todd carpenter presentation at project muse publishers meeting - april 24, 2014
DESCRIPTION
Presentation by Todd Carpenter during the Project Muse Publishers meeting in Baltimore, MD on April 24, 2014. During this talk, Todd discussed standards related to scholarly publishing and the output of several NISO initiatives.TRANSCRIPT
Around the publishing technology world in 45 minutes
A bit on NISO & standards for digital content Authorship & Iden>fica>on Demand Driven Acquisi>on Open Discovery Annota>on Altmetrics
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Photo: Minneapolis College���of Art and Design Library �
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! Non-‐profit industry trade associa>on accredited by ANSI
! Mission of developing and maintaining technical standards related to informa>on, documenta>on, discovery and distribu>on of published materials and media
! Volunteer driven organiza>on: 400+ contributors spread out across the world
! Responsible (directly and indirectly) for standards like ISSN, DOI, Dublin Core metadata, DAISY digital talking books, OpenURL, MARC records, and ISBN
About
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April 24, 2014�
38% Publishers/Publishing Organizations �
27% Libraries/Library Organizations �
123 LSA Members �(non-voting) �
35% Library Systems Suppliers, Publishing Vendors & Intermediaries �
ISO �
ANSI �
Other SDOs �
National Information Standards Organization (NISO)
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Standards are familiar, even if you don’t no4ce
Image: DanTaylor Image: Joel Washing
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Communica>ng science has changed
Image: Walters Art Museum
Image: Domenico, Caron, Davis, et al.
Being an author isn’t what it used to be
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Standard Model Higgs boson paper
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Y
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Y
Y
• ISO 27729: Informa>on & Documenta>on -‐-‐ Interna>onal Standard Name Iden>fier (ISNI)
• Launched in Spring 2012 • Iden>fier for public iden>ty of par>es in cultural crea>on across all media
• Main contributor is the Virtual Interna>onal Authority File (VIA) – Created by 16 na>onal libraries
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Nearly 7.5 Million ISNIs are assigned Another 6 million “unverified” names
800,000 researchers/scholars 490,000 ins>tu>ons
Authorita4ve iden4ty (ISNI)
Versus Individually asserted ID (ORCID)
Poten>al reference of the future?
<ORCID/ISNI>, <ISSN>, <Vol/Issue [DOI metadata]>, <Ins>tu>on ID>, <Geo-‐loca>on [based on ISNI]>,
<Date [DOI metadata]>, <DOI>
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ODI -‐ Open Discovery Ini>a>ve
The context for ODI • Emergence of Library Discovery Services solu>ons
– Based on index of a wide range of content – Commercial and open access – Primary journal literature, ebooks, and more
• Adopted by thousands of libraries around the world, and impact millions of users
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General Goals
• Define ways for libraries to assess the level of content providers’ par>cipa>on in discovery services
• Help streamline the process by which content providers work with discovery service vendors
• Define models for “fair” linking from discovery services to publishers’ content
• Determine what usage sta>s>cs should be collected for libraries and for content providers
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Balance of Cons>tuents Libraries
Publishers
Service Providers
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Marshall Breeding, Independent Consultant �Jamene Brooks-Kieffer, Kansas State University �Laura Morse, Harvard University�Ken Varnum, University of Michigan����
Sara Brownmiller, University of Oregon�Lucy Harrison, Florida Virtual Campus (D2D liaison/observer) �Michele Newberry, Independent �
Lettie Conrad, SAGE Publications �Jeff Lang, Thomson Reuters �Linda Beebe, American Psychological Assoc �
Aaron Wood, Alexander Street Press �Roger Schonfeld, JSTOR, Ithaka�
Jenny Walker, Independent Consultant �John Law, Proquest�Michael Gorrell, EBSCO Information Services ��
David Lindahl, University of Rochester (XC) �Jeff Penka, OCLC (D2D liaison/observer) ��
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Subgroups
• Technical recommenda>ons for data format and data transfer
• Communica>on of library’s rights/descriptors regarding level of indexing
• Defini>on of fair linking • Exchange of usage data
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Deliverables
• Vocabulary • NISO Recommended Prac>ce – Data format and data transfer – Library rights to specific content – Level of indexing – Fair linking – Usage sta>s>cs
• Mechanisms to evaluate conformance with recommended prac>ce
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Current steps
• 30-‐day public comment period October 18-‐November 18, 2013
• Working Group evalua>on of comments, edits to RP, responses
• Working Group approval (spring) • Discovery to Delivery Topic CommiNee approval (summer)
• NISO Publica4on (summer)
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Demand-‐Driven Acquisi>on (DDA) of Monographs
Barbara Fister’s take on the Five Laws of Library Science
http://www.slideshare.net/bfister/erl-slides-fister �
If you’re not ac>vely involved in geong what you want, you don’t
really want it.
