1 The Ontologically Privileged Status of the Past Barry Smith.

Slides:



Advertisements
Similar presentations
Ontology Assessment – Proposed Framework and Methodology.
Advertisements

A Unified Approach to Combat Counterfeiting: Use of the Digital Object Architecture and ITU-T Recommendation X.1255 Robert E. Kahn President & CEO CNRI,
ECO R European Centre for Ontological Research Strategies for Referent Tracking in Electronic Health Records Dr. W. Ceusters European Centre for Ontological.
Study Designs in Epidemiologic
ECO R European Centre for Ontological Research Ontology-based Error Detection in SNOMED-CT ® Werner Ceusters European Centre for Ontological Research Universität.
Introduction to Research Methodology
Division of Biomedical Informatics Beyond Interoperability: What Ontology Can Do for the EHR William R. Hogan, MD, MS July 30 th, 2011 International Conference.
ECO R European Centre for Ontological Research Practical implementations of realism-based ontologies: Referent Tracking in Electronic Health Records MIE.
Signs, Symptoms and Findings. EXAMPLES OF TYPES OF PHYSICAL PATHOLOGY Independent organismal continuant Portion of canonical body substance Pathological.
1 An Ontology of Relations for Biomedical Informatics Barry Smith 10 January 2005.
The Role of Foundational Relations in the Alignment of Biomedical Ontologies Barry Smith and Cornelius Rosse.
1 Beyond Concepts Barry Smith
1 Ontology in 15 Minutes Barry Smith. 2 Main obstacle to integrating genetic and EHR data No facility for dealing with time and instances (particulars)
ECO R European Centre for Ontological Research Requirements for natural language understanding in referent-tracking based electronic patient records. CS.
1 Logical Tools and Theories in Contemporary Bioinformatics Barry Smith
Referent Tracking: Towards Semantic Interoperability and Knowledge Sharing Barry Smith Ontology Research Group Center of Excellence in Bioinformatics and.
AN INTRODUCTION TO BIOMEDICAL ONTOLOGY Barry Smith University at Buffalo 1.
VT. From Basic Formal Ontology to Medicine Barry Smith and Anand Kumar.
New York State Center of Excellence in Bioinformatics & Life Sciences R T U Referent Tracking: The New Paradigm Dagstuhl May 23th, 2006 Werner Ceusters,
Sabine Mendes Lima Moura Issues in Research Methodology PUC – November 2014.
1/24 An ontology-based methodology for the migration of biomedical terminologies to the EHR Barry Smith and Werner Ceusters.
1 Introduction Introduction to database systems Database Management Systems (DBMS) Type of Databases Database Design Database Design Considerations.
1 The Future of Clinical Bioinformatics: Overcoming Obstacles to Information Integration Barry Smith Brussells, Eurorec Ontology Workshop, 25 November.
Foundations This chapter lays down the fundamental ideas and choices on which our approach is based. First, it identifies the needs of architects in the.
IMPROVING THE DOCUMENTATION OF DIAGNOSES Carol A. Lewis.
Introduction to Database Systems 1.  Assignments – 3 – 9%  Marked Lab – 5 – 10% + 2% (Bonus)  Marked Quiz – 3 – 6%  Mid term exams – 2 – (30%) 15%
Chapter 17 Nursing Diagnosis
RSBM Business School Research in the real world: the users dilemma Dr Gill Green.
Bringing the technology of FedEx parcel tracking to the Electronic Health Record (EHR) 1/2 0.
Chapter 9 Database Planning, Design, and Administration Sungchul Hong.
© 2003 East Collaborative e ast COLLABORATIVE ® eC SoftwareProducts TrackeCHealth.
Electronic Health Records Dimitar Hristovski, Ph.D. Institute of Biomedical Informatics.
Bringing the technology of FedEx parcel tracking to the Electronic Health Record (EHR) 1/2 0.
A GENERIC PROCESS FOR REQUIREMENTS ENGINEERING Chapter 2 1 These slides are prepared by Enas Naffar to be used in Software requirements course - Philadelphia.
New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U.
1 Science as a Process Chapter 1 Section 2. 2 Objectives  Explain how science is different from other forms of human endeavor.  Identify the steps that.
ifomis.org 1 Die Ontologie biomedizinischer Daten Barry Smith Institute for Formal Ontology and Medical Information Science.
New York State Center of Excellence in Bioinformatics & Life Sciences R T U Referent Tracking Unit R T U Guest Lecture for Ontological Engineering PHI.
Networking and Health Information Exchange Unit 5b Health Data Interchange Standards.
Sharing Ontologies in the Biomedical Domain Alexa T. McCray National Library of Medicine National Institutes of Health Department of Health & Human Services.
1 The Theoretical Framework. A theoretical framework is similar to the frame of the house. Just as the foundation supports a house, a theoretical framework.
Database Environment Chapter 2. Data Independence Sometimes the way data are physically organized depends on the requirements of the application. Result:
Basic Nursing: Foundations of Skills & Concepts Chapter 9
ECO R European Centre for Ontological Research Referent Tracking in Electronic Health Records MIE 2005, Geneva Dr. W. Ceusters European Centre for Ontological.
ECO R European Centre for Ontological Research Ontology for indexing electronic patient records. There is only one right way: Referent Tracking ! STIC-Santé.
Validity and utility of theoretical tools - does the systematic review process from clinical medicine have a use in conservation? Ioan Fazey & David Lindenmayer.
Introduction to research
New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U.
Health IT Workforce Curriculum Version 1.0 Fall Networking and Health Information Exchange Unit 4a Basic Health Data Standards Component 9/Unit.
New York State Center of Excellence in Bioinformatics & Life Sciences R T U Discovery Seminar /UU – Spring 2008 Translational Pharmacogenomics: Discovering.
New York State Center of Excellence in Bioinformatics & Life Sciences R T U MIE Tutorial Biomedical Ontologies: The State of the Art (Part 2) Introduction.
Chapter 1 Overview of Databases and Transaction Processing.
New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U.
New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U.
Research Design
1 Standards and Ontology Barry Smith
Knowledge Representation Part I Ontology Jan Pettersen Nytun Knowledge Representation Part I, JPN, UiA1.
Department of Psychiatry, University at Buffalo, NY, USA
Research using Registries
NeurOn: Modeling Ontology for Neurosurgery
European Centre for Ontological Research
Achieving Semantic Interoperability of Cancer Registries
Towards the Information Artifact Ontology 2
Werner CEUSTERS a, Peter ELKIN b and Barry SMITH a, c
Structured Electronic Health Records and Patient Data Analysis: Pitfalls and Possibilities. January 7, 2013 Farber Hal G-26, University at Buffalo, South.
Werner Ceusters & Shahid Manzoor
Ontology in 15 Minutes Barry Smith.
© 2012 The McGraw-Hill Companies, Inc.
Ontology in 15 Minutes Barry Smith.
Principles of Referent Tracking BMI714 Course – Spring 2019
Presentation transcript:

