Viewing universities as landscapes of scholarship, VIVO keynote, 2017-08-04

Viewing universities as

landscapes of scholarship

Jodi Schneider

@jschneiderjschneider@pobox.com

2017-08-04

VIVO keynote

New York, NY

Heaney’s report proposes:

The information

landscape can be seen

as a contour map in

which there are

mountains, hillocks,

valleys, plains and

plateaux.

Heaney 2000, “An Analytical Model of Collections and their Catalogues"

A large general collection

of information

– say a research library –

can be seen as a

plateau, raised above

the surrounding plain.

Heaney 2000

A specialized collection

of particular importance

is like a sharp peak.

Heaney 2000flickr: pefectfutures/3299973538/

Upon a plateau there might be undulations

representing strengths and weaknesses.

Heaney 2000

Heaney 2000

The scholar surveying the

landscape is looking for

the high places. A high

point represents an area

where the potential for

gleaning desired

information by visiting that

spot (physically or by

remote means) is greater

than that of other areas.

Heaney 2000flickr: pefectfutures/3299973538/

To continue the analogy, the scholar is concerned at the initial survey to identify areas rather than specific features – to identify rainforest rather than to retrieve an analysis of the canopy fauna of the Amazon basin. This model attempts to characterise that initial part of the process of information retrieval.

Heaney 2000, “An Analytical Model of Collections and their Catalogues"

The landscape is, however, multidimensional. Where one scholar may see a peak another may see a trough. The task is to devise mapping conventions which enable scholars to read the map of the landscape fruitfully, at the appropriate level of generality or specificity.

Heaney 2000

What might the information landscape look like?

VosViewerhttp://www.vosviewer.com/

University collaboration map

What might the information landscape of a university cover?

The information landscape of the

university would have to consider

• People & Organizations

• Spaces & Places

• Activities & Resources

• Ideas

• …Maybe More?

VosViewerhttp://www.vosviewer.com/

Cardiology 2006-2010

Slice into topical landscapes

• The information landscape of a reearch

group

• … of a program

• … of a department

• … of a college

It would interlock with increasingly

larger landscapes

• The information landscape of a university

• … of a region

• … of a nation

• … of the world

Also sliced into topical landscapes

• The information landscape of a subfield

• … of a field

• … of a mega-field

VosViewerhttp://www.vosviewer.com/

Patient safety 2006-2010

How do fields differ?

Patient safety 2006-2010

Cardiology 2006-2010

Where are the opportunities in the field?

Patient safety 2006-2010

Cardiology 2006-2010

Where are the opportunities in the field?

Patient safety 2006-2010

Cardiology 2006-2010

And who is at the pinch points?

What stakeholder questions could this map help answer?

Your systems have GREAT data!

Does it provide a pathfinder for your stakeholders?

Who are YOUR stakeholders? What do they want?

Student & scholar questions

• If I want to study topic X, where should I

go?

• Where are the best holdings

(library/archive) for a given topic?

• How can I track and map research for a

literature review?

PI questions

• I want to find a collaborator who

understands topic X/paper Y. Who has co-

cited between work in my field and that?

• Who is working in topic X, either here or

somewhere I’ve been.

• Who do I know in common with person Z?

• Who at my institution has already been

funded on this grant program?

Collection & research

management questions

• What were the papers in top 10 journals

published by our people last year?

• What books have faculty published?

Strategic questions

• What are the key areas for strategic

investment?

• Is the area growing? shrinking? How will

external events impact that?

• Are there disjoint groups working in this

topic? Could and should they be bridged?

• What are this unit’s peers?

Serving stakeholders

• Scholarship is the unique business of the university.

• Stakeholders have specific questions that come from their interactions with scholarship.

• To serve stakeholders, the research information system community needs to envision what’s possible & what’s desirable for SCHOLARSHIP.

• Different roles for librarians, systems developers, repository managers, ontologists.

