niso two part webinar: is granularity the next discovery frontier? part 1: supporting direct...

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NISO Two Part Webinar: Is Granularity the Next Discovery Frontier? Part 1: Supporting Direct Access to Increasingly Granular Chunks of Content Wednesday, March 11, 2015 Speakers: Myung-Ja (MJ) Han, Metadata Librarian, University of Illinois at Urbana-Champaign Urbana Tito Sierra, Director of Product Management, EBSCO Information Services Daniel Mayer, Vice President of Product & Marketing, TEMIS http://www.niso.org/news/events/2015/webinars/granularity_pt1/

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NISO Two Part Webinar: Is Granularity the Next Discovery Frontier?

Part 1: Supporting Direct Access to Increasingly Granular Chunks of Content

Wednesday, March 11, 2015

Speakers:

Myung-Ja (MJ) Han, Metadata Librarian, University of Illinois at Urbana-Champaign Urbana

Tito Sierra, Director of Product Management, EBSCO Information Services

Daniel Mayer, Vice President of Product & Marketing, TEMIS

http://www.niso.org/news/events/2015/webinars/granularity_pt1/

Metadata with Levels of Description

Myung-Ja (MJ) HanMetadata Librarian

University of Illinois at Urbana-Champaign

23/11/2015NISO Webinar on Supporting Direct Access to Increasingly Granular Chunks of Content

Metadata is …

Prime sources of information to:

• Organize

• Manage

• Provide access to resources

• Preserve library resources

Access and Management

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00667cam a2200229Ii 4500001000800000005001700008008004100025035002300066040002300089035001300112035001600125090002200141049000900163100003500172245010800207260003800315300001900353500003200372910001200404994001200416910000900428262410820030807121329.0900530s1841 enk 000 1 eng d a(OCoLC)ocm03535290 aSUCcSUCdOCLdUIU 9ARY-4606 9UC 12037257 aPR4058b.S65 1841 aUIUU1 aIngoldsby, Thomas,d1788-1845.10aSome account of my cousin Nicholas /cby Tomas Igoldsby, esq. ; to which is added, The rubber of life. aLondon :bRichard Bentley,c1841. a3 v. ;c19 cm. aFirst edition. Sadleir 157. arcp3356 a02bUIU aMARS

Localized card cataloging

Library of Congress’card service

MARC

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MARC

• MARC Format Record

- has been a cataloging tool in the library community since the 1960’s

- has more than 1,900 fields

- has made libraries move towards the Computer Age (Tennant, 2004)

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Changes - Environments

• Libraries have lost their place as primary information providers (Coyle & Hillmann, 2007)

• Users’ search behaviors have changed

• Printed book is no longer the only major vehicle for scholarly communication (Sandler, 2005)

• Increase in diverse formats/web-based information resources

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Changes - Metadata

• Metadata - contains more than descriptive information

- is harvested and converted

- is provided by vendors and others

- is enhanced by users

- should support discovery service

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“Virtually any content we digitize and make available to our clientele requires metadata for

discovery and access.”

(Tennant, 2002, p. 32)

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Metadata Should be created in

different levels of granularity

to support granular levels of access!

3/11/2015

NISO Webinar on Supporting Direct

Access to Increasingly Granular Chunks

of Content

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Different Levels of Access

• Volume on a shelf

• Chapter of a book

• Article of a journal issue

• Special unit of a book

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Different Levels of Metadata

• Book/Journal title

• Chapter

• Article

• Special unit of a book

• And more…

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Granularity of Metadata I

• Emerging needs

– Meet users’ needs to find and use resources

– Support the library’s discovery services

– Increase interest and development of digital humanities

Need granular levels of metadata!

3/11/2015NISO Webinar on Supporting Direct Access to Increasingly Granular Chunks of Content

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3/11/2015NISO Webinar on Supporting Direct Access to Increasingly Granular Chunks of Content

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?

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Riley, Jennifer. (2010).“Seeing Standards: A Visualization of the Metadata Universe.”

http://www.dlib.indiana.edu/~jenlrile/metadatamap/

Granularity of Elements• MARC

100 1 _ $a Last name, First name. $d 1111-1222, $e role. • TEI

<name type="person">First name and Last name</name> or, <author>Last name, First name.</author>

• Dublin Core<dc:creator>Last name, First name. Date. </dc:creator>

• MODS<name type=”personal”>

<namePart type=”given”>Last name</namePart><namePart type=”family”>First name </namePart><role>

