PLEASE SEND CATALOGERS:
Metadata Staffing in the 21st Century
Jennifer A. Liss
@cursedstorm
CaMMS Competencies and Educati...
What tasks are catalogers good at?
 Enter text here!
2014-06-27
CaMMS Competencies and Education for a
Career in Catalogi...
Competencies vs.
Performance Indicators
(or, MARC is not a cataloging competency)
2014-06-27
CaMMS Competencies and Educat...
Competencies for catalogers
performing metadata work
Reimagining performance indicators
2014-06-27
CaMMS Competencies and ...
Selected Competencies
 Normalizing data
 Parsing resource metadata
 Exploring information hierarchically
 Recognizing ...
Normalizing data
 Applies content standards
(AACR2, RDA) for resource
description and access
 Expand to use of:
 Archiv...
Parsing resource metadata
 Assigns descriptive metadata
by parsing textual materials
 Expand to:
 Parsing visual materi...
Exploring info hierarchically
 Applies taxonomies by
navigating broader/narrower
terms (LCSH)
 Expand to applying struct...
Recognizing relationships
 Provides additional access
points; performs subject
analysis
 Expand to include:
 ALL OF THE...
With change comes opportunity
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
10
Human dimension of tech change
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
11
Great Expectations
 Everything online
 Everything interlinked
 Everything in one search box
 Everything in your pocket...
What about the semantic web?
(It’s already here)
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
Dawn of the semantic search
Schema.org, K-Graph & Hummingbird
2014-06-27
CaMMS Competencies and Education for a
Career in ...
Schema.org
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
15
Schema.org
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
16
Google Knowledge Graph
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
17
Knowledge Graph in action
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
Knowledge Graph in action
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
19
Google Hummingbird
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
Google keyword search
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
21
Google semantic search
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
22
golden retriever
Google semantic search
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
23
golden retriever
Welcome, robot overlords.
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
The expectation shift
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
NO, IT ISN’T.
2014-06-27
CaMMS Competencies and Education for a
Career in Cataloging IG
Semantic web: SEND CATALOGERS
 Normalize data
 Explore information hierarchically
 Structure data for machine manipulat...
Image credits
Slide 3 Balance, Hans Splinter
Darth Vader in a Kilt playing the Bagpipes on a Unicycle,
Trevor Dykstra
Slid...
THANK YOU!
Find these slides:
bit.ly/sendcatalogers
Jennifer A. Liss
Head, Monographic Cataloging Image
Indiana University...
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Please send catalogers : metadata staffing in the 21st century

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This presentation addresses the ways in which traditional catalogers are uniquely positioned to make valuable contributions to the linked library data future and outlines competencies for performing metadata work.

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  • Let’s spend a couple minutes doing some group brainstorming.
    Let’s keep these actionable tasks in mind but for now, I’d like to transition into talking about competencies.
  • Competencies are behaviors or tasks that must be completed in order to show adequate job performance. Competencies are usually not concrete in nature.
    For example, being a performance artist requires balance—balance is a competency.
    How do we know that a performer possesses good balance? We look for performance indicators.
    For example, you may observe a bagpiping Sith Lord riding a unicycle and you may draw a conclusion as to whether that performer has demonstrated the competency of balance adequately.
    On their own, neither the unicycle, nor the bagpipes, nor the costume are competencies; they’re tools of the performer’s trade.
    Similarly, MARC is one of many tools catalogers use to perform their jobs. Consistent and correct usage of MARC is evidence that a cataloger has a met one of the key competencies for catalogers: the structuring of data for machine manipulation.
  • When “traditional catalogers” perform metadata work, I don’t automatically assume that existing competencies must change (new competencies occasionally arise—I’ll give an example later)
    I do however, expect tasks and performance indicators to change.
    When introducing metadata work into daily duties of a cataloger, the highest concentration of change is more likely to be in the realm of tools and tasks.
    This is what I’d like to address next—how to reimagine performance indicators in light of expanded metadata tasking
  • This is, of course, not an exhaustive list! I’ve selected a few competencies for the sake of illustration.
  • Standardizing data values, by using tools like content standards, helps us normalize data for indexing, display, etc.
    Being familiar with a set of content standards such as AACR2 and RDA primes us for cataloging work even when we’re in unfamiliar territory--we don’t have to start completely from scratch every time we’re met with something new, we have a framework to build upon
    The benefit of learning new content standards and how they are applied in a user community, is that you begin to see the biases of standards you know well
    For example, I refuse to use RDA to describe archival materials. Why? How do you reconcile the idea of FRBR Expression with a handwritten letter? RDA has a built-in publication bias. This doesn’t work for archival materials.
