Algorithms and Tools Relevant for the Mapping of Science and HPS Lead: Kevin Boyack Participants: Tony Beavers Yunwei Chen Jean-Gabriel Ganascia Jaimie Murdock Andrew Ravenscroft Chris Sula John Walsh Angela Zoss Breakout session on

General Considerations Differences between network creation analysis and visualization algorithms Data formats don’t fit directly into tools: for example, data needs to be fielded for some tools (may need some middleware, additional conversion tools) What are the similarities and differences between science and HPS? Are there different needs? Can the same algorithms be applied to all data sets?

Associated Challenges and Opportunities How to generate maps/networks from HPS data?

Proposed Solutions Host a NWB demo – online workshop, DVD Have HPS researchers send feedback on desired features to NWB team

Data TEI-XML docs (1990s  ); see tei-c.org –Names –Dates –Links Text blocks (documents, without tags)

Tools NWB Simile Timeline Google Maps Adobe Flex (with Google Code Library Birdeye) Python/PERL/SQL Pajek

Algorithms Visualization algorithms: –Layout algorithms (spring weights – no clustering) –Clustering algorithms (after/within visualization) –Treemaps –Graph layouts (nodes and edges) –Dendrogram –Self-organizing map (also generates the network) Network creation/analysis algorithms: –TFIDF (for word co-occurrence) –Clustering algorithms (agglomerative, pure, trained/supervised)