1 Guy Divita Qing Zeng-Treitler Salt Lake City VA, University of Utah School of Medicine Pragmatic Interoperability

2 Toy Story We all agree one-off-solution is not good Many approaches to Interoperability

3 Internal Interoperability

4 Framework Supporting Interoperability

5 Within System Issues Many Master Builders who do not share a plan! And plan changes…

6 Within System Issues Sometimes integration is more work than building from scrtach

7 Pragmatic Interoperability

8 Overview

9 Terminology

10 Messaging Protocol

11 Ontological Alignment

12 Pragmatics

13 Pragmatics (2)

14 Feature Alignment Semantics

15 Feature Alignment Semantics (2)

16 Expressibility

17 Expressibility (2)

18 Expressibility(3)

19 Pragmatics (again)

20 Interoperability Efforts within v3NLP

21 From survey of existing NLP systems Common ontological referent points Combines CDA, Penn Treebank labels New labels where needed – Document structure (table, figure, snippet, slot value … Rendered into UIMA Type Descriptors Protégée Ontology Common Set of Labels

22 Interoperability Efforts within v3NLP

23 Special Considerations

24 Modeling Negation

25 Asymmetric Interoperability

26 Barriers to Interoperability

27 Solution Limit the number of moving parts + Some planning Simple protocol Simple semantics

28 Pragmatic Interoperability Principles

29 Programs, projects, ideas, utilities, services and shared resources workflow aids, annotation editors, evaluation tools, lexicon generation aids, ontology development tools, dashboards Repo’s, wiki’s, website(s) Evolving standards, guidelines, best practices NLP Ecosystem Elements

30 Big goals, grand challenges, many little dance steps Engendering developer and user communities Engendering collaborative environments Governing body to influence direction …… NLP Ecosystem Elements (continued)

31 One-off code for specific tasks (GSpell) Open source software developed on common framework (HITEx) Interoperable and user friendly systems on common framework (V3NLP) NLP ecosystem/ Marketplace Clinical NLP Development Trend

32 EMMA Sophia cTAKESVoogo ARC UFIT Common Labels Sublanguage Model UIMA-GATE converter WEKA UIMA U Compare MetaMap RapTAT Mallot … Toward a NLP Ecosystem Dave

33 POS Tagger Shallow NP Parser Full Parser Section Tokenizer Document Classifier De-Identification Semantic Classification Concept Identification Annotation Tools Corpus Annotation Analysis Negation Relationship Identification Temporal Relations Local Terminology Development Tool Co-reference Resolution Word Sense Disambiguation Document / Section / Sentence/ Phrase Information Retrieval indexes Concept: value Identification Table Tokenization Figure/Caption Identification Document Summarization Multi-Document Summarization – Novelty Detection Anaphora Resolution Text Normalization (stemming) Spelling Suggestion Text Simplification Theme Detection Concordance Term Identification Template Detection Text-To-Structured Data GATE UIMA Knowtator NLP Standards An Ecosystem that includes