<roleTerm type=”code”authority=”marcrelator”>aut</roleTerm>

<roleTerm type=”text”authority=”marcrelator”>author</roleTerm>

</role></name>

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of Content

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<dc:title>1818-1918, a hundred years of Sunday school history in Illinois; a mosaic.</dc:title><dc:creator>Mills, Andrew H.,1851- </dc:creator><dc:type>text</dc:type><dc:publisher>Decatur, Ill., The author</dc:publisher><dc:date>[1918?]</dc:date><dc:language>eng</dc:language><dc:subject>International Sunday school association.</dc:subject><dc:subject>Sunday schools</dc:subject><dc:relation/><dc:identifier>http://www.archive.org/details/18181918hundredy00mill</dc:identifier>

<mods:mods><mods:titleInfo>

<mods:title>1818-1918, a hundred years of Sunday school history in Illinois..</mods:title></mods:titleInfo><mods:name><namePart type="given">Andrew H.</namePart>

<namePart type="family">Mills</namePart><namePart type="date">1851- </namePart>

<mods:role><mods:roleTerm mods:type="text">author</mods:roleTerm>

</mods:role></mods:name>

…..</mods:mods>

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Extensibility of Element

“Schemas allow users to extend the

elements set to meet the local use.”

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Granularity of Values

How to add subject headings?

•20% rule

•Rule of three

•Rule of four

Does this serve well in resource discovery and retrieval in the digital age?

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Granularity of Metadata II

• Creating/extending metadata schemas

– *Assess the granularity of access points

– *Develop a new set of elements (Application profile)

– Identify available semantics

– Create a new metadata schema • (Application Profile)

*Metadata record creation

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3/11/2015NISO Webinar on Supporting Direct Access to Increasingly Granular Chunks of Content

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3/11/2015NISO Webinar on Supporting Direct Access to Increasingly Granular Chunks of Content

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Book Emblem Pictura

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of Content

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3/11/2015

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<biblioDesc> <mods>

<mods:titleInfo> <mods:title>XL [i.e. Quadraginta] emblemata miscella nova </mods:title>

</mods:titleInfo> <mods:physicalDescription>

<mods:digitalOrigin>reformatted digital</mods:digitalOrigin> <mods:form authority="marcform">print</mods:form> <mods:extent>[8], xxxx p. : 41 ill. ; 20 cm.</mods:extent>

</mods:physicalDescription> ... </mods>

3/11/2015NISO Webinar on Supporting Direct Access to Increasingly Granular Chunks of Content

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<copyDesc> <copyID>uiu2895515</copyID>

<owner countryCode="US">University of Illinois</owner> <digDesc comp="complete" scope="all"

xml:id="xliequadragintae00mure" globalID=http://hdl.handle.net/10111/UIUCOCA:xliequadragintae00mure>

<copyID>10111/UIUCOCA:xliequadragintae00mure</copyID> <owner countryCode="US">University of Illinois</owner>

</digDesc> …

</copyDesc>

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<emblem xmlns:rdf=http://… xmlns:skos=http://…xml:id="E000944" citeNo="I." globalID="http://... :E000944">

<motto><transcription xml:lang="de"> Alchimisterey: <normalisation>xml:lang="de">Alchemie:</normalisation></transcription>

</motto> <pictura xml:id="E000944_P1">

<iconclass rdf:about="http://www.iconclass.org/rkd/31A247"> <skos:notation>31A247</skos:notation> <skos:prefLabel>looking over the shoulder</skos:prefLabel>

</iconclass> …

</picture> </emblem>

</biblioDesc>

3/11/2015

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Metadata

• Involves designing data model

• Is a highly collaborative effort

– Scholars/users

– Domain specialists

– Metadata/Cataloging librarian(Cole, Han, and Vannoy, 2012)

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New MetadataSchema

Catalogers/Metadata Librarians

Users

Domain Specialists

New discovery services

Images• Building Blocks (Attribution-ShareAlike 2.0 Generic (CC BY-SA

2.0))http://www.flickr.com/photos/bdesham/2432400623/• Lego Parts (Attribution-NonCommercial-NoDerivs 2.0

Generic (CC BY-NC-ND 2.0))http://www.flickr.com/photos/starstreak007/3882987034/in/ph

otostream/• Lego Pencil and Notebook (Attribution-NonCommercial-

NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))http://www.flickr.com/photos/starstreak007/3882191947/in/ph

otostream/

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References

• Coyle, K., & Hillmann, D. (2007). Resource Description and Access (RDA). D-Lib Magazine, 13(1/2). doi:10.1045/january2007-coyle

• Cole, T. W., Han, M-J, & Vannoy, J. (2012). Descriptive Metadata, Iconclass, and Digitized Emblem Literature." Proceedings of the12th Annual Joint Conference on Digital Libraries. New York: Association for Computing Machinery. 111-120.

