How taxonomies and facetsbring end-users closer to big data                  Anna Divoli                  @annadivoliBosto...
Taxonomies• τάξις/τάξη + νομία (arrangement/class + method/rule/law)• hierarchical classification• formal nomenclature• va...
User Studies TypesSpecialized domain studies:1. Facets (HCIR): Biomedical Scientists    Anna Divoli and Alyona Medelyan   ...
Our studies  1. Facets (HCIR): Biomedical Scientists   Anna Divoli and Alyona Medelyan   Search interface feature evaluati...
Facets – favorite feature for search systems    Anna Divoli and Alyona Medelyan, Search interface feature evaluation in   ...
Facets (in search systems)           animal models huntington disease           Boston Oct 2012
Bio-Facets      Most liked                     Least liked  animal models huntington disease                   Boston Oct ...
Facets as search features for biomedical scientists: Findings• Faceted search is the most important stand alone feature in...
Search expansions★Facets as search feature: likes & dislikes brffig                                                       ...
Our studies  2. Expert needs (media group)              Boston Oct 2012
Case Study: Media GroupThey have a system/”taxonomy” in place that nobodymaintains or uses…~ 10,000 articles / week, ~5 mi...
Expert content needs - Case Study: Media Group Ideally update the taxonomy daily/weekly Must be dynamic & handle new cas...
Our studies  3. Existing popular systems (EuroHCIR)   Matthew Pike, Max L. Wilson, Anna Divoli and Alyona Medelyan   CUES:...
Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD            Boston Oct 2012
Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD            Boston Oct 2012
Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD            Boston Oct 2012
Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD            Boston Oct 2012
Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD  A B C D E F       A B C D E F       A B C D E F   A B C ...
Exploring UI features (Yippy, Carrot, MeSH, ESD): likes & dislikes      •   Menu highlighting      •   Hierarchical folder...
Our studies  4. Mock ups of specific features (survey)              Boston Oct 2012
Taxonomy UI preferences (ongoing survey):                                     The (51) participants            Age:       ...
popularity (A)    44.2%Concept sorting             alphabetically (B)   42.3%                               no preference ...
A   42.3%Displaying Counts                       B   51.9%                            no preference   5.8%          Boston...
in frames (A)    72.5%Using Labels                 with labels (B)   23.5%                             no preference     3...
A   47.1%Plus/minus signs or arrows               B   37.3%                             no preference   15.7%           Bo...
A   13.7%Search Results Display                   B   11.8%                                         C   70.6%             ...
partial   74.5%Search Functionality                hidden    64.7%                             no preference    2.0%      ...
Where we standOur team works on automatic generated taxonomies but werealized the need for customization for specific need...
Taxonomy “Taxonomy is described sometimes as a science and sometimes as an art, but really it’s a battleground.”          ...
T echnology                 A rt              a X iomatic           phil O sophy          desig N               l O gic   ...
Summary• There is a place for manually, socially and automatically  generated taxonomies (as well as hybrids).• Text is “b...
Acknowledgements             Alyona Medelyan (Pingar)             Max L. Wilson (Swansea/Nottingham)             Matthew P...
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How Taxonomies and facets bring end users closer to big data

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Pingar researcher Dr Anna Divoli's presentation given at the 2012 Text Analytics World Boston. Content includes discussion of taxonomies and big data,.

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  • Based on our current knowledge, experience and the results of our user studies the direction our research team is taking
  • How Taxonomies and facets bring end users closer to big data

