Clay Shirky, Fantasy Football, and Using Data to Glean the Future of Library Collections - Radically Different Future of Collection Development
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This document discusses moving from traditional supply-driven library collections to demand-driven collections using data analysis. It notes that collection budgets are unsustainable under traditional models and that data can help lower costs by making collections more precise and responsive to user needs. The document advocates analyzing usage data to modify collecting practices and asserts that demand-driven, user-focused models will become a larger share of budgets. It provides examples of how North Carolina State University uses data like usage statistics, citations, and user feedback to evaluate resources and make evidence-based decisions about collections.
Clay Shirky, Fantasy Football, and Using Data to Glean the Future of Library Collections - Radically Different Future of Collection Development
- 1. Clay Shirky, Fantasy Football, and Using Data to Glean the Future of Library Collections Greg Raschke and John Vickery, North Carolina State University Charleston Conference November 3, 2010
- 2. Assumptions Economics are not sustainable Collections budgets will not grow at rate of past 30 years Unit growth and growth in cost per unit are not sustainable Need to lower costs of overall system Lower unit costs Use data and users to be more precise Therefore collection practices and strategies must change This change will be hard – much reason for optimism
- 3. Supply-Side Collections Print-based, unpredictable demand, and legitimate need for just in case collections Lead to judging quality by size (as in the ARL rankings) and libraries were then held captive to this standard Contributed to inelastic demand for journals and a combination of speculative and package buying Use is secondary to size, dollars expended, and other input measures Credit to David Lewis (http://ulib.iupui.edu/users/dlewis)
- 4. Supply-Side Can Not Continue
- 5. Demand-Driven Collections Make information easily, widely, and cheaply available Collections as drivers of research, teaching, and learning To make special or unique collections held/managed by the library available to the user community and the world
- 6. Demand-Driven – Changing Practice Tension between time-honored role as custodians of scholarship versus enabling digital environment for scholars Not just PDA – portfolio of approaches, but certainly more responsive Utilize new tools and techniques to become advanced analysts Truly embrace evidence based decision making Look at how collections are actually used, not at expressed need
- 7. Demand-Driven – More Assumptions Less tolerance for and less investment in lower use general collections Resource management based increasingly on use Modify collecting based on changes in the actual use Risks of doing nothing – newspapers
- 8. Demand-Driven – Assertions Rewards of adapting – more used and vital than ever Use based and user driven collecting models will take growing share of budget Bet on numbers Bet on good and quick Put resources into enabling digital environment for scholars and custodian role will come out of that strategy
- 9. Why So Much Data? Data analysis is a key component in solving/managing: Increasing pressure for accountability Increasing capability to gather and analyze data Increasing precision in the way we build collections and expend resources Advocacy Changing practice and data analysis at NCSU
- 11. Serials Review 2009 – Open, Data-Driven, and Real-Time Analysis Standardized usage data (where available) Bibliometrics - publication data and citation patterns (e.g LJUR) Impact factor and eigenfactor User community feedback via interactive, database-driven applications Weigh/calculate/quantify user feedback Weigh price against multiple data points Usage ((07 usage+08 usage/2)+ (publications*10)+ (citations*5)+ (Impact Factor) Community Feedback ((Weighted Ranking x % Match) x Total # Rankings) + 0.1 x # of "1s“ Price/feedback value Price/use Merge results to filter out top 20% and bottom 20%
- 12. Looking closer – Finding balance An example - a closer look at print item usage Traditional ILS reporting tools can make this difficult Advanced analytical tools can help What types of questions can we ask? Should Patron-Driven records not purchased be purged after 2 years? How does print item usage break down? Do print items even get used?
- 13. If it’s not used after 2 years… Should PDA records be purged? Maybe… We haven’t even hit 50% usage But what if we take a longer view…
- 14. If it’s not used after 2 years… Things begin to look different
- 15. Looking even closer… How does print item use break down? Single circ usage is consistently ~14% Would this change in a PDA only world?
- 16. Expenditures to University Data
- 17. Expenditures to University Data
- 18. Expenditures to University Data
- 19. Expenditures to University Data
- 20. Measurable Uses of the Collection 2009/2010 Full-text journal downloads* 3,672,600 Database use 1,989,972 Print book circulations/renewals 525,430 Digital collections requests 471,403 E-books 149,815 Reserves** 327,267 Total Uses 7,136,487 * Includes use of NC LIVE full-text content ** Includes textbook, print, and e-reserves usage Measurable Uses of the Collection 2009/2010
- 21. Challenges Have ability to be more precise, more used, and more relevant than ever – need to make the necessary changes Apps are a risk – silo(ing) networked, web environment – connections where libraries can excel Not enough data - still lack much of the comprehensive data we need – must improve quickly Data can punish niche areas, disciplinary variation, and titles without data Open resources impact ability to control and command data
Editor's Notes
- #3: * Reference David Lewis
- #5: Many reasons for this: Technology and increasing amount of content on open networks Changes in publishing Supply-chain capabilities and print-on-demand Increased accountability One reason trumps all others - economics
- #8: “That is what real revolutions are like. The old stuff gets broken faster than the new stuff is put in its place. The importance of any given experiment isn’t apparent at the moment it appears; big changes stall, small changes spread. Even the revolutionaries can’t predict what will happen. Agreements on all sides that core institutions must be protected are rendered meaningless by the very people doing the agreeing. (Luther and the Church both insisted, for years, that whatever else happened, no one was talking about a schism.) Ancient social bargains, once disrupted, can neither be mended nor quickly replaced, since any such bargain takes decades to solidify.” – Clay Shirky “One of the difficult aspects of change, particularly when it is accompanied by complex technology and multiplying data sources, is the ability to give up an old story and develop a new one. The ‘story’ is a common sense version that unfolds.” – Jennifer James “I don’t know. Nobody knows. We’re collectively living through 1500, when it’s easier to see what’s broken than what will replace it. The internet turns 40 this fall. Access by the general public is less than half that age. Web use, as a normal part of life for a majority of the developed world, is less than half that age. We just got here. Even the revolutionaries can’t predict what will happen.” – Clay Shirky
- #9: Spending this year’s money based on last year’s statistics, gut instinct, and what other people are saying. Trends are likely to hold. Price and demand instability. Waiver wire – aggregated packages. Spend money on people because that is what you have always done. Auction process changing everything – differential pricing. Key is management after use and results. Package challenges.
- #12: 13,000+ points of data from 700 users – how do you at least run an initial filter through that data? Relationships between usage data and community feedback data. Way more open and data-driven process than ever before where capturing data and feedback and analyzing it in real-time.
- #22: “Web browser’s dominance is coming to a close. And the Internet’s founding ideology – that information wants to be free, and that attempts to constrain it are not only hopeless but immoral – suddenly seems naïve and stale in the new age of apps, smart phones, and pricing plans.”