semantic societies: uncovering new research paths, engaging members better

Semantic SocietiesUncovering new research pathsEngaging members better

Charlie Rapple, TBI Communications

SSP Annual Meeting 2010

Society for Scholarly Publishing

What we will cover

The contextThe visionThe experimentThe realityThe futureThe vision (redux)

© Elijah Nouvelage via Flickr

Context: technology and publishing

Online publishing ≠ digital publishingPrint + PDF ≠ digitalPDF = 0Print + PDF = print

Context: hidden knowledge

“It is quite depressive to think that we are spending millions in grants for people to perform experiments, produce new knowledge, hide this knowledge in a often badly written text and then spend some more millions trying to second guess what the authors really did and found”

Amos Bairoch, Nature Precedings, via Biochemical Journal

Waiting for innovation to go away

Context: societies and publishing

Threats from all sidesBudget cuts, big deals, open accessChanging user behaviourAutonomous professional networks

But retain unique / vital role Mission-driven publishingFunding and dissemination of research

© Dinky Divas via Flickr

The Vision

© Wen Nag via Flickr

Speeding up scientific progress

What semantic data analysis can add to research information

How societies could add value to content strengthen role in communitymeet emerging needs of members

© Sadia Raval via Flickr

The Experiment

Breathing Space

The first semantic web collaboration between scholarly societies

Exploring the value of compiling and mining a critical mass of data within a discipline ERS and ATS together account for 30% of citations within respiratory medicine

Why

To find out whether semantic web technologies are useful in practice

To better support teaching, research and learning by exploring new ways of finding research material

To position societies as leaders in respiratory research by providing more effective, interesting tools

To help authors achieve higher visibility

How

Publishing Technology’s pub2web platform

Semantic content storage and analysis (data mining)

Interconnecting content based on citations, keyword density and author relationships

Where

http://respiratory.publishingtechnology.com

What: semantic browsing

What: concept homepages

What: concept tagclouds

What: faceted search

What: enhanced article homepage

What: author homepage

Author profiles

http://www.researchprofiles.collexis.com/ohsuV3/expert.asp?n=Dorsa%2C+Daniel+M&u_id=428

The Reality

Challenges

Finding an altruistic technology partner!Acquiring dataHerding catsDefining parameters for data miningMaking the horse drinkFinding convincing examples

© Matteo Dudek via Flickr

The Future

Lessons learned

Free = low priority

Data mining = inexact; science = exact

Context = blinkers

Examples are key to explanation

Advocates are key to spreading the word

Future developments

Phase IContinue roll out to widen usageUsage analysisQualitative feedback / research

Phase IIAdd more journals?Develop additional functionality around authors?Provide curation tools to editors?

The Vision (Redux)

© Sadia Raval via Flickr

Thank you

Charlie RappleTBI Communicationscharlie.rapple@tbicommunications.com

SSP Annual Meeting 2010