Trending Issues in Licensed Content

EIFL GA 2014

Arnold HirshonAssociate Provost & University Librarian

Case Western Reserve UniversityCleveland, OH USA

trends to watch: content

• Journals: TDM, DS and controlling your own destiny

• E-books: messy management

• Discovery layers: democratizing access

• Measuring value: emerging assessment techniques

TDM: what is it? (as defined by publishers)

http://www.stm-assoc.org/2012_03_15_Sample_Licence_Text_Data_Mining.pdf

“Text and Data Mining Output” means the result of any Text and Data Mining activity or operation, capable of fixation, reproduction and/or communication in any form, such as the creation of an index, reference, abstract, relative or absolute description or representation of Publishers’ Content, an algorithm, formula, metrics, method, standard or taxonomy describing or based on Publishers’ Content, a relational expression or measurement, whether scalable or not, of Publishers’ Content, extraction, alternative representation or translation, expression or discussion of any extracts from mined Publisher’s Content, whether in the form of a direct extraction or a representation in any form which is based on Publishers’ Content.

TDM: what is it? what is the licensing concern?

• Globally, the research community generates >1.5 million new scholarly articles per year

• TDM mines (collects) data from a large dataset (e.g., a publisher’s full-text journal database) so the text can be accessed, copied, analyzed, annotated and related to existing knowledge about a field

Even if the user has access rights to the material, making annotated copies can be illegal under current [U.K.]

copyright law without the permission of the copyright holder

Diane McDonald and Ursula Kelly. “The Value and Benefits of Text Mining.” http://www.jisc.ac.uk/reports/value-and-benefits-of-text-mining

http://www.jisc.ac.uk/sites/default/files/value-text-mining.pdf

TDM: so why is it important?

digitization“big data”

born digitalGIS

statistical analysislongitudinal studies

visualizationdigital humanities

“digital scholarship”

TDM example: Google NgramsLongitudinal frequency of mentions of names indexed

within the texts from Google Books of four English Victorian novelists

https://books.google.com/ngrams

Longitudinal frequency of mentions of terms indexed within

the texts from Google Books of the words “love” and “sex”

the value of text mining: key findings

• Significant use in biomedical sciences, chemistry; early adoption in social sciences & humanities

• Benefits: increased researcher efficiency; unlock hidden information to develop new knowledge; improve research and evidence base; improve the research process and quality

• Entry costs: sophisticated technology, transaction costs, and negotiating “a maze of licensing agreements covering the collections researchers wish to study”

• Copyright restrictions can make it difficult to source robust data, which limits the availability of material to text mine

• Resolving legal restrictions requires changes to the current licensing system and global adoption of interoperability standards

Diane McDonald and Ursula Kelly. “The Value and Benefits of Text Mining.” http://www.jisc.ac.uk/reports/value-and-benefits-of-text-mining

http://www.jisc.ac.uk/sites/default/files/value-text-mining.pdf

the new conundrum: copyright originally was meant to protect creative producers, but it may now be inhibiting new knowledge discovery and innovation

TDM: STM Declaration (Nov. 2013)STM Declaration: Text and Data Mining for Non-commercial Scientific Research: a Statement of Commitment By STM Publishers to a Roadmap to Enable Text And Data Mining (TDM) For Non-Commercial Scientific Research In the European Union http://www.stm-assoc.org/2013_11_11_Text_and_Data_Mining_Declaration.pdf

“Signatories commit to granting the necessary copyright licenses to permit the text and data mining of copyright-protected content and other subject-matter on reasonable terms for non-commercial scientific research purposes in the European Union. … [S]ignatories will retain the ability to apply and develop safeguards, such as technological solutions to minimise online system performance degradation.”

SIGNATORY PUBLISHERS: American Chemical Society; American Institute of Physics; American Physical Society; British

Medical Journal Publishing Group; Brill Publishers; Elsevier;Georg Thieme; Hogrefe Verlag; Institute of Physics/IOP;John Wiley & Sons; New England Journal of Medicine; Oxford University Press; Royal Society of Chemistry; Springer Science;

Taylor and Francis; Wolters Kluwer Health

• Commitment 1: The Sample Clause * for non-commercial Text and Data Mining in scientific research.

Implement at no additional cost to researchers or subscribing institutions the STM sample clause for non-commercial text and data mining into existing agreements (on request or as part of subscription renewal), OR to offer researchers and institutions to which researchers are affiliated comparable and equivalent access rights for non-commercial text and data mining of subscribed journal content for non-commercial scientific research

• Commitment 2: Developing the Mine-ability of Content. Find the best methods to use and enable existing proprietary electronic infrastructure to facilitate text and data mining, taking into account available resources and technology for content migration and formatting, and market demand in the different academic disciplines.

• Commitment 3: Developing the Platforms. Find solutions for researchers resident at “European non-commercial institutions holding relevant subscriptions” to integrate subscribed journal content and open access licensed content for text and data mining through suitable technical applications and infrastructure, such as CrossRef Prospect.

TDM: STM Declaration (Nov. 2013)

* Sample clauses at http://www.stm-assoc.org/2012_03_15_Sample_Licence_Text_Data_Mining.pdf

TDM: CrossRef

Added two software components free for use by researchers and the public to address text and data mining the scholarly literature across multiple publishers

• The “TDM Common API” to access the full text of content identified by CrossRef DOIs across publisher sites and regardless of their business models

• The “License Registry” can (optionally) be used by researchers and publishers as an efficient mechanism to provide “click-through” agreement of proprietary TDM licenses

https://prospect.crossref.org/

Elsevier’s New Text and Data Mining Policy

“Researchers at academic institutions can text mine subscribed content on ScienceDirect for non-commercial purposes via the ScienceDirect APIs.”

