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1 genSpace: Community- Driven Knowledge Sharing for Biological Scientists Gail Kaiser’s Programming Systems Lab Columbia University Computer Science.

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Presentation on theme: "1 genSpace: Community- Driven Knowledge Sharing for Biological Scientists Gail Kaiser’s Programming Systems Lab Columbia University Computer Science."— Presentation transcript:

1 1 genSpace: Community- Driven Knowledge Sharing for Biological Scientists Gail Kaiser’s Programming Systems Lab Columbia University Computer Science

2 2 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.

3 3 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 – may be outdated, requires active participation  We seek to enable automatic knowledge sharing – without requiring “extra work” by scientists

4 4 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 …”

5 5 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

6 6 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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8 8 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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17 17 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

18 18 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

19 19 Ross Lab Semantic Ranking and Result Visualization for PubMed Search Social Network Aware Search in Collaborative Tagging Sites 2 posters & demo (Julia Stoyanovich)

20 20 genSpace: Community-Driven Knowledge Sharing for the Discovery and Visualization of Workflows in geWorkbench Gail Kaiser kaiser@cs.columbia.edu www.psl.cs.columbia.edu/genspace/


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