• Sandler, M. (2005). Disruptive Beneficence, Internet Reference Services Quarterly, 10(3-4), 5-22.

• Tennant, R. (2002). The Importance of Being Granular. Library Journal, 127(9), 32.

• Tennant, R. (2004). A Bibliographic Metadata Infrastructure for the Twenty-First Century. Library Hi Tech, 22(2), 175-181.

3/11/2015NISO Webinar on Supporting Direct Access to Increasingly Granular Chunks of Content

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Is Granularity the Next

Discovery Frontier?

Granular Discovery: User

Challenges and Opportunities

Tito Sierra

Director of Product Management, Search

EBSCO Information Services

EBSCO Discovery Service

Agenda

• The Evolution of Library Discovery

• Discovery in the Age of Google

• Metadata and Granular Discovery

– Metadata-centered approaches

– User-centered approaches

• Concluding Thoughts

EBSCO Discovery Service

The Evolution of Library Discovery

EBSCO Discovery Service

The Evolution of Library Discovery

Library search has come a long way

• OPACs

• Online Research Databases

• Federated Search

• Next Generation Catalogs

• Web-scale Discovery Services

EBSCO Discovery Service

The Evolution of Library Discovery

From siloed discovery to unified discovery

• Articles / e-journal content

• Print collection (catalog)

• E-books

• Magazines / trade publications / news sources

• General reference / specialized reference

• Multimedia (images, audio, videos)

EBSCO Discovery Service

The Evolution of Library Discovery

Supporting a variety of discovery needs

• Known-item book and article citation search

• Exploratory search / topic exploration

• Discipline-specific research / literature reviews

• Curriculum support / course assignments

• General reference / specialized reference

• Specialized content discovery

EBSCO Discovery Service

Discovery in the Age of Google

EBSCO Discovery Service

User Expectations for Search

EBSCO Discovery Service

User Expectations for Search

Shaped by popular search engines

• Support basic keyword search

• Deep content coverage

– Diverse content types

– Diverse content sources

• Predictive relevance ranking

• Intelligent search features

– Autocomplete, Did-you-mean

EBSCO Discovery Service

Findings from EDS User Research

Observation Implication

Keyword search most

common

Discovery service cannot assume users will pre-

coordinate their search. Discovery service needs to

anticipate user intent based on limited input.

Faceted search used

sparingly

Discovery service cannot assume users will post-

coordinate their search. Discovery service needs to

provide more user-friendly narrowing options.

Search queries length

often short (1-2 words)

Discovery service needs to anticipate user intent

based on limited input. Search features needed to

help users clarity their search intent.

Broad and imprecise

queries common

Discovery service needs to help users narrow their

search based on limited input. Many users looking for

a topical overview on a subject.

User focus on top

results

Relevance ranking crucial for delivering a quality

search experience. Need to optimize search to display

most relevant results on first page.

EBSCO Discovery Service

The Discovery Service Challenge

Despite major evolutions in library search,

libraries, publishers, and discovery service

providers need to work harder to meet

evolving user expectations for search.

EBSCO Discovery Service

The Discovery Service Advantage

One advantage that library discovery

services have over general purpose

search engines is access to high-quality,

well structured metadata.

EBSCO Discovery Service

Metadata and Granular Discovery

EBSCO Discovery Service

Metadata, Metadata, Metadata

EBSCO Discovery Service

Metadata, Metadata, Metadata

EBSCO Discovery Service

Metadata, Metadata, Metadata

EBSCO Discovery Service

Metadata, Metadata, Metadata

• Citation metadata– Title, Authors, Publication Date, Volume, Issue…

• Descriptive metadata– Publication Type, Document Type, Subject Terms,

Abstract, Author-supplied keywords, Lexile level…

• Source metadata– Publisher, Content Provider, Database…

• Identifiers– ISBN, ISSN, LCCN, Call Number…

EBSCO Discovery Service

Metadata-centered Approaches to

Granular Discovery

Advanced Search

Advanced Search

Advanced search options: Single fielded search

Title

Author

Subject Terms

Multi-fielded search

Search modes

Boolean/Phrase

Find all search terms

Find any search terms

Search limiters

Full Text

Scholarly Journals

Catalog Only

Language

Faceted Search

Faceted Search

EBSCO Discovery Service

Faceted Search

EBSCO Discovery Service

Metadata-centered Approaches

Advanced Search and Faceted Search are

powerful tools—for those who know how

to effectively use them.