    1. 1. How taxonomies and facetsbring end-users closer to big data Anna Divoli @annadivoliBoston Oct 2012
    2. 2. Taxonomies• τάξις/τάξη + νομία (arrangement/class + method/rule/law)• hierarchical classification• formal nomenclature• varied dimensions• evaluation/measures/metrics• types: manually constructed, social, auto-generated• purposes: auto-indexing, search facilitation, navigation, knowledge management, organization….• it is OK to change the classification systems to adjust to new knowledge – not just adding new concepts• the data have become “big” and available but not accessible• many “end users” Boston Oct 2012
    3. 3. User Studies TypesSpecialized domain studies:1. Facets (HCIR): Biomedical Scientists Anna Divoli and Alyona Medelyan Search interface feature evaluation in biosciences, HCIR 2011, Google, Mountain View, CA2. Expert needs (media group)UI preferred features studies:3. Existing popular systems (EuroHCIR) Matthew Pike, Max L. Wilson, Anna Divoli and Alyona Medelyan CUES: Cognitive Usability Evaluation System, EuroHCIR 2012, Nijmegen, Netherlands4. Mock ups of specific features (survey) Boston Oct 2012
    4. 4. Our studies 1. Facets (HCIR): Biomedical Scientists Anna Divoli and Alyona Medelyan Search interface feature evaluation in biosciences, HCIR 2011, Google, Mountain View, CA Boston Oct 2012
    5. 5. Facets – favorite feature for search systems Anna Divoli and Alyona Medelyan, Search interface feature evaluation in biosciences, HCIR 2011, Google, Mountain View, CA, USA Boston Oct 2012
    6. 6. Facets (in search systems) animal models huntington disease Boston Oct 2012
    7. 7. Bio-Facets Most liked Least liked animal models huntington disease Boston Oct 2012
    8. 8. Facets as search features for biomedical scientists: Findings• Faceted search is the most important stand alone feature in a search interface for bioscientists.• Few, query-oriented facets presented as checkboxes work best.• Overly simple aesthetics, although not desirable, do not hurt overall UI score.• Complex aesthetics turn users away from the systems.• Bioscientists prefer tools that help them narrow their search, not expand it.• For generic search: doc-based facets. For domain-specific search: query-based facets. Boston Oct 2012
    9. 9. Search expansions★Facets as search feature: likes & dislikes brffig S Facetted refinement • Useful categories + useful categories + quick paper access + “topbr - slow functionality• Simple + “reviews” category + simple - tooff - too complex/busy - too many colors • - limited functional. Vertical list - poor design + vertical list - nothing specialig Semedico PubMed Solr Go Related searchesbr - not scientific + colors • Too complex/busy + relevantff - too small - too busy • Too many colorsvariety - poor context - noig Bing • Poor design PubMed Results preview★ • Limited functionality • Too many symbolsbrff • Not special/ Colorlessig Legend + positive comments Boston Oct 2012 positive
    10. 10. Our studies 2. Expert needs (media group) Boston Oct 2012
    11. 11. Case Study: Media GroupThey have a system/”taxonomy” in place that nobodymaintains or uses…~ 10,000 articles / week, ~5 million in their archives~ 21 years, 10,000 authorsHandful of top categoriesMain reasons/uses:- Advertisement- Packing up stories and selling them- Readers finding stories & related stories- Journalists finding related stories Boston Oct 2012
    12. 12. Expert content needs - Case Study: Media Group Ideally update the taxonomy daily/weekly Must be dynamic & handle new cases/concepts Deep nesting is OK If multiple inheritance, need to disambiguate where a particular article belongs to Be able to edit (be able to verify , in case of anomalies based on automation & move nodes around) Boston Oct 2012
    13. 13. Our studies 3. Existing popular systems (EuroHCIR) Matthew Pike, Max L. Wilson, Anna Divoli and Alyona Medelyan CUES: Cognitive Usability Evaluation System, EuroHCIR 2012, Nijmegen, Netherlands Boston Oct 2012
    14. 14. Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD Boston Oct 2012
    15. 15. Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD Boston Oct 2012
    16. 16. Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD Boston Oct 2012
    17. 17. Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD Boston Oct 2012
    18. 18. Exploring UI features - Systems Tested: Yippy, Carrot, MeSH, ESD A B C D E F A B C D E F A B C D E F A B C D E F A B C DE F C F B D A E Boston Oct 2012
    19. 19. Exploring UI features (Yippy, Carrot, MeSH, ESD): likes & dislikes • Menu highlighting • Hierarchical folder layout • Expand hierarchy with “+” and “–” • Dual view (tree on left, results on right) • Ability to change visualisations of taxonomy • Search function is important • Familiar interface with folders • Too simple or too much writing - would be nice to have color • Lots of scrolling • Dots in carrot circle – confusing • Double click on foam tree is unintuitive • Too broad taxonomies Boston Oct 2012
    20. 20. Our studies 4. Mock ups of specific features (survey) Boston Oct 2012
    21. 21. Taxonomy UI preferences (ongoing survey): The (51) participants Age: How comfortable you are with computers? 25 or younger 27.3% Somewhat 5.5% 26-40 60.0% Very 47.3% 41-60 12.7% Second nature 47.3% 61 or older 0% Highest level of education: Do you have experience using taxonomies? High School 3.6% No 30.9%College/University 52.7% Yes, but very little 47.3% Graduate School 43.6% Yes 21.8% bit.ly/pingar_taxonomies Boston Oct 2012
    22. 22. popularity (A) 44.2%Concept sorting alphabetically (B) 42.3% no preference 13.5% Boston Oct 2012
    23. 23. A 42.3%Displaying Counts B 51.9% no preference 5.8% Boston Oct 2012
    24. 24. in frames (A) 72.5%Using Labels with labels (B) 23.5% no preference 3.9% Boston Oct 2012
    25. 25. A 47.1%Plus/minus signs or arrows B 37.3% no preference 15.7% Boston Oct 2012
    26. 26. A 13.7%Search Results Display B 11.8% C 70.6% no preference 3.9% Boston Oct 2012
    27. 27. partial 74.5%Search Functionality hidden 64.7% no preference 2.0% Boston Oct 2012
    28. 28. Where we standOur team works on automatic generated taxonomies but werealized the need for customization for specific needs Boston Oct 2012
    29. 29. Taxonomy “Taxonomy is described sometimes as a science and sometimes as an art, but really it’s a battleground.” Bill Bryson, A Short History of Nearly Everything Boston Oct 2012
    30. 30. T echnology A rt a X iomatic phil O sophy desig N l O gic hu M anities lingu I stics E thnonology S cienceBoston Oct 2012
    31. 31. Summary• There is a place for manually, socially and automatically generated taxonomies (as well as hybrids).• Text is “big” and in many fields dynamic.• “End-users” (not Information Management experts) need access to “big text”.• Auto-generated taxonomies with manual editing facilities is now possible & makes sense.• Domain specific background knowledge is vital for the quality and detail required per solution.• User friendly systems are very important for end users. Boston Oct 2012
    32. 32. Acknowledgements Alyona Medelyan (Pingar) Max L. Wilson (Swansea/Nottingham) Matthew Pike (Swansea/Pingar) Pingar Brainspingar.com All 65+ anonymous studies participants! Boston Oct 2012
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