The document discusses the development of a comprehensive knowledge base (hpc-kb) aimed at enhancing human performance and cognition through structured exploration and search systems. It outlines the distinctions between knowledge bases and ontologies, emphasizing the need for dynamic updates to incorporate new scientific knowledge and relationships beyond traditional categories. Future work includes automating updates, improving the quality of the knowledge base, and utilizing advanced filtering and integration techniques to enhance user experience.

1. An Up-to-date Knowledge Base and Focused Exploration System for Human Performance and CognitionAmitShethLexisNexis Ohio Eminent ScholarDirector, Kno.e.sis CenterWright State UniversityRamakanthKavuluruPostdoctoral Research ScientistKno.e.sis CenterThanks to Dr. Victor Chan for support and guidanceHPC-KB team: Christopher Thomas, Wenbo Wang, Alan Smith, Paul Fultz, and Delroy Cameron

2. Focused Knowledge BasesA knowledge base (KB) functions as astandalone reference for a particular domain of interestbackend for knowledge-based search, browsing, and exploration of literature

3. What is a KB?“A body of knowledge describing a topic or domain of interest”categories or classes – Neurotransmitters, Diseaseindividuals (instances of classes)Dopamine, Magnesium, Migraineroles (properties/predicates) – inhibits, is a, part ofassertions (triples)Dopamine is a neurotransmitterMagnesium treats Migraine

4. Then, What are Ontologies?“Ontology is the basic structure or armature around which a knowledge base can be built” (Swartout and Tate, 1999)“An ontology is an explicit representation of a shared understanding of the important concepts in some domain of interest.” (Kalfoglou, 2001)So, mostly static blocks of well accepted and consensual knowledge

5. Ontologies in Life SciencesThe National Center for Biomedical Ontology (NCBO) - Open Biomedical Ontologies (OBO)About 200 ontologies and 1.5 million termsOnly part_of and is_a relations in the Gene OntologyHistolysis is_a positive regulation of cell sizeRequests for changes are expert reviewed before modifications

6. What about Emergent Knowledge, Richer Relationships?New scientific results and insights published everyday backed by experimentationPubMed: 18+ million articles; 1300 new per dayAlso, what about other predicates besides is_a and part_of (eg., UMLS Semantic Network of 54 predicates). Need a way of capturing and meaningfully utilizing this emerging knowledge

7. Enter HPC-KBNLPPatternsSCOONER

8. Steps in Creating the HPC-KBCarve a focused domain hierarchy out of WikipediaExtract mentions of entities and relationships in the relevant scientific literature (Pubmed abstracts) to support non-hierarchical guidance.Map extracted entity mentions to concepts and extracted predicates to relationships to create the knowledge-base

9. Workflow OverviewHPC keywordsDoozer: Base Hierarchy from WikipediaFocused Pattern based extractionSenseLab Neuroscience OntologiesInitial KB CreationMeta KnowledgebasePubMed AbstractsKnoesis: Parsing based NLP Triples Enrich Knowledge BaseNLM: Rule based BKR TriplesFinal Knowledge Base

10. Hierarchy Using Wikipedia Categories and Graph Structure

11. Triple ExtractionOpen Extraction No fixed number of predetermined entities and predicatesAt Knoesis – NLP (parsing and dependency trees)Supervised ExtractionPredetermined set of entities and predicatesAt Knoesis – Pattern based extraction to connect entities in the base hierarchy using statistical techniquesAt NLM – NLP and rule based approaches

12. Mapping of Triples to HierarchyEntities in both subject and object must contain at least one concept from the hierarchy to be mapped to the KBPreliminary synonyms based on anchor labels and page redirects in WikipediaProlactostatin redirects to DopaminePredicates (verbs) and entities are subjected to stemming using Wordnet

13. HPC-KB Stats Number of Entities -- 2 Million

14. Number of non-trivial facts -- 3 Million Examples:NLP based: calcium-binding protein S100B modulates long-term synaptic plasticityPattern based: Olfactory Bulb has physical part of anatomic structure Mitral cell Extracted from all abstracts untilAug 2008(Note: Abstracts accessible through Scooner: Oct 2010)