“Access is granted to faculty, researchers, staff and students at the subscribing institution.”

Text mining output can be shared publically under these conditions1. May contain "snippets" of up to 200 characters of the original text2. Proprietary notice3. Must include DOI link to original content4. Researchers must sign a click-through agreement

http://www.elsevier.com/tdm

Open access content: text and Data mining permission are determined by the author's choice of user license as detailed in the individual articles

• External distribution may include a few lines of “query-dependent text of individual full text articles or book chapters,” to a maximum length of 200 characters surrounding and excluding the text entity matched (“snippets”) or bibliographic metadata.

• Snippets and/or bibliographic metadata should be accompanied by a DOI link pointing back to the individual full text article or book chapter.

• Researchers should clear with the relevant copyright owner and/or rights holder the rights for reuse of any images.

• Include the following proprietary notice:“Some rights reserved. This work permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.”

Elsevier Requirements Calif. Digital Library ResponseSlightly improved Elsevier’s language

• The Elsevier API was acceptable as long as the language of the agreement did not explicitly restrict researchers to use the Elsevier API as the only possible method of TDM

• CDL was not able to get Elsevier explicitly to authorize other forms of TDM)

• Rejected the 200-character text limit as unacceptable and would not bind their users to terms that required all downstream uses to be non-commercial

• CDL did agree that its own authorized users’ uses should be non-commercial

• May have been able to mitigate language relating to a click-through agreement for use of the API

• note: this point is yet to be confirmed

Regardless of the publisher/vendor, your consortium should negotiate these provisions!

TDM: remember the eifl model licences!Institutional licence: Journals – Paying Countries

Note: currently the eifl model institutional licence for journals for countries with free access includes no clause regarding TDM

Institutional licence: Datasets & E-book Subscriptions – Paying Countries

3.1.8.9 use of the Licensed Material and Modifications to perform and engage in text mining/data mining activities for academic research and other Educational Purposes and allow Authorised Users to mount, load and integrate the results on a Secure Network and use the results in accordance with this Licence.

Institutional licence: Purchased E-books

Journal Inflation & Open Access: Closing Pandora’s Box?A Case Study: Elsevier & the Netherlands Universities

• Negotiations between Dutch universities and Elsevier on subscription fees and Open Access “ground to a halt”

• Elsevier’s most recent response was unacceptable, and the universities hope that Elsevier will submit an amended proposal

• The universities are informing their researchers about the consequences of this deadlock

• The universities will not renew “Big Deal” agreements if publishers, including Elsevier, take meaningful steps towards Open Accesso The universities assert that Open Access publications are easier to find, more frequently quoted,

and capable of reaching a larger audience o The Dutch Secretary for Education, Culture and Science stated that within 5-10 years, 60% -

100% of all Dutch academic publications should be Open Access

• Negotiations with publishers other than Elsevier have shown that the parties do succeed in moving towards Open Access

Source: Press Release – 4 November 2014

E-books: Library/PublisherTensions

• Too many unique tech platforms with different interfaces• Downloading possibilities vary considerably (if available at all)• Copies of e-books often cannot be retained in local files (as can be done

with journal articles, which can then be marked up and commented upon by the reader)

• There are few (if any) effective consortial purchasing and lending models

• Publishers unwilling to take risks on pricing models (shared purchases, unlimited use, etc.)

• Adobe DRM books (ePub) tracked usage in unencrypted and open files

E-books: procurement• Short-term loans (STL) & demand driven acquisitions (DDA)o Publishers are pulling away from or increasing costs of STL as they

believe they threaten their revenue streamso The average cost per book increased dramatically (66% in a

LYRASIS study) over one yearo Biggest increases by Taylor & Francis, Cambridge & Wiley

o STLs seem to threaten DDA acquisitions

discovery layers: democratizing access• Discovery layers (e.g., EBSCO EDS) are makes open access and licensed

content become indistinguishable – which is a good thing!

• Budapest Open Access Initiative is nearing its 15th anniversaryo has the OA promise to disrupt the purchased licensing model been

fulfilled? What were the unintended positive consequences?

measuring content value: altmetricsMeasure impacts from social media to quantify reader engagement with scholarly literature by collecting data from• Twitter, Facebook, LinkedIn, and Academia.edu activity• Number of “Saves” in online reference managers (e.g., Mendeley, CiteULike)• Scholarly and popular blog interest and activity• Data and software use & reuse (GitHub, FigShare)• Slide presentation views and downloads (SlideShare)

Platforms • Non-profit: ImpactStory – designed for the individual researcher, tools to visualize impact of research

products. Helps “researchers to tell data-driven stories about their impacts.” “Featured and funded by BBC, nature, the Chronicle of Higher Education, JISC, Alfred P. Sloan Foundation, National Science Foundation.

• Commercial:o Altmetric.com: provide article level metrics (owned by Macmillan)o Mendeley.com: collects and displays altmetrics (owned by Elsevier)o Plum Analytics: article-level data to compare individuals, departments, universities (owned by EBSCO)

http://www.acrl.ala.org/value/?p=688

Example: Impactstory.org

Example: Impactstory.org

Map view Use of Slide Decks

OA, licensed, free = its all content!

• OA: a sustainable path to disrupt licensed content model?

• The future of the library as publisher / repository• Digitized special collections• Born digital new publications • Platforms: Fedora Hydra, etc.

Contact InformationArnold Hirshon

Associate & University LibrarianCase Western Reserve University

Cleveland, OH USA

arnold.Hirshon@case.edu

Twitter: ahirshonSkype: ahirshon