Formative Usability Test
http://hubzero.org/ HUBzero ® is a powerful, open source software platform for creating dynamic web sites that support scientific research and educational activities
- Multiform Multiview Trees
- Multiple overlapping Classification Hierarchies
- Extending Taxonomic Visualization
- Visual Exploration of Alternative Taxonomies
- TaxVis Demos
- TaxVis Instructions
- Survey of Multiple Tree Visualizations
- Survey of Multiple Tree Visualization Paper
- InfoVis 2003 Contest on Visualization and PairWise Comparison of Trees
- TreeJuxtaposer Demos
- The Book of Trees
- effective filtering: http://data.canadensys.net/explorer/search;jsessionid=AB4DE0B44B6B756FDBADB7EB6A1B2EAE
- Joe Miller, acaciamulga.net (email@example.com), taxonomy tree with characters. shows 10 characters along the species, aggregate character values at higher ranks, highlights variations of characters using vertical bars, link to distribution on a map. http://www.acaciamulga.net/#!phylojive-demo-trait-data/cwpe
- GWAS : http://www.ebi.ac.uk/fgpt/gwas/ visualizing traits associated with genes.
- Graph lib: Gephi https://gephi.org/ internally used GraphXML. Used by the Open Tree of Life. Load tens thousands of node efficient. Have different modules that emphasis differences or similarity.
- View a tree at http://portnoy.iplantcollaborative.org/
- initial idea from Michael McGuffin <firstname.lastname@example.org> and Shrey Gupta <email@example.com>:
- Graham, M., Kennedy, J. (2007). Visual Exploration of Alternative Taxonomies through Concepts. Ecological Informatics, 2(3), 248-261. DOI: 10.1016/j.ecoinf.2007.07.004 http://www.iidi.napier.ac.uk/c/publications/publicationid/11002883
- Graham, M., and J. Kennedy. 2010. A Survey of Multiple Tree Visualization. http://researchrepository.napier.ac.uk/3039/1/Graham.pdf
- Graham, M., and J. Kennedy. 2014. Vesper: Visualising species archives. Ecological Informatics 24:132–147. Elsevier B.V.
- "Defining N-ary Relations on the Semantic Web" http://www.w3.org/TR/swbp-n-aryRelations/
Glossaries and Ontologies
- "TERMS FOR SURFACE VESTITURE AND RELIEF OF CUCURBITACEAE FRUITS"
- SSWAP tools by iPlant Collaboratives:
- Ontology Modularization: Del Vescovo C, Gessler D, Klinov P, Parsia B, Sattler U, Schneider T, Winget A (2011). Decomposition and Modular Structure of BioPortal Ontologies. In Proceedings of the 10th International Semantic Web Conference ISWC 2011 (Part I) pp. 130-145 
- Gessler DDG, Joslyn C, Verspoor K. (2013) A Posteriori Ontology Engineering for Data-Driven Science. In Data Intensive Science, Eds. T. Critchlow, K. Kleese van Dam. CRC Press.
- Phenotator: http://wwwdev.ebi.ac.uk/fgpt/phenotator/ (Use this tool to enter phenotypes descriptions and annotate these description with ontology terms using the entity/quality (EQ) pattern. An application ontology is generated automatically based on the annotations)
- Ontology version control:
- git(gui:Tower) and svn (gui: smartSVN).
- It is best practice to include a versionIRI or other indicator in the file itself, for example: <owl:versionIRI rdf:resource="http://purl.obolibrary.org/obo/uberon/releases/2013-06-13/ext.owl"/>
- To compare differences:
- for OWL files, use compare files function in Protege, also use regular text diff tools
- OBO format doesn't pose any problems here, and is a major reason why some people have not changed
- There are other tools that look at the actual OWL: http://krizik.felk.cvut.cz/km/owldiff/documentation.html
- Groza, Tudor, Jane Hunter, and Andreas Zankl. 2012. “Supervised Segmentation of Phenotype Descriptions for the Human Skeletal Phenome Using Hybrid Methods.” BMC Bioinformatics 13 (1) (October 15): 265.
Pdf to Text
Based on WordNet, provide path, depth, info content based measures, may include relatedness measures like lesk, vector, hso
ws4j https://code.google.com/p/ws4j/ [leaves large and leaves small has similarity of 100%, do not deal with antonyms]
Based on UMLS (Unified Medical Language System), provide path, depth, info content measures, includes relatedness measures lesk, vector
Based on (GO), provide path, depth, and info content measures