark Zuckerberg testifies before Congress April 2018 European Union implements new data collection regulations May 2018 June 2018 Facebook gives data to telecom firms (Reported) 12@ScottLZiegler
- 13. Data Brokers Collect information about individuals from a wide variety of sources Package data to create a profile of a person Sell this package to advertisers, credit agents, government entities 13@ScottLZiegler
- 14. So, Are We Better Than Data Brokers? 14@ScottLZiegler
- 15. Intentions and Subjects Our intentions are better ● Research not personal profit Our subject is different ● Individuals we deal with are often historical 15@ScottLZiegler
- 16. Intentions and Subjects Intent: Intent is not particularly important. Outcomes and results are important. - Safiya Nobel, Algorithms of Oppression Harm should be understood in wider terms than just individuals 16@ScottLZiegler
- 17. How Could We Be Better? 17@ScottLZiegler
- 18. Taking Advantage of the Help Already Out There Benefit from the expertise of others ● Bring the writings of humanities/social science to the development team 18@ScottLZiegler
- 19. Standardize the Practice of Asking For Help Representation Officers ● Person in charge of investigating who is being represented in a digital project ● Research possible partners from that group/community Tie this closely to the role of outreach/promotion. ● We want to act as though the people being described will be looking closely at the description 19@ScottLZiegler
- 20. Standardize a Path for Feedback and Adjustments Clarify why we did what we did ● “During the planning phase of this project, we worked with the following scholars and community groups” And how anyone can suggest we do it otherwise ● Perhaps a form and/or contact email address Explain what the process looks like for considering changes ● Though we might not be able to accommodate every request for modification, these are the steps we will take after we receive your comments 20@ScottLZiegler
- 21. This Is Going to Be Lots of Work ● It’s work to read books ● It’s work to apply these ideas to our day jobs ● It’s work to listen to criticism of our projects ● It’s work to try to get people to participate And Also: ● It’s work to help us ● It’s work to explain things to us in a way that we’ll understand 21@ScottLZiegler
- 22. Thank You Thanks for listening Please reach out if you want to talk more @ScottLZiegler sziegler1@lsu.edu 22
Editor's Notes
- #2: Talking about (1) open data in special collections: what this is, why we do it (2) what it means to work with data in the current social context, in which a shocking amount of data about is gathered, packaged and sold After talking about one specific example of using open historic data to open new types of interaction with archival material, I’ll use the case of data brokers, people and organizations that collect and sell data, as a means for thinking about what we shouldn’t be doing with open historic data. I rely heavily on the work and thoughts of many people. I’ll argue that doing so is the only way to ensure that we’re better than data brokers.
- #8: While my team and I were busy playing with all this data, a lot was happening out in the world.
- #10: Beyond the legal constraints (HIPPA, COPPA, etc), and traditional archival concerns of privacy, we’re also concerned about how our data is
- #11: While my team and I were busy playing with all this data, a lot was happening out in the world.
- #12: Significant scholarship on the misuses of data was released.
- #13: And to compliment the scholarship “Oh shit, this affect us” Also in April, CNBC reported that data analytics firm CubeYou has app suspended from Facebook for sharing data with advertises, suggesting that what Cambridge Analytica was doing is much more common that we knew. On Tuesday of this week, as I was putting this slide together, Mark Zuckerberg was testifying to congress about the use of Facebook data.
- #14: It’s in the context that I want to weigh what I do against the creepy business of data brokers, how gather personal information repackage and sell it to anyone for any purpose. Cambridge Analytica doesn’t consider itself a data broker, I should mention. There are plenty of shades of creepiness, to be sure. I’m using the data broker example as a flash point against which to compare my own work. I use it in general terms to mean people who benefit from data of others, by the representation of others. And what bothers me is that practice of representing other people and benefiting from this representation
- #16: Here’s one way of thinking about it: Basically, we’re not creating/sharing this data to make money, or to make anyone’s life harder And the people that we’re describing are usually deceased, and probably cannot be harmed by our work.
- #17: Dr Nobel writes, “Many people say to me, ‘But tech companies don’t mean to be racist; that’s not their intent.’ Intent is not particularly important. Outcomes and results are important.”
- #19: I’ve never thought of myself as someone how doesn’t take the expertise of others seriously, but I need to face the fact that I haven’t always acted like I do. There have been many calls to combine technologists with social scientists and humanists. In my library, I work very closely with the development team, many of whom have a background in the humanities.
- #20: Beyond bringing the writings of others to us, standardize the way that we ask outside scholars, community members for assistance Build things with the assumption that they’ll be seen by the people being described in them
- #21: I’m not sure how well this work for everything, but a place to start is to be explicit with any digital project we put out that we understand that we’re describing people who are not here to speak for themselves. Make the process explicit: “We worked with the following scholars for advice and guidance” When we are doing our best, there is no reason to be opaque or mysterious Following Cathy O’Neil’s suggestions from her book Weapons of Math Destruction, I’d like to work on projects in which the description of people updated as needed, the decisions are transparent and the conclusion and assumptions are open to scrutiny.
- #22: And this is just from our point of view. It’s always work to write the books and to continuously point out to us that we inadvertently harm people It’s work to help us It’s work to explain things to us in a way that will will understand Without a way to pay these scholars for their expertise, I’m not sure how many will be willing to help. Identifying individuals based on their interests is the first step I have in mind However, before anything else a commitment is necessary from us: a commitment to read what we can and learn what we can; to bring the literature into the shop and struggle with the adoption of it in our everyday work.