    Danger of using/knowing only one standard is that you’re unaware of how metadata you produce “plays” with other metadata in The Wild.
    Be aware of your blinders. You can’t know everything but you can try to know what you don’t know.
  • Parsing a resource for descriptive metadata is one of the first things catalogers are trained to do. Experienced catalogers do this so naturally, we’re not aware we’re doing it.
    What happens when the resource is predominantly visual, rather than textual, in nature? How does one parse an image?
    Here’s an instance where there may be a new competency to be considered! Visual literacy is required for successful image description—this is hardly new territory for media catalogers but it not so with those who only cataloged text-based resources.
  • Catalogers’ brains seem to be hard-wired to recognize structural patterns and hierarchy of information.
    This competency is needed to master taxonomies that contain broader and narrower terms, such as Library of Congress Subject Headings.
    This competency is also useful for encoding textual content for machines to parse and display; has been useful in text encoding projects using TEI and EAD.
    Is domain expertise (in a subject or language) a competency?
  • Recognizing and recording relationships has always been important in cataloging work; in AACR2-speak, think of all of those main and added entries we supply during cataloging and subject analysis.
    RDA really pushes us to focus on this particular competency.
    Think of all of those 7XX and $e relator terms that RDA wants you to add…
    The identifier at the center is for James Whitcomb Riley. We have physical materials (books as well as letters, papers, and photographs in which Riley is the subject); many of these objects are being digitized.
    By declaring relationships, one can discover that Lew Wallace once posed with Riley for some photographs; and that Riley wrote letters to the man who would become is biographer, John Marcus Dickey--our special collections library hold’s the biographer’s papers
    This linked data stuff REALLY hinges on authority data!
  • Change is nothing new to catalogers. Technology has always seemed to be changing out from under us—standards changed and continued to develop (MARC), we implemented OPACs, etc.
  • Technology doesn’t fundamentally change people; however, it can have a significant impact on their behaviors and expectations.
    And then there’s that semantic web thing…
  • Schema.org was the brainchlid of Google, Yahoo, Bing! Introduced in summer of 2011, it was implemented to structure web content semantically to support searching.
    This means that not just headings and paragraphs are being marked up; ingredients and cook times are encoded for recipe pages, actors, directors, and synopses are encoded in movie pages, and location, hours, and contact information are encoded in restaurants’ webpages.
    Shown here is a search result from a search on events in Las Vegas. Dates and shows can be displayed because that data is marked up semantically on this particular website.`
  • Because most emails are coded in HTML, semantic markup is appearing in our inboxes too.
  • Google’s Knowledge Graph was introduced in 2012.
    Although Google hasn’t divulged much about the Knowledge Graph’s inner workings, the word “graph” suggests linked data graphs (triple statements).
    Relationships between people, places, things, and concepts are being encoded semantically. I have to imagine that some sort of taxonomy is being built to map complex concepts (such as broader, narrower, and related terms).
  • You know those cards that pop up at the right of your web browser, next to the search results list? That is data is being pulled in from the Knowledge Graph.
    A keyword search cannot do this; this feature is powered by taxonomies much like the controlled vocabularies we use in libraries. The difference is the Knowledge Graph is expressed in linked data.
    In DaVinci’s card, related artists and works of art are displayed.
  • Drilling down into works of art related to the search.
  • And then Google pushes things even further. Google quietly launched it’s new Hummingbird search algorithm in late August 2013 and announced the release a month later.
  • This algorithm is a complete rewrite; gone now is the keyword search, which, although powered by sophisticated algorithms, was still essentially a machine matching strings of text and displaying results that seemed to be the most relevant.
  • Instead of keywords, the new search algorithm focuses not on text strings but on concepts.
    Searching is meant to be conversational. Now, even when you type in keywords, Google seems to be answering natural-language question you didn’t ask.
  • This is where Google’s Knowledge Graph comes in—a rich taxonomy, expressed in linked data, provides powerful platform on which to build algorithms that tease out what searchers REALLY want to know.
    In this case, Google guessed that I wanted to know more about the dog breed (Wikipedia and American Kennel Club is at the top of list), or perhaps that I’m interested in adopting a retriever.
    The one-box approach to searching was once a “blind” matching of keywords; that one-box search now operates like a machine-facilitated reference interview
  • How serious is this change to semantic search?