1 The Ontologically Privileged Status of the Past Barry Smith

2 Universals vs. instances Assertions in scientific texts pertain to universals in reality Assertions in a lab report pertain (also) to instances of these universals

3 Universals are those invariants in reality which make possible the use of general terms in scientific inquiry the use of standardized therapies in clinical care the use of standardized procedures in business transactions...

4 universalsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records, lab reports, X-ray images macroeconomic surveys credit card transaction records databases

5 universals / conceptsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records macroeconomic surveys credit card transaction records databases relate indiscriminately to past, present and future

6 universals / conceptsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records, lab reports, X-ray images macroeconomic surveys credit card transaction records relate only to the past

7 universalsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records macroeconomic surveys credit card transaction records databases

8 universals / conceptsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records macroeconomic surveys credit card transaction records databases

9 UMLS Semantic Network

10 Pleural Cavity Pleural Cavity Interlobar recess Interlobar recess Mesothelium of Pleura Mesothelium of Pleura Pleura(Wall of Sac) Pleura(Wall of Sac) Visceral Pleura Visceral Pleura Pleural Sac Parietal Pleura Parietal Pleura Anatomical Space Organ Cavity Organ Cavity Serous Sac Cavity Serous Sac Cavity Anatomical Structure Anatomical Structure Organ Serous Sac Mediastinal Pleura Mediastinal Pleura Tissue Organ Part Organ Subdivision Organ Subdivision Organ Component Organ Component Organ Cavity Subdivision Organ Cavity Subdivision Serous Sac Cavity Subdivision Serous Sac Cavity Subdivision Foundational Model of Anatomy