Peter McWilliams from "You Can't Afford the Luxury of a Nega8ve Thought"
Goals of NISO DDA Ini>a>ve
• Create a recommended prac>ce to address the complex issues around Demand Driven Acquisi>on of Monographs
• Develop a flexible model for DDA that works for publishers, vendors, aggregators, and libraries. – Flexible, but addresses budget, consor>al buying, aggrega>on and data management needs
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Timeline • Appointment of working group • Informa>on gathering
– Main survey completed – Interviews – Addi8onal surveys
• Public libraries • consor8a
– Informa8on gathering completed
• Comple8on of ini8al draD • Gathering of public comments
• Comple8on of final report
Aug 2012 Aug 2013
Nov 2013
Mar 2014 Mar-‐Apr 2014 May 2014
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Commiqee members • Lenny Allen
Oxford University Press • Stephen Bosch
University of Arizona • Scoq Bourns
JSTOR • Karin Byström
Uppsala University • Terry Ehling
Project Muse • Barbara Kawecki
YBP Library Services • Lorraine Keelan
Palgrave Macmillan • Michael Levine-‐Clark
University of Denver • Rochelle Logan
Douglas County Libraries
• Lisa Mackinder University of California, Irvine
• Norm Medeiros Haverford College
• Lisa Nach>gall Wiley
• Kari Paulson ProQuest
• Cory Polonetsky Elsevier
• Jason Price SCELC
• Dana Sharvit Ex Libris
• David Whitehair OCLC
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NISO DDA RECOMMENDATIONS (DRAFT)
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Outline of DDA Recommenda>ons • Goals for DDA • Choosing content to make available • Choosing a DDA model • Profiling content to include • Loading records • Removing records • Assessment • Preserva>on • Consor>a & DDA • Public Libraries & DDA
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1. Establishing Goals
• Four Broad Goals for DDA – Saving Money – Spending The Same Amount of Money More Wisely
– Providing Broader Access – Building a Permanent Collec>on via Patron Input
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2. Choosing Content to Make Available • Important Issues – Not all p-‐books available as e-‐books – No single supplier provides all e-‐books – Not all e-‐books available via DDA or under same models
• Therefore – More comprehensive coverage requires more suppliers and more models
– Broadest coverage possible = include print – Approval vendors can help manage DDA across mul>ple suppliers
• Publishers should recognize that libraries may wish to limit number of suppliers, and plan accordingly
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3. Choosing DDA Models Mix of auto-‐purchase and Short Term Loans based on goals of program
• Auto-‐Purchase – Purchase triggered on the first use longer than free browse – Purchase triggered awer set number of uses – Purchase triggered awer set number of STLs
• Short Term Loans (short term rental) – A set number of STLs prior to auto-‐purchase – Only STLs, with no auto-‐purchase
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3. Choosing DDA Models (cont)
• Evidence-‐based acquisi>on – Some>mes only op>on based on plaxorm capabili>es
– Library and publisher should develop expecta>ons based on analysis of past usage
• Publishers may wish to par>cipate in some or all models.