“the scholar is concerned at the initial survey to identify areas rather than specific features”

“enable scholars to read the map”

http://scimaps.org/mapdetail/a_chart_illustrating_124

http://scimaps.org/mapdetail/phd_thesis_map_94

http://scimaps.org/mapdetail/being_a_map_of_physi_171

What questions do YOUR stakeholders want to “read off the map”?

Needs an ECOSYTEM of data

• Not just native system data

• Not just MY institution

Data you own vs. data you get from

others

• People & Organizations

• Spaces & Places

• Activities & Resources

• Ideas

• …Maybe More?

Needs to be user-centered

• Linked Data Principles

• The Del.ici.ous lesson

Linked Data Principles

• Linked Data Principles

https://www.w3.org/DesignIssues/LinkedData.html

Linked Data Principles

• Linked Data Principles

https://www.w3.org/DesignIssues/LinkedData.html

1. Use URIs as names for things2. Use HTTP URIs so that people can look up those names.3. When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL)4. Include links to other URIs. so that they can discover more things.

- Tim Berners-Lee

Linked Data Principles

• Linked Data Principles

https://www.w3.org/DesignIssues/LinkedData.html

1. Use URIs as names for things2. Use HTTP URIs so that people can look up those names.3. When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL)4. Include links to other URIs. so that they can discover more things.

- Tim Berners-Lee

Linked Data Principles

How interlinked is your data?

https://www.w3.org/DesignIssues/LinkedData.html

The Del.ici.ous lesson

http://bokardo.com/archives/the-delicious-lesson/

The Del.ici.ous lesson

“The one major idea behind the Del.icio.usLesson is that personal value precedes network value. What this means is that if we are to build networks of value, then each person on the network needs to find value for themselves before they can contribute value to the network. In the case of Del.icio.us, people find value saving their personal bookmarks first and foremost. All other usage is secondary.” –Joshua Porter

http://bokardo.com/archives/the-delicious-lesson/

The Del.ici.ous lesson

What does your data do for the individual?… the research group?… the department?… the field?

http://bokardo.com/archives/the-delicious-lesson/

Mapping knowledge claims & evidence

“[Y]ou can transform a fact into

fiction or a fiction into fact just by

adding or subtracting references”- Bruno Latour

... two miRNAs, miRNA-372 and-373, function as potential novel oncogenes in testicular germ cell tumors by inhibition of LATS2 expression, which suggests that Lats2 is an important tumor suppressor (Voorhoeve et al., 2006).

Raver-Shapira et.al, JMolCell 2007

miR-372 and miR-373 target the Lats2 tumor suppressor (Voorhoeve et al., 2006)

Yabuta, JBioChem 2007:

As claims get cited, they become facts:

To investigate the possibility that miR-372 and miR-373 suppress the expression of LATS2, we...

Therefore, these results point to LATS2 as a mediator of the miR-372 and miR-373 effects on cell proliferation and tumorigenicity,

Voorhoeve et al, Cell, 2006:

Hypothesis

Implication

Cited Implication

Fact

Slide credit: Anita DeWaard: 'Stories that persuade with data' - talk at CENDI meeting January 9 2014https://www.slideshare.net/anitawaard/stories-that-persuade-with-data-talk-at-cendi-meeting-january-

9-2014/6

“The conversion of hypothesis to

fact through citation alone.”

- Stephen Greenberg

Greenberg, Steven A. "Understanding belief using citation networks." Journal of evaluation in clinical practice 17.2 (2011): 389-393.http://dx.doi.org/10.1111/j.1365-2753.2011.01646.x

“The conversion of hypothesis to fact through citation alone.”

- Stephen Greenberg

Greenberg, Steven A. "How citation distortions create unfounded authority: analysis of a citation network." BMJ 339 (2009): b2680.

https://doi.org/10.1136/bmj.b2680

Funded grants with citation bias & citation distortion.

