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Walk Before You Run
Prerequisites to Linked DataKenning Arlitsch
Dean of the Library@kenning_msu
Linked Data applications will not matter if search engines can’t find library websites and repositories, crawl them, and understand the metadata provided.
First, Take Care of Basics
AgendaTraditional SEO (Search Engine Optimization)– Hardware, software, websites, metadata
Semantic Web Optimization– Semantic Identity– Schema.org Project 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
DeRosa, Cathy, et al. “Perceptions of Libraries, 2010: Context and Community: A
Report to the OCLC Membership”, OCLC, 2010.
Where College Students Begin Research - 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%)
How much of that traffic is directed to our libraries?
Need more reasons?
Our Research Inspiration• Decade building digital libraries - Univ of Utah– Mountain West Digital Library– Utah Digital Newspapers– Western Waters Digital Library– Western Soundscape Archive
• Were they being used…?
Uh, not really…
• 2010 situation at Utah– 12% of digital collections indexed by Google– 0.5% of Utah’s IR scholarly papers accessible via
Google Scholar
Basic SEO began producing significant increases in the average number of page views per day…
Avg. Page Views / Day content.lib.utah.edu
Basic SEO improved Utah’s collection accessibility in Google…
Average
0% 25% 50% 75% 100%
92%
79%
51%
12%
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)
…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
Nearly 100% USpace IR content indexed in Google
Google Index Ratio
Board of Regents
UScholar Works
ETD 2
ETD 1
0% 25% 50% 75% 100%
97%
98%
98%
97%
47%
51%
68%
69%
4%
23%
0%
12%07/05/1011/19/1010/16/11
Google Scholar Index Ratio
~0%*October 16, 2011 Weighted Average Google Index Ratio = 97.82% (10,306/10,536).
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
SEO 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
Recommended SEO Process1. Institutionalize SEO
● Strategic Planning● Accurate Measurement Tools
2. Traditional SEO● Get Indexed = Index Ratio● Get Visible = Search Engine Results Page (SERP)
Advanced SEO Programs3. Semantic SEO
● Get Relevant = Click Through Ratios (CTR)● Semantic Identity● Schema.org for Libraries● Linked Open Data (LOD)
4. Social Media Optimization● Faculty Outreach
SEMANTIC IDENTITY
For Accurate Representation on the Web
12/09/2014
Current SituationAcademic organizations are poorly represented on the Semantic Web…
…because search engines don’t understand them…
…because we don’t maintain the data sources search engines trust.
Affects reputation of the entire academic institution
Colleges
Departments Centers Institutes
Institutional reputation
Researcher collaboration/employment
Research funding
University rankings
Student enrollment
Manage Risk
Google’s Knowledge Graph
The Web is moving from “strings” to “things”
“A knowledge base … to enhance search results with semantic-search information gathered from a wide variety of sources”
Source: Wikipedia
Knowledge Graph Products• Answer Box– Facts about concepts
• Carousel– Group of instances that comprise a concept
• Knowledge Card– Displays information about organizations and
people
Lack of a Knowledge Card in search results is indicative of a larger problem…
…and as a result Google is unlikely to connect users with the organization’s website
…it means Google doesn’t understand that the organization exists or what its business is…
Survey of ARL Libraries• n=125• Searched by name listed in ARL directory• Knowledge Card? Yes/No• Robustness scale of 1-5
Survey of ARL LibrariesNo Knowledge Card at all
43Have Knowledge Card
82 -10 incorrect
-29 (robustness of 1)Total = 43
Google’s Perception of MSU Lib - 2012
MSU Library - 2014
Where does Google get its information?
Trusted Sources for Search Engines• No Wikipedia presence? – Organization doesn’t exist as an “entity” or “thing”– It exists as a string of (confusing) text
• Other influences on Google’s Knowledge Graph– FreeBase (phasing out in favor of Wikidata)– Google Places/Google My Business– Google+
Wikipedia - 2012
DBPedia entry - 2012
2014 DBpedia entry
MSU COLLEGES
MSU CENTERS AND INSTITUTES
Summary• Define library organization in Wikipedia– Beware of *pedia culture and process
• Engage with other trusted data sources– Wikidata– Google Places/Google My Business– Google+
• Mark-up metadata with Schema.org
New Knowledge Work for Libraries• Build set of replicable services– Populate and maintain structured data records– Add rich semantic markup to websites
• Communicate– Understand ourselves from stakeholder perspective– Machine-understandable information
SCHEMA.ORG PROJECTPart 3 of 3
57
Schema.org • Common vocabulary for describing things on 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
Hypothesis• Implementing Schema.org in library websites– Improves machine understanding of content– Improves rich snippets shown in SERP– Increases click-through rates from SERP
• Result– More traffic– More users finding what they’re looking for
Project: 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• 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
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.