Walk Before You Run

Prerequisites to Linked Data

Kenning ArlitschDean of the Library

@kenning_msu

Linked Data applications will not matter if search engines can’t first find library websites and repositories, crawl them, and understand the metadata provided.

First, Take Care of Basics

Agenda

Traditional SEO (Search Engine Optimization)– Optimize hardware, software, websites, metadata

Semantic Web Optimization– Semantic Identity– Schema.org Projects at MSU

• Using a vocabulary understood by search engines• Improve machine comprehension

Funded Research

• 2011-2014– “Getting Found: Search Engine Optimization for

Digital Repositories”• 2014-2017

– “Measuring Up: Assessing Accuracy of Reported Use and Impact of Digital Repositories

– Partners• OCLC Research• Association of Research Libraries• University of New Mexico

SEARCH ENGINE OPTIMIZATIONPart 1 of 3

SEO Building Blocks

• Priority 1 – Increase Reach– Get objects indexed by search engines

• Priority 2 – Increase Visibility in SERP– Provide robust descriptive content

• Priority 3 – Get Relevant– Increase click-through rates (CTR)

Why it Matters

Where College Students Begin Research

2005 2010

DeRosa, Cathy, et al. “Perceptions of Libraries, 2010: Context and Community: A Report to the OCLC Membership”, OCLC, 2010.

* http://www.comscore.com/Insights/Market-Rankings/comScore-Releases-November-2014-U.S.-Desktop-Search-Engine-Rankings

Americans submit 18 billion search queries to search engines each month*• 12 billion to Google sites (67%)• 3.5 billion to Microsoft sites (19%)• 1.8 billion to Yahoo! Sites (10%)• 355 million to Ask Networks (.02%)• 224 million to AOL, Inc. (.01%)How much of that traffic is directed to our libraries?

Need more reasons?

Our Research Inspiration

• Ten years building digital libraries– Mountain West Digital Library– Utah Digital Newspapers– Western Waters Digital Library– Western Soundscape Archive

• Were they being used?

Basic SEO improved Utah’s collection accessibility in Google…

92%

79%

51%

12%

0% 25% 50% 75% 100%

Average

07/05/10 04/04/11 11/30/11 12/05/13

Google Index Ratio - All Collections*

• Google Index Ratio = URLs submitted / URLs Indexed by Google• ~150 collections containing ~170,00 URLs (07/2010) and ~170 collections containing ~282,000 URLs (12/2013)

...Producing significant increases in the average number of page views per day…

Avg. Page Views / Day content.lib.utah.edu

…resulting in more referrals and visitors

12 week comparison 2010 vs. 2012

Technical Barriers to SE Crawlers

• Website Design – Graphics– Confusing site hierarchies and paths

• Slow servers• CMS often lack canonical links• Metadata

– Schema not understood by SE– Not unique– Inconsistent/inaccurate

Challenge is presenting structured data SE’s can identify, parse and digest

Wolfinger, N. H., & McKeever, M. (2006, July). Thanks for nothing: changes in income and labor force participation for never-married mothers since 1982. In 101st American Sociological Association (ASA) Annual Meeting; 2006 Aug 11-14; Montreal, Canada (No. 2006-07-04, pp. 1-42). Institute of Public & International Affairs (IPIA), University of Utah.

Human Readable

Google ScholarUnderstandable

Google Scholar can read and understand!Google Scholar

Organizational/Cultural Themes

• Traditional SEO is an afterthought• Librarians think too small re potential traffic• Organizational communication is poor• Analytics are usually poorly implemented• Vendors are slow to catch on to SEO problems

– Because we don’t demand it

How does a library justify SEO?

• Promote use of collections• Accountability to funding organizations• Improve institutional reputation

– Increase citation rates– Attract research funding– Attract students and faculty

Recommended SEO Process

• Institutionalize SEO– Strategic Plan/driven by administration– Accurate Measurement Tools

• Traditional SEO– Get Indexed = Index Ratio– Get Visible = Search Engine Results Page (SERP)

• Semantic Web Optimization– Get Relevant = Click Through Rates (CTR)

SEMANTIC WEB OPTIMIZATIONPart 2 of 3

Semantic Identity

Library organizations are poorly defined and represented on the Semantic Web…

Google’s Knowledge Graph

“A knowledge base … to enhance search results with semantic-search information gathered from a wide variety of sources”

Source: Wikipedia

Google’s Perception of MSU Lib - 2012

Where does Google get its information?