They require user to translate discovery

need into the language of metadata.

Consequently they are underutilized.

EBSCO Discovery Service

User-centered Approaches to

Granular Discovery

EBSCO Discovery Service

User-centered Approaches

Anticipate end user intent using clues from

the user query and user context.

Deliver targeted content at the top of the

results list where users expect.

Research Starters

Topic overviews for broad

topical queries.

Publication Title Placard (Beta)

Journal name searched,

exact match found.

Publication match based

on customer’s holdings.

EBSCO Discovery Service

Concluding Thoughts

EBSCO Discovery Service

Metadata Necessary But Insufficient

Supporting access to increasingly granular

chunks of content will requires capture and

management of finer-grained metadata.

Metadata needs to be coupled with search

intelligence to have a broad impact.

EBSCO Discovery Service

Areas for Future Investment

• Deepen analysis of usage data to better

understand user context and expressed

granular discovery needs

• Develop intelligent bridging between user

queries and granular metadata

• Build in adaptive learning capabilities to

automatically refine intelligent search

approaches over time

EBSCO Discovery Service

Discussion / Q&A

From Unstructured Contentto Granular Insights

Daniel MayerVP Product & [email protected]

Copyright © 2012 TEMIS - All Rights Reserved - Slide 65

Pioneer of Textual Big Data since 2000

• 20 languages

• In production for 12 years

• 8 Billion+ pages processed

70

26

Copyright © 2012 TEMIS - All Rights Reserved - Slide 66

Key customers in the Information IndustrySTM, Legal, B2B, Trade, Media, Public

Copyright © 2012 TEMIS - All Rights Reserved - Slide 67

Textual Big DataChallenge

• News• Market Studies• Economic Data• Financial Publications• Scientific Literature• Patents• Books• Conference Proceedings• Clinical Research• Patient Health Records• Regulations• Legal Decisions• Customer Emails• Tweets• Blog posts

+50%Per year

Copyright © 2012 TEMIS - All Rights Reserved - Slide 68

• Save timewith quick & easy accessto the most relevant

• Improve your insightinto your interest area

• Take better decisions

Textual Big DataOpportunities

Copyright © 2012 TEMIS - All Rights Reserved - Slide 69

Textual Big DataHow to seize these opportunities ?

by adding structure

• Save timewith quick & easy accessto the most relevant

• Improve your insightinto your interest area

• Take better decisions

Copyright © 2012 TEMIS - All Rights Reserved - Slide 70

How do you structure ?

We report a 52 year-old man presenting an acute hair loss induced by carbamazepine (CBZ) in concentration of 8.6 microg/ml.

By extracting granular & domain-specific information

Relations

We report a 52 year-old man presenting an acute hair loss induced by carbamazepine (CBZ) in concentration of 8.6 microg/ml.

Verb Patient Verb Symptom Verb Dosage informationSubj

Entities

Drug Name

Terms

Pro Verb NumArt N-P Noun Verb Art Adj Nn Nn Verb Pp PropNn Pp Noun Pp Num UnitAbbr

Attributes

Roles

Adverse EventSide Effect Alopecia

Cause Carbamazepine

Dosage 8.6 mg/ml

Patient 52 year old male

Copyright © 2012 TEMIS - All Rights Reserved - Slide 71

A case of hair loss induced by carbamazepine

Kohno Y, Ishii A, Shoji S, Department of Clinical Neurology, Tsukuba University.

We report a 52 year-old man presenting with an acute considerable hair loss induced by carbamazepine (CBZ). The remarkable scalp hair loss started within a week after CBZ administration. There was no evidence of dermatitis or allergic reaction, or other cause for the hair loss. The serum concentration of CBZ was 8.6 microg/ml therapeutic range 8-12 microg/ml). CBZ was discontinued, and the hair loss stopped within several days with new hair growth. Medication-induced hair loss is an occasional adverse effect of many drugs used for neuropsychological diseases. CBZ also induces hair loss and its frequency was reported below 2%. Only a limited number of detailed case reports describing CBZ-induced hair loss were available, and we found these cases could divide into two groups with regard to a delay in starting hair loss after administration of CBZ. In one group, the hair loss started within a week suggesting anagen effluvium and in another it started after two or three months suggesting telogen effluvium. This finding suggests the causative mechanism of CBZ-induced hair loss is not unitary.