11 Pleural Cavity Pleural Cavity Interlobar recess Interlobar recess Mesothelium of Pleura Mesothelium of Pleura Pleura(Wall of Sac) Pleura(Wall of Sac) Visceral Pleura Visceral Pleura Pleural Sac Parietal Pleura Parietal Pleura Anatomical Space Organ Cavity Organ Cavity Serous Sac Cavity Serous Sac Cavity Anatomical Structure Anatomical Structure Organ Serous Sac Mediastinal Pleura Mediastinal Pleura Tissue Organ Part Organ Subdivision Organ Subdivision Organ Component Organ Component Organ Cavity Subdivision Organ Cavity Subdivision Serous Sac Cavity Subdivision Serous Sac Cavity Subdivision part_of is_a

12 Gene Ontology

13 Gene Ontology

14 Holy grail of biomedical informatics = integration of genomic and EHR data Main obstacles 1. Poor facility for dealing with time and instances / particulars in current ontologies 2. Poor facility for dealing with instances / particulars in current clinical record systems

15 Current ontologies are about meanings (‘concepts’, ‘conceptualizations’)

16 The Ontologically Privileged Status of Universals

17 The Ontologically Privileged Status of Universals (a.k.a. Concepts)

18 ? The concept diabetes mellitus becomes ‘associated with a diabetic patient’ concept patient concept diabetes what it is on the side of the patient ?

19 ? The concept diabetes mellitus becomes ‘associated with a diabetic patient’ concept patient concept diabetes what it is on the side of the patient ? What is the relation here? Not a relation between concepts

20 A contains B =def the concept A stands in a containment relation to the concept B A causes B =def the concept A stands in a causative relation to the concept B A is_a B =def. ‘A’ is more specific in meaning than ‘B’

21 GALEN vomitus contains carrot

22 UMLS Semantic Network: Food causes Experimental Model of Disease Biomedical or Dental Material causes Mental or Behavioral Dysfunction Manufactured Object causes Disease or Syndrome

23 vomitus contains carrot The authors of ontologies have not paid attention to the question whether these are all or some assertions

24 because they have not paid attention to instances some instances of vomitus contain instances of carrot all instances of vomitus contain instances of carrot

25 IFOMIS proposal: move from associative relations between concepts/meanings to strictly defined relations between the universals (types, kinds) in reality embraced also by Gene Ontology Consortium

26 Key idea Ontological relations like contains, part_of, causes are relations between universals, but to define them properly we need to take account of instances and of time

27 Three kinds of relations : is_a, part_of,... : this throb here and now instance_of the class throb : Mary’s heart part_of Mary at t

28 part_of A part_of B =def. given any particular a and any time t, if a is an instance of A at t, then there is some instance b of B such that a is an instance-level part_of b at t HAS ALL-SOME FORM

29 transformation_of c at t 1 C c at t C 1 time same instance mature RNA transformation_of pre-RNA adult transformation_of child

30 transformation_of A transformation_of B =def for all a, t, if a is an instance of A at t then there is some t´ earlier than t which is such that a is an instance of B at t´ HAS ALL-SOME FORM

31 transformation_of in short: A transformation_of B =def. any instance of A was at some earlier time an instance of B Contrast: A transforms_into B child transforms_into adult The ontologically privileged status of relations pointing towards the past

32 C c at t c at t 1 C 1 embryological development

33 C c at t c at t 1 C 1 tumor development

34 Advantages of the methodology of enforcing commonly accepted coherent definitions promote quality assurance (better coding) guarantee automatic reasoning across ontologies and across data at different granularities yields direct connection to times and instances in EHR

35 The story of Jane Smith (with thanks to Werner Ceusters)

36 Jane’s favourite supermarket July 4th, 1990: Jane goes shopping: The freezer section of Jane’s favourite supermarket The only available warning sign used outside A very suspiciously shaped upper leg

37 A visit to the hospital City Health Centre Dr. Peters (City HC) Dr. Longley

38 Diagnosis: a severe spiral fracture of the femur

39 The City HC’s medical record captures in a structured form all of the ‘clinically significant’ information in the narrative notes Rector AL, Nowlan WA, Kay S, Goble CA, Howkins TJ. A framework for modelling the electronic medical record. Methods Inf Med Apr;32(2):

40 Structured Medical Record 04/07/1990 – 17:10Dr. Peters Jane Smith Orthopedics Emergency visit: 04/07/1990 – Severe Left upper leg Since fall on floor Constant closed fracture of shaft of femur fracture, closed, spiral

41 CityHC’s representation formalism for statements in records Occurrences: “ are specific occurrences of individuals and must be situated in space and time. The most important group of occurrences are observations — i.e. agents ’ observations of individuals. ”

42 City HC’s EHR model

43 Rector et al: “Every occurrence level statement concerning the Jane Smith’s Fracture of the Femur is an observation of the corresponding individual.” “The existence of the individual Jane Smith’s Fracture of Femur does not imply that Jane Smith has, or has ever had, a fracture of the femur, but merely that some observation has been made about Jane Smith regarding a fracture of the femur.” “(The only observation recorded about Jane Smith’s Fracture of the Femur might be that she did not have it.)”

