BiOnIC: A Catalog of User Interactions with Biomedical Ontologies
BiOnIC is a catalog of aggregated statistics of user clicks, queries, and reuse counts for access to over 200 biomedical ontologies. BiOnIC also provides anonymized sequences of classes accessed by users over a period of four years. To generate the statistics, we processed the access logs of BioPortal, a large open biomedical ontology repository. We publish the BiOnIC data using DCAT and SKOS metadata standards. The BiOnIC catalog has a wide range of applicability, which we demonstrate through its use in three different types of applications. To our knowledge, this type of interaction data stemming from a real-world, large-scale application has not been published before. We expect that the catalog will become an important resource for researchers and developers in the Semantic Web community by providing novel insights into how ontologies are explored, queried and reused. The BiOnIC catalog may ultimately assist in the more informed development of intelligent user interfaces for semantic resources through interface customization, prediction of user browsing and querying behavior, and ontology summarization. The BiOnIC catalog is available at: http://onto-apps.stanford.edu/bionic.
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BiOnIC: A Catalog of User Interactions with Biomedical Ontologies
- 1. BiOnIC: A Catalog of User Interactions with Biomedical Ontologies 16th Interna+onal Seman+c Web Conference (ISWC) Vienna, 21st - 25th October 2017 M A U L I K KA M D A R , S I M O N WA L K , TA N I A T U D O R A C H E , MA R K MU S E N Stanford Center for Biomedical Informa:cs Research maulikrk@stanford.edu
- 2. Benefits of analyzing user interac+ons Ø Ontology Engineers: v Iden+fy explora+on and querying paVerns v Understand ontology usage and reuse v Prune unwanted classes and rela+ons Ø Ontology Repository Maintainers: v Categorize user behaviors v Develop intelligent interfaces v Provide targeted recommenda+ons Ø Biomedical Researchers: v Iden+fy temporal research trends v Iden+fy frequently accessed classes
- 9. NCBO API Usage APIRequestsperMonth 2013−O ct 2014−Jan 2014−Apr 2014−Jul 2014−O ct 2015−Jan 2015−Apr 2015−Jul 2015−O ct 2016−Jan 2016−Apr 2016−Jul 2016−O ct 2M8M32M Filtering Access Logs Filtering Ontologies Compu+ng Class Counts Compu+ng Sequences Anonymizing Data NCBO Website Traffic OccurrencesperMonth 2009−Jan 2010−Jan 2011−Jan 2012−Jan 2013−Jan 2014−Jan 2015−Jan 2016−Jan 0100K200K Page Requests Unique IP Addresses BiOnIC datasets crea+on • Removing robot/invalid requests • Normalizing ontology iden+fiers and class IRIs
- 10. Filtering Access Logs Filtering Ontologies Compu+ng Class Counts Compu+ng Sequences Anonymizing Data BiOnIC datasets crea+on • January 2015 version. • Ontologies should have classes that are reused by others OR reuse classes from other ontologies. • Ontologies should have minimum of 10 unique users via WebUI and API
- 11. Filtering Access Logs Filtering Ontologies Compu+ng Class Counts Compu+ng Sequences Anonymizing Data BiOnIC datasets crea+on Class Sta:s:cs Datasets For each class in each ontology: • Access AGributes: o Total IP Requests (WebUI/API) o Unique IP Requests (WebUI/API) • Reuse AGributes: o Number of ontologies reusing a class • Structural AGributes: o Number of parent/child/sibling classes o Depth from ontology root
- 22. 2a’ 1’ 2b’ 3b’ 2a 3a 4a 3a 1 Filtering Access Logs Filtering Ontologies Compu+ng Class Counts Compu+ng Sequences Anonymizing Data BiOnIC datasets crea+on User Interac:on Sequences Datasets Ontology 1 Ontology 2
- 23. Filtering Access Logs Filtering Ontologies Compu+ng Class Counts Compu+ng Sequences Anonymizing Data BiOnIC datasets crea+on Anonymiza:on Steps • IP addresses anonymized using unique SHA-224 hash-encoded user iden+fiers generated from “user_<Random String>_<Random_Integer>”. • e.g. 39fd4e6d569a034973g61bb392a694d4eabe1ef98c43ee68ca2fc86 • Absolute Time-stamps converted to rela+ve +me-stamps, with respect to first interac+on with BioPortal repository. • e.g. 0, 2757, 2786, 3586, 3618, 3803, 3959, 4047, 5111 (s), …
- 24. BiOnIC schema to model sta+s+cs and sequences data countStat bionic:CountStat bionic:ReuseCount - reuseType - reusingOntologies bionic:RequestCount - accessType - year - totalUsers - uniqueUsers prov:Agent bionic:Sequence - accessType - totalTime - uniqueClasses bionic:SeqEn:ty - rela6veTimestamp bionic:Ontology - skos:prefLabel - totalClasses - maxDepth owl:Class - skos:prefLabel skos:Collec:on skos:Concept begin end nextEn6ty class class requests skos:member bionic:SeqDataset - accessType bionic:StatDataset dcat:Dataset sequence classInfo ontology ontology bionic:ClassInfo - siblings - directParents - directChildren - classDepth class subClassOf ontology SKOS, PROV and DCAT standards are reused in the BiOnIC schema.
- 29. Characteris+cs of the BiOnIC Catalog • WebUI Access: 5.4M class requests, 1M unique agents • API Access: 67.2M class requests, 205K unique agents • 255 biomedical ontologies
- 40. Novel research direc+ons may be enabled through the BiOnIC and VisIOn resources • Categorize user browsing behaviors by incorpora+ng the structural features of the ontology classes. • Develop personalized user interfaces for ontology naviga+on, which take into account the user type and the predic+ons of the next class that a user is likely to access. • Develop advanced methods for ontology summariza+on and modulariza+on, using BiOnIC datasets as features. …