Neuropsychological diseasesDiseases

8.6 microg./mlDosage information

8-12 microg./ml

man52 year oldPatient information

Dept of Clinical Neurology, Tsukuba UniversityOrganizations

Kohno Y Ishii A Shoji SPeople

Carbamazepine CBZ

Drugs

Alopecia Dermatitis Allergic reaction

Anagen effluvium Telogen effluvium

Symptoms

How does this help ?Enrich document metadata

Side-effect Relationships

Drug-induced alopecia

A case of hair loss induced by carbamazepine

Kohno Y, Ishii A, Shoji S, Department of Clinical Neurology, Tsukuba University.

We report a 52 year-old man presenting with an acute considerable hair loss induced by carbamazepine (CBZ). The remarkable scalp hair loss started within a week after CBZ administration. There was no evidence of dermatitis or allergic reaction, or other cause for the hair loss. The serum concentration of CBZ was 8.6 microg/ml therapeutic range 8-12 microg/ml). CBZ was discontinued, and the hair loss stopped within several days with new hair growth. Medication-induced hair loss is an occasional adverse effect of many drugs used for neuropsychological diseases. CBZ also induces hair loss and its frequency was reported below 2%. Only a limited number of detailed case reports describing CBZ-induced hair loss were available, and we found these cases could divide into two groups with regard to a delay in starting hair loss after administration of CBZ. In one group, the hair loss started within a week suggesting anagen effluvium and in another it started after two or three months suggesting telogen effluvium. This finding suggests the causative mechanism of CBZ-induced hair loss is not unitary.

Copyright © 2012 TEMIS - All Rights Reserved - Slide 72

Extraction

Luxid® Annotation

Server

How does this help ?Exploiting enriched metadata

Metadata / Triples

Copyright © 2012 TEMIS - All Rights Reserved - Slide 73

SearchEngine

IndexDe

RechercheIndex

IndexingExtraction

Luxid® Annotation

Server

How does this help ?Exploiting enriched metadata

Metadata / Triples

Copyright © 2012 TEMIS - All Rights Reserved - Slide 74

Applications

SearchAnalysis

VisualizationFacets

Recommendations

PortalsTopic Pages

DecisionSupport

SearchEngine

IndexDe

RechercheIndex

IndexingExtraction

Luxid® Annotation

Server

How does this help ?Exploiting enriched metadata

Metadata / Triples

Linked DataKnowledge Bases

Copyright © 2012 TEMIS - All Rights Reserved - Slide 75

Examples

Copyright © 2012 TEMIS - All Rights Reserved - Slide 76Facetted search/navigation

Copyright © 2012 TEMIS - All Rights Reserved - Slide 77

Sources/Content Types

Scan Types

Anatomical Regions

Pathologies / Indications

Facetted search/navigation

Copyright © 2012 TEMIS - All Rights Reserved - Slide 78Facetted search/navigation

Copyright © 2012 TEMIS - All Rights Reserved - Slide 79

Nature of the offense

Nature of the sentence

Numerical data regarding the sentence

Numerical Dataregarding the context

Facetted search/navigation

Copyright © 2012 TEMIS - All Rights Reserved - Slide 80

……

Semantic Shortcuts

Copyright © 2012 TEMIS - All Rights Reserved - Slide 81

CorrespondingScans & Illustrations

Differential DiagnosisSupport

Relevant Content

Topic Page

Copyright © 2012 TEMIS - All Rights Reserved - Slide 82Copyright © 2009 TEMIS - All Rights Reserved - Slide 82

Topic Page

Copyright © 2012 TEMIS - All Rights Reserved - Slide 83Topical Feed

Copyright © 2012 TEMIS - All Rights Reserved - Slide 84Topic Page

Copyright © 2012 TEMIS - All Rights Reserved - Slide 85Smart Snippets

Copyright © 2012 TEMIS - All Rights Reserved - Slide 86

Semantic AnalyticsCompetitive Intelligence - Product/Supplier map

Analytics

Copyright © 2012 TEMIS - All Rights Reserved - Slide 87

Semantic Analytics

Analytics – Corporate Relationships

Copyright © 2012 TEMIS - All Rights Reserved - Slide 88

Semantic Analytics

Analytics – Staff Map

Copyright © 2012 TEMIS - All Rights Reserved - Slide 89Delivery in the workflow

Thank YouYour Questions

Daniel MayerVP Product & [email protected]

NISO Webinar • March 11, 2015

Questions?All questions will be posted with presenter answers on

the NISO website following the webinar:

http://www.niso.org/news/events/2015/webinars/granularity_pt1/

NISO Two-Part Webinar

Is Granularity the Next Discovery Frontier?

Part 1: Supporting Direct Access to Increasingly Granular

Chunks of Content

Thank you for joining us today.

Please take a moment to fill out the brief online survey.

We look forward to hearing from you!

THANK YOU