/07/ closed fracture of shaft of femur /07/ Fracture, closed, spiral /07/ closed fracture of shaft of femur /07/ Accident in public building (supermarket) /07/ Essential hypertension /12/ benign polyp of biliary tract /03/ closed fracture of shaft of femur /03/ Accident in public building (supermarket) /04/ Other lesion on other specified region /05/ Essential hypertension 29822/08/ Closed fracture of radial head 29822/08/ Accident in public building (supermarket) /04/ closed fracture of shaft of femur /04/ Essential hypertension PtIDDateObsCodeNarrative /12/ malignant polyp of biliary tract Same patient, same hypertension code: Same (numerically identical) hypertension ? Different patients, same fracture codes: Same (numerically identical) fracture ? Same patient, different dates, same fracture codes: same (numerically identical) fracture ? Same patient, same date, 2 different fracture codes: same (numerically identical) fracture ? Problems Different patients. Same supermarket? Maybe the same (irrelevant ?) freezer section ? Or different supermarkets, but always in the freezer sections ? Same patient, different dates, Different codes. Same (numerically identical) polyp ?

45 Main problems of EHRs Statements refer only implicitly to the concrete entities about which they give information. Codes are general: they tell us only that some instance of the class the codes refer to, is referred to in the statement, but not what instance precisely. Mixing up the act of observation and the thing observed. Mixing up statements and the entities these statements refer to.

46 Consequences Difficult to: –count the number of (numerically) different diseases Bad statistics on incidence, prevalence,... Bad basis for health cost containment –relate (numerically the same or different) causal factors to disorders: –Dangerous public places (specific work floors, swimming pools), HIV contaminated blood from donors, food from unhygienic source,... Hampers prevention

47 Proposed solution: Referent Tracking Purpose: –explicit reference to the concrete individual entities relevant to the accurate description of each patient’s condition, therapies, outcomes,... Method: –Introduce an Instance Unique Identifier (IUI) for each relevant particular / instance

48 CUI (coo-ey): Concept Unique Identifier (e.g. a SNOMED code) UUI (oo-ey): Universal Unique Identifier IUI (you-ey): Instance Unique Identifier (e.g. a Social Security Number)

49 Referent tracking a response to the hard NLP problem of reference resolution in running text

50 Ontology An ontology is a representation of some pre- existing domain of reality which (1) reflects the properties of the objects within its domain in such a way that there obtains a systematic correlation between reality and the representation itself, (2) is intelligible to a domain expert (3) is formalized in a way that allows it to support automatic information processing

51 Basic Formal Ontology ContinuantsOccurrents / Events endure identically through time while undergoing changes, including gaining and losing parts unfold themselves through time in successive temporal phases

52 Basic Formal Ontology ContinuantsOccurrents Independent: things, substances Always dependent on their bearers (participants/agents) Dependent: functions, qualities, shapes, roles...

53 An ontological analysis continuants City HC The freezer section of Jane’s favourite supermarket Jane’s left femur Jane’s left femur fracture Jane Smith Dr. Peters Jane’s left femur Jane’s fracture’s image Dr. Longley City HC’s EHR system t Universals EHR system HC Freezer section Person Femur Fracture Image Jane’s falling Jane’s femur breaking Dr. Peter’s examination of Jane’s fracture Dr. Peter’s ordering of an X-ray Shooting the pictures of Jane’s leg occurrents Jane’s fracture’s healing Dr. Peter’s diagnosis making Jane dies Freezer section dismantled Dr. Longley’s examination of Jane’ s fracture

54 Essentials of Referent Tracking Deciding what particulars should receive a IUI; Finding out whether or not a particular has already been assigned a IUI; Using IUIs in the EHR, resolve issues concerning the syntax and semantics of statements containing IUIs; Correcting errors in the assignment of IUIs; Dealing with relation between IUI-identified instances and corresponding universals

