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genSpace: Community-Driven Knowledge Sharing

for Biological Scientists

Gail Kaiser’s Programming Systems Lab

Columbia University

Computer Science

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Introduction Scientists collaborating together in the same lab

on the same project share: Data: specimens, samples, materials, analyses Tools: instruments, software, hardware Knowledge: open discussion, whiteboard

However, there are temporal (time) and physical (space) constraints

This model does not scale to communities of scientists working on different projects but who could possibly learn from each other’s expertise, experience, etc.

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CSCW Approaches Most current generation Computer-Supported

Cooperative Work systems enable data sharing and/or tool sharing (e.g., PNNL Collaboratories, UIUC BioCoRE)

However, these systems support relatively limited knowledge sharing how/when/where/why to use tools and data

Knowledge sharing is partially enabled through labor intensive approaches: pubs, email lists, wikis, chat, shared display, etc. – may be outdated, requires active participation

We seek to enable automatic knowledge sharing – without requiring “extra work” by scientists

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Social Networking Metaphor Some online social networking is a form of

CSCW that is potentially enjoyable and profitable but requires “extra work”, with dynamism limited by explicit user participation Facebook, MySpace, LinkedIn, Twitter, etc.

Other social networking automatically records, aggregates, data mines and disseminates what people do online in an enjoyable and profitable fashion, with no “extra work” required Collaborative filtering – “people like you …”

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genSpace We combine implicit and explicit social

networking (and collective intelligence) concepts in our approach to knowledge sharing

Prototype implemented as a set of plugins for geWorkbench, MAGNet’s platform for analysis and visualization tools for integrated genomics

Records, aggregates, data mines and disseminates geWorkbench users’ activities with tools and tool sequences (workflows)

Users can opt-in or opt-out

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Integrated genomics analysis application Support for gene expression data,

sequences, pathways, structure. 50+ visualization and analysis modules. Access to local and remote data sources and

analytical services. Integration with biological annotation sources.

Development platform Open source, Java-based. Component architecture, facilitating

customization.

www.geworkbench.org

geWorkbench – A platform for Integrated Genomics

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geWorkbench – A platform for Integrated Genomics

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Questions genSpace Can Answer What do I do first? Which tools work well together? Where does this tool fit in a typical workflow? Who do I know who also uses this tool? How do I get help (from an expert who is

online right now)?

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Contributions We investigate an approach to collaborative

knowledge sharing that is based on data mining and social networking requiring little or no “extra work” by scientists

We have developed a prototype implementation, genSpace, built on the geWorkbench platform

Logging, data mining, etc. of geWorkbench user activities, tool/workflow recommendation and visualization already included in local pre-release repository

Planned for next external release

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Future Work More precise monitoring - specific analysis

parameters and options, visualization activities Privacy and Confidentiality – Leverage collaborative

networks to restrict dissemination Address “concept drift” as user participation,

tool/workflow usage, privacy settings change Scaling up to hundreds of users and hundreds of

thousands of logs – Caching at client and server, incremental update, offline access

genSpace APIs enabling easy port to other tool integration frameworks beyond geWorkbench

Integration with pub “tagging” in Ken Ross lab

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Ross Lab Semantic Ranking and Result Visualization

for PubMed Search Social Network Aware Search in

Collaborative Tagging Sites

2 posters & demo (Julia Stoyanovich)

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genSpace: Community-Driven Knowledge Sharing for the

Discovery and Visualization of Workflows in geWorkbench

Gail Kaiserkaiser@cs.columbia.edu

www.psl.cs.columbia.edu/genspace/