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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
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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
April 24, 2014� 70�
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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