15. Full Architecture

16. Scooner FeaturesKnowledge-based browsing: Relations window, inverse relations, creating trailsPersistent projects: Work bench, browsing history, comments, filteringCollaboration: comments, dashboard, exporting (sub)projects, importing projects

17. Comments on Scooner“The ability to browse predications together with documents will likely reduce the cognitive load required for encountering interesting facts, both for novice users and domain experts.” – Thomas Rindflesch, Researcher in Biomedical Informatics, NLM.“Being able to keep track of multiple articles is a really nice tool to have, and it cuts down on time between jumping back and forth between articles” - Anonymous comment from an AFRL researcher

18. Future Work: KnexpaceAutomatic UpdatesIndex new abstracts as they arriveExtract relationships as new abstracts arrivePeriodically update indices for abstracts and triplesOther MaintenanceAdmin interfacesApplication software support

19. Improving the KB Quality & FilteringAdhere to a stricter schemaHaving a fixed number of predicates and a fixed range and domain for each predicateEx: For the immunology and chemical warfare agentsPredicate: activates Restricted Domain: Cytokines OR μRNARestricted Range: MacrophagesAlso useful to directly launch queries of the form Question: ?x activates Macrophages Answer: TNF-α and IFN-γ

20. Normalize Entities and Predicates How do we find Bovine spongiform encephalopathy and mad cow disease are same (Use UMLS Metathesaurus! )long term memory and long lasting memory are the same computationally (UMLS does not work)More complex similarities: HepG(2) cell line and Human Hepatoma G2 cellswhich textual forms map to the fixed set of predicates: Do modulates, regulates, stimulates all map to affects?(NLM expert collaboration & AFRL help)NLM tools: MetaMap, SemRep, and other lexical tools

21. Provenance and other meta dataOriginal abstract PMIDs will be captured for each triple.Other data: authors, journal namesHow about other meta data for filtering:In Vitro / In VivoIf, In Vivo, which organism. If Mice, which type: Ames Dwarf Which techniques are used. ex: Flow Cytometry

22. New Knowledge ExampleVIP Peptide – increases – Catecholamine BiosynthesisCatecholamines – induce – β-adrenergic receptor activityβ-adrenergic receptors – are involved – fear conditioningVIP Peptide – affects – fear conditioningIn CattleIn RatsIn Humans

23. Domain Specific ProvenanceFor Immunology and Warfare Agent effectsWhich pathogen: FrancisellatularensisWhich Strains: U112, LVS, …What is measured: Cells (dendritic, macrophages, monocytes), Proteins, cytokines, chemokinesNeed to find preexisting taxonomies for organisms, techniques, pathogens; or need to build some and integrateThe more the specificity, the more the KB quality

24. Better Ranking of Abstracts and TriplesUse search phrases to fine tune ranking of abstracts and triplesJust because the user clicked on neurogenesis, does not mean she wants to know everything about it. Predict which triples or abstracts the user might be more interested in the current search session.Show top-k entities in the result set to facilitate filtering based on top conceptsVisualize networks of a set of browsed triples

25. Semantic IntegrationFamous OBO Ontologies (total 7 foundry ontologies)Gene OntologyPRotein OntologyOther domain specific OBO candidateontologiesNCBI organismal classificationInfectious DiseaseHuman Disease (Tularemia found here, and also in SNOMED, & others too, what to choose for mapping?)Pathogen transmission

26. Semantic Integration, contd…Linked Open Drug DataDrugBank: drugs and drug targets (pathways, structures, sequences)Diseasome: disorders and disease-gene associationsLinkedCT: Clinical trialsMendelian InheritanceOnline MendelianInhertance in Animals (OMIA)Online Mendelian Inheritance in Man (OMIM)Different formats: owl, obo, rrf

27. Tools, Vocabularies, OntologiesUMLS