Greenberg, Steven A. "How citation distortions create unfounded authority: analysis of a citation network." BMJ 339 (2009): b2680.

https://doi.org/10.1136/bmj.b2680

Modeling arguments and

evidence

https://dvcs.w3.org/hg/rdf/raw-file/default/rdf-primer/index.html

SEPIO – evidence lines

Brush, Matthew, Kent Shefchek, and Melissa Haendel. "SEPIO: a

semantic model for the integration and analysis of scientific

evidence." International Conference on Biomedical Ontology and BioCreative. 2016. http://ceur-ws.org/Vol-1747/IT605_ICBO2016.pdf

“A proposition has_evidence

one or more evidence lines, which have_supporting_data

one or more data items used in evaluation of the

proposition’s truth.”

SEPIO – evidence lines example

Brush, Matthew, Kent Shefchek, and Melissa Haendel. "SEPIO: a

semantic model for the integration and analysis of scientific

evidence." International Conference on Biomedical Ontology and BioCreative. 2016. http://ceur-ws.org/Vol-1747/IT605_ICBO2016.pdf

“A simplified account of existing evidence related to this proposition is presented below,

presenting summaries of five evidence lines (E1-E5) from five studies relevant to the

classification of the variant for Fabry Disease:

E1. Six affected individuals with the variant were found to have reduced GLA enzyme

activity.

E2. The variant was absent from 528 unaffected controls.

E3. The variant is predicted to cause abnormal splicing that inserts additional sequence.

E4. Pedigree analyses showed Fabry Disease phenotypes segregating with the variant.

E5. Population databases show high frequency of individuals homozygous for the variant.”

SEPIO – evidence lines example

Brush, Matthew, Kent Shefchek, and Melissa Haendel. "SEPIO: a

semantic model for the integration and analysis of scientific

evidence." International Conference on Biomedical Ontology and BioCreative. 2016. http://ceur-ws.org/Vol-1747/IT605_ICBO2016.pdf

“A simplified account of existing evidence related to this proposition is presented below,

presenting summaries of five evidence lines (E1-E5) from five studies relevant to the

classification of the variant for Fabry Disease:

E1. Six affected individuals with the variant were found to have reduced GLA enzyme

activity.

E2. The variant was absent from 528 unaffected controls.

E3. The variant is predicted to cause abnormal splicing that inserts additional sequence.

E4. Pedigree analyses showed Fabry Disease phenotypes segregating with the variant.

E5. Population databases show high frequency of individuals homozygous for the variant.”

Modeling arguments and

evidence

SEE

Bölling, Christian, Michael Weidlich, and Hermann-Georg Holzhutter.

"SEE: structured representation of scientific evidence in the biomedical

domain using Semantic Web techniques." Journal of Biomedical Semantics 5.1 (2014): 1.

SEE

Bölling, Christian, Michael Weidlich, and Hermann-Georg Holzhutter.

"SEE: structured representation of scientific evidence in the biomedical

domain using Semantic Web techniques." Journal of Biomedical Semantics 5.1 (2014): 1.

Modeling arguments and

evidence

Micropublications

Clark, Tim, Paolo N. Ciccarese, and Carole A. Goble.

"Micropublications: a semantic model for claims, evidence, arguments

and annotations in biomedical communications." Journal of Biomedical

Semantics 5.28 (2014). http://dx.doi.org/10.1186/2041-1480-5-28

Jodi Schneider, Paolo Ciccarese, Tim Clark, Richard D. Boyce. “Using the Micropublications ontology and the Open Annotation Data Model to represent evidence within a drug-drug interaction knowledge base.” Linked Science at ISWC 2014 http://ceur-ws.org/Vol-1282/lisc2014_submission_8.pdf

Mapping knowledge claims & evidence

Where are the opportunities in the field?

Patient safety 2006-2010

Cardiology 2006-2010

And who is at the pinch points?

Together we can have a fuller view

of our information landscape

• People & Organizations

• Spaces & Places

• Activities & Resources

• Ideas

• …Maybe More?

Heaney 2000

• What would a “Connected Graph of

Scholarship” do, that we can’t do now?