Trusted Sources for Search Engines

• No Wikipedia presence? – You don’t exist as an important “entity” or “thing”– You exist as a string of (confusing) text

• Other influences on the Knowledge Graph– FreeBase (phasing out)– Wikidata– Google Places/Google My Business– Google+

Wikipedia - 2012

DBPedia entry - 2012

2014 DBpedia entry

Remember, this was 2012

MSU Library - 2014

TWO MSU SCHEMA.ORG PROJECTSPart 3 of 3

Schema.org

• Common vocabulary for describing things on the web

• Supported by Bing, Google, Yahoo and Yandex• “On-page markup helps search engines

understand the information on webpages and provide richer results.”

• https://support.google.com/webmasters/answer/1211158?hl=en

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Hypothesis

• Implementing Schema.org will– Improve machine understanding of content– Improve rich snippets shown in SERP– Increase click-through rates from SERP

– More traffic– More users finding what they’re looking for

Project 1: A Controlled Experiment by Jason Clark (with Michelle Gollehon)

• Two digital collections• Similar size/content/date range

– Photos and historical documents

• 1 optimized with Schema.org (Schultz)• 1 control (Brook)

A Revised Digital Library Architecture

• Collection Page (home page)– arc.lib.montana.edu/schultz-0010/

• About Pages (about page, topics page)– arc.lib.montana.edu/schultz-0010/about.php– arc.lib.montana.edu/schultz-0010/topics.php

• Item Pages (individual record page)– arc.lib.montana.edu/schultz-0010/item/31

• Sitemap and rel=canonical work– arc.lib.montana.edu/schultz-0010/

Results

Project 2: Schema.org IR Data Model by Jeff Mixter and Patrick OBrien

• 1909 DC records from the Montana State University ScholarWorks IR– scholarworks.montana.edu

• Started with Schema.org as the base • Created an extension vocabulary using the same

mechanics and conventions used in Schema.org– It is published as RDFa– http://purl.org/montana-state/library/

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schema: http://schema.org/dcterms: http://purl.org/dc/terms/mont: http://purl.org/montana-state/library/

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Syndication of RDF data

• Loaded all 1909 RDF descriptions back into the ScholarWorks repository – Tweaked DSpace to pull and display JSON-ld data

• Newly created entities loaded into a Triple Store with a Pubby frontend – Amazon Web Services

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Google Webmaster Tools

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CTR? Not so much, yet

Semantic Web Team• Kenning Arlitsch, Dean @kenning_msu• Patrick OBrien, Semantic Web Director @sempob• Jeff Mixter, Research Associate, OCLC Research• Jason Clark, Head of Lib Informatics and Computing @jaclark• Scott Young, Digital Initiatives Librarian @hei_scott• Doralyn Rossmann, Head of Coll Development @doralyn• Jean Godby, Senior Research Associate, OCLC Research

Relevant Publications• Arlitsch, Kenning, and Patrick S. OBrien. (2013) Improving the visibility and use of digital

repositories through SEO. Chicago: ALA TechSource. ISBN-13: 978-1-55570-906-8

• Mixter, Jeff, Patrick OBrien and Kenning Arlitsch. “Describing Theses and Dissertations using Schema.org,” Proceedings of the International Conference on Dublin Core and Metadata Applications 2014, Dublin Core Metadata Initiative: 138-146.

• Arlitsch, Kenning. “Being Irrelevant: How Library Data Interchange Standards have kept us off the Internet,” Journal of Library Administration, 54, no. 7 (2014): 609-619.

• Arlitsch, Kenning, Patrick OBrien, Jason A. Clark, Scott W.H. Young and Doralyn Rossmann. “Demonstrating Library Value at Network Scale: Leveraging the Semantic Web with New Knowledge Work,” Journal of Library Administration, 54, no. 5 (2014): 413-425.

• Arlitsch, Kenning, Patrick OBrien, and Brian Rossmann. "Managing Search Engine Optimization: An Introduction for Library Administrators." Journal of Library Administration 53, no. 2-3 (2013): 177-188.

• Arlitsch, Kenning, and Patrick S. O'Brien. "Invisible institutional repositories: Addressing the low indexing ratios of IRs in Google Scholar." Library Hi Tech 30, no. 1 (2012): 60-81.