• Some concern by publishers about sustainability of STL
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4. Profiling • DDA profiles should be based on the broadest defini>ons possible within these areas, and rela>ve to goals of the program – Subject coverage should provide access to a wide range of content, even in subjects that may not be core
– Retrospec>ve coverage for cri>cal mass • Especially in programs that otherwise limit coverage • May or may not overlap with print holdings, depending on library preference
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5. Loading Records
• Libraries should – Load records regularly and as soon awer receipt as possible
– Load records into as many discovery tools as possible
– Code records for easy suppression or removal – Enrich metadata to increase discoverability – Load point-‐of-‐purchase records awer purchase to ease acquisi>ons workflow/payment
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6. Removing Content
• Libraries should: – Remove records from all discovery tools as soon as feasible, owen using supplier’s delete file
– Establish regular cycle for removal – Maintain a record of >tles removed for assessment
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7. Assessment • There are mul>ple reasons for assessment, so this should be planned from the start – Measuring overall effec>veness of the program – Measuring success at cost reduc>on – Measuring usage – Predic>ng future spending – Managing the considera>on pool
• Data sources might include – COUNTER reports – Vendor/publisher supplied reports – ILS or other local data
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8. Preserva>on
Libraries and publishers should work together to ensure that un-‐owned content remains available, perhaps in partnership with third-‐party solu>ons such as LOCKSS and Por>co.
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How DDA impacts specific groups 9. Consor4a DDA Three basic models – Mul>plier (a mul>ple of list price allows shared ownership)
– Limited Use (shared ownership, but with a cap on use before a second copy purchased)
– Buying Club (shared access to considera>on pool, but individual ownership)
10. Public Library DDA – Mediated for greater control (fewer resources) – Wish lists – Owen not through the catalog
April 24, 2014� 40�
Reading can be a social ac>vity
Is this what you thought we meant?
Reading isn’t necessarily anti-social�
Reading can be very social�
“Books have been held hostage offline for far too long. Taking them digital will unlock
their real hidden value: the readers.” – Clive Thompson
The Future of Reading in a Digital World in Wired Magazine 17.06 (2009)
What’s so hard about sharing annota>ons?
How do we find what we want to share?
What does page “147” mean in a re-‐flowable text?
Version control and
Edi>on varia>ons
Sharing between walled gardens
Chapter & verse? Character count?
X-‐Path? Pre/post mark hashing?
Some (imperfect) loca8on methods
Who’s done & doing what?
• NISO hosted a series of thought leader mee>ngs in 2012
• Recommended focus on loca>on determina>on (started group, now disbanded)
• Open Annota>ons model based on work with Open Annota>on Collabora>on
• W3C Annota>ons mee>ng last month – New W3C working group forming as part of their Digital Publishing ini>a>ve.
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What are the infrastructure elements
of alternative assessments?
Basic Definitions������
(So we are all talking��� about the same thing)
Comparison across providers �
Source: Scott Chamberlain, Consuming Article-‐Level Metrics: Observations And Lessons From Comparing Aggregator Provider Data, Information Standards Quarterly, Summer 2013, Vol 25, Issue 2. �
Element Identification
Open exchange of component data
TRUST
=�
What is NISO working toward?
Steering Commiqee • Euan Adie, Altmetric • Amy Brand, Harvard University • Mike Buschman, Plum Analy>cs • Todd Carpenter, NISO • Mar>n Fenner, Public Library of Science (PLoS) (Chair) • Michael Habib, Reed Elsevier • Gregg Gordon, Social Science Research Network (SSRN) • William Gunn, Mendeley • Neoe Lagace, NISO • Jamie Liu, American Chemical Society (ACS) • Heather Piwowar, ImpactStory • John Sack, HighWire Press • Peter Shepherd, Project Counter • Chris>ne Stohn, Ex Libris • Greg Tananbaum, SPARC (Scholarly Publishing & Academic Resources Coali>on)
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Alterna4ve Assessment Ini4a4ve
Phase 1 Mee4ngs
October 9, 2013 -‐ San Francisco, CA December 11, 2013 -‐ Washington, DC
January 23-‐24 -‐ Philadelphia, PA Round of 1-‐on-‐1 interviews – March/Apr
Phase 1 report expected in May 2014�
Mee>ngs’ General Format
• Collocated with other industry mee>ng • Morning: lightning talks, post-‐it brainstorming • Awernoon: discussion groups – X – Y – Z – Report back/react
• Live streamed (video recordings are available)
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Mee>ng Lightning Talks • Expecta>ons of researchers • Exploring disciplinary differences in the use of social media in
scholarly communica>on • Altmetrics as part of the services of a large university library
system • Deriving altmetrics from annota>on ac>vity • Altmetrics for Ins>tu>onal Repositories: Are the metadata
ready? • Snowball Metrics: Global Standards for Ins>tu>onal
Benchmarking • Interna>onal Standard Name Iden>fier • Altmetric.com, Plum Analy>cs, Mendeley reader survey • Twiqer Inconsistency
“Lightning" by snowpeak is licensed under CC BY 2.0 �
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SF Mee>ng – General outputs
• The importance of best prac>ces for media coverage of science (using DOIs, etc.)