  • Like it or not, Google is EVERYWHERER. It’s not just in search browsers that Google will be implementing semantic search; Google is in the OS and hardware markets too, meaning that semantic search is in our pockets, on our faces, and around our wrists.
    User expectations are already beginning to shift; our users will never be happy with keyword search again—this is very good news for catalogers.
  • How often have we heard this argument, usually offered as a reason why structuring data is a waste of time?
    It is no longer all about keyword searching. Please learn as much as you can about semantic search and start educating your staff and your administrators.
  • Rest assured catalogers already possess the core competencies needed in order to participate in the semantic web.
    The challenge will be in reimagining the tools we use to do our work and figuring out what those performance indicators will be.
  • Please send catalogers : metadata staffing in the 21st century

    1. 1. PLEASE SEND CATALOGERS: Metadata Staffing in the 21st Century Jennifer A. Liss @cursedstorm CaMMS Competencies and Education for a Career in Cataloging Interest Group June 27, 2014
    2. 2. What tasks are catalogers good at?  Enter text here! 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 2
    3. 3. Competencies vs. Performance Indicators (or, MARC is not a cataloging competency) 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG
    4. 4. Competencies for catalogers performing metadata work Reimagining performance indicators 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 4
    5. 5. Selected Competencies  Normalizing data  Parsing resource metadata  Exploring information hierarchically  Recognizing relationships 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 5
    6. 6. Normalizing data  Applies content standards (AACR2, RDA) for resource description and access  Expand to use of:  Archives (DACS)  Moving images (AMIM)  Cultural objects (CCO)  Data sets (?) 214 p. 62 pages 7 cubic feet (7 boxes) 179 leaves; text block: 26.6 x 19.1 cm (10 1/2 x 7 1/2 inches); text area: 17 x 13 cm (6 3/4 x 5 1/8 inches); oak covers: 27.3 x 19.8 cm (10 3/4 x 7 7/8 inches) 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 6 What are the biases of each standard?
    7. 7. Parsing resource metadata  Assigns descriptive metadata by parsing textual materials  Expand to:  Parsing visual materials for description and access 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 7
    8. 8. Exploring info hierarchically  Applies taxonomies by navigating broader/narrower terms (LCSH)  Expand to applying structural metadata standards:  Books (TEI)  Finding aids (EAD)  Music (MEI) 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 8
    9. 9. Recognizing relationships  Provides additional access points; performs subject analysis  Expand to include:  ALL OF THE THINGS 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 9
    10. 10. With change comes opportunity 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 10
    11. 11. Human dimension of tech change 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 11
    12. 12. Great Expectations  Everything online  Everything interlinked  Everything in one search box  Everything in your pocket 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 12
    13. 13. What about the semantic web? (It’s already here) 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG
    14. 14. Dawn of the semantic search Schema.org, K-Graph & Hummingbird 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG
    15. 15. Schema.org 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 15
    16. 16. Schema.org 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 16
    17. 17. Google Knowledge Graph 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 17
    18. 18. Knowledge Graph in action 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG
    19. 19. Knowledge Graph in action 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 19
    20. 20. Google Hummingbird 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG
    21. 21. Google keyword search 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 21
    22. 22. Google semantic search 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 22 golden retriever
    23. 23. Google semantic search 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 23 golden retriever
    24. 24. Welcome, robot overlords. 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG
    25. 25. The expectation shift 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG
    26. 26. NO, IT ISN’T. 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG
    27. 27. Semantic web: SEND CATALOGERS  Normalize data  Explore information hierarchically  Structure data for machine manipulation  Recognize and declare relationships  Disambiguate persons, corporations, places, topics, and things 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 27
    28. 28. Image credits Slide 3 Balance, Hans Splinter Darth Vader in a Kilt playing the Bagpipes on a Unicycle, Trevor Dykstra Slide 7 James Whitcomb Riley and Lew Wallace, The Lilly Library Slide 10 Students Using Card Catalog, Indiana University Slide 11 Bernard Fry with the Hazeltine 2000, Indiana University Slide 13 Calvin & Hobbes, Bill Watterson Slide 24 Android robot toy, Lucas Zallio 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG 28
    29. 29. THANK YOU! Find these slides: bit.ly/sendcatalogers Jennifer A. Liss Head, Monographic Cataloging Image Indiana University, Bloomington Libraries jaliss@indiana.edu 0000-0003-3641-4427 2014-06-27 CaMMS Competencies and Education for a Career in Cataloging IG Please Send Catalogers: Metadata Staffing in the 21st Century by Jennifer A. Liss is licensed under a Creative Commons Attribution 4.0 International License.
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