• More Altmetrics research is needed and could be promoted through this group
• Providing a standard set of research outputs that we can use to compare different services
• The importance of use cases for specific stakeholder groups in driving the discussion forward
April 24, 2014� 69�
SF Mee>ng Discussions • Business & Use cases
– Publishers want to serve authors, make money – People don’t value a standard, they value something that helps them – … Couldn’t iden>fy a logical standard need that actors in the space would value,
and best prac>ces are of interest
• Quality & Data science – Themes: context, valida>on, provenance, quality, descrip>on & metadata – We'll never get to the point where assessment can be done without a human
in the loop, but discovery and recommenda>on can
• Defini>ons – Define “ALM” and “Altmetrics” – Map the landscape – We'll never get to the point where assessment can be done without a human in
the loop, but discovery and recommenda>on can
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DC Mee>ng Discussions • Business and Use Cases • Discovery
– metrics only get generated if material is discovered
• Qualita>ve vs. Quan>ta>ve • Iden>fying Stakeholders and their Values
– stakeholders in outcomes / stakeholders in process of crea>ng metrics – shared values but tensions – branding
• Defini>ons/Defining Impact – metrics and analyses – what led to success of cita>on? – how to be certain we are measuring the right things
• Future Proofing – what won't change – impact -‐ hard to establish across disciplines
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Philly Mee>ng Discussions • Defini>ons
– Define life cycle of scholarly output and associated metrics – Qualita>ve versus Quan>ta>ve aspects -‐ what is possible to define here – Consider other aspects of these data collec>ons
• Standards – Develop defini>ons (what is a download? what is a view?) – Differen>ate between scholarly impact versus popular/social use – Define sources/characteris>cs for metrics (social, commercial, scholarly)
• Data Integrity – Counter biases/gaming – Associa>on with credible en>>es -‐ e.g. ORCID ID v. gmail account – Reproduceability is key – Everyone needs to be at the table to establish overall credibility
• Use cases (3X)
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Alterna4ve Assessment Ini4a4ve
Phase 2 Presenta4ons of report (June 2014) Priori4za4on Effort (June -‐ Aug, 2014)
Project approval (Sept 2014) Working group forma4on (Oct 2014)
Consensus Development (Nov 2014 -‐ Dec 2015) Trial Use Period (Dec 15 -‐ Mar 16)
Publica4on of final recommenda4ons (Jun 16)
Other work underway
• Open Access Metadata & Indicators • Bibliographic data exchange • SUSHI-‐lite profile • Project Transfer formaliza>on • Book Interchange Tag Suite (BITS) -‐ Poten>al • Data transforma>on -‐ Poten>al • Scholarly data cita>on -‐ Poten>al • E-‐book circula>on data exchange -‐ Poten>al
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We all want our own
May 15, 2013� 75�
For regular updates from NISO
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Questions?
Todd Carpenter
Executive Director [email protected]
National Information Standards Organization (NISO) 3600 Clipper Mill Road, Suite 302 Baltimore, MD 21211 USA +1 (301) 654-2512 www.niso.org
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