55 Architecture of a Referent Tracking System (RTS) Ideally set up to be as geographically broad in scope as possible Services: –IUI generator –IUI repository: statements about assignments and reservations –Referent Tracking Database (RTDB): statements relating instances to instances and universals

56 IUI generation Universally Unique IDs: –recently standardized through ISO/IEC :2004, –specifies format and generation rules enabling users to produce 128-bit identifiers that have a very high probability of being globally unique –Meaningless strings

57 IUI assignment = an act of labelling carried out by the first cognitive agent needing to acknowledge the existence of a particular it has information about cognitive agent: –A person –An organisation –A device or software agent, e.g. Bank note printer Image analysis software Credit card transaction reader

58 Criteria for IUI assignment (1) The particular’s existence must be determined: –Easy for persons in front of you, for body parts, for X- ray images –More difficult for subjective symptoms –No need to know what the particular exactly is, i.e. which universal it instantiates –No need to be able to point to it precisely One bee out of a particular swarm that stung the patient

59 Criteria for IUI assignment (2) The particular should not have been already determined as something else: Morning star / evening star May not have already been assigned a IUI. Must be salient/relevant/significant: Personal decision, (scientific) community guideline,... Reflects a possibility offered by the EHR system Once a IUI has been assigned, everybody making statements about this particular should use it

60 IUI assignments The act of IUI assignment can be represented as: d a = IUI of the registering agent A i = p a = IUI of the author of the assertion p p = IUI of the particular t ap = time of assignment c = optional description t d = time of registering A i in the IUI-repository Neither ‘t d ’ nor ‘t ap ’ give any information about when #p p began to exist.

61 Management of IUI-repository Adequate safety and security provisions –Access authorisation, control, read/write,... –Pseudonymisation Deletionless but with facilities for correcting mistakes. Central management with adequate search facilities.

62 Representation in the EHR Relevant particulars referred to using IUIs Relationships that obtain between particulars at time t expressed using strictly defined relations from an ontology Statements describing for each particular at time t of what universal from an ontology it is an instance CityHCDr. Peters Jane Smith Jane Smith’s Fracture Of Femur Fracture Of Femur Severe Spiral Jane Smith’s consultation with Dr. Peters at City HC on 4th July 1990 Dr. Peters’ assessment of Jane Smith’s fracture of femur at City HC on 4th July 1990 Jane Smith’s Fracture Of Femur’s severity Jane Smith’s Fracture Of Femur’s shape 4th July 1990

63 PtoP (particular to particular) statements ordered sextuples of the form: s a the IUI of the author of the statement, t a the time when the statement is made, r a relationship obtaining between the particulars referred to in P, o the ontology from which r is taken, P an ordered list of the IUIs of the particulars between which r obtains, t r the time at which r obtains.

64 PtoCL (particular to class) statements s a the IUI of the author of the statement, t a the time when the statement is made, inst an instance relationship available in o obtaining between p and cl, o the ontology from which inst and cl are taken, p the IUI of the particular whose inst relationship with cl is asserted, cl the class in o to which p enjoys the inst relationship, t r the time at which the relationship obtains.

65 PtoCO (particular to concept code) statements s a the IUI of the author of the statement, t a the time when the statement is made, cbs the concept-based system from which co is taken, p the IUI of the particular which the author associates with co, co the concept-code in cbs which the author associates with p, t r a reference to the time at which the author considers the association appropriate,

66 Interpretation of PtoCO statements Such statements tell us that within the linguistic and scientific community in which cbs is used, the terms associated with co may be used to denote p

67 A SNOMED-CT example #IUI-0945: author of the statement #IUI-1921: the left testicle of patient #IUI : the SNOMED concept-code to which “left testis” is (in SNOMED) attached as term So we can denote #IUI-1921 by means of that left testis that entire left testis that testicle, that male gonad, that testis that genital structure that physical anatomical entity BUT NOT: that SNOMED-CT concept

68 Pragmatics of IUIs in EHRs IUI assignment requires (just a bit) more effort compared to current use of general codes from concept-based systems –A search for concept-codes is replaced by a search for the appropriate IUI using exactly the same mechanisms Browsing Code-finder software Auto-coding software (CLEF NLP software Andrea Setzer) –With some IUIs there comes a wealth of already registered information

69 IUIs in structured EHRs 04/07/1990 – 17:10Dr. Peters Jane Smith Orthopedics Emergency visit: 04/07/1990 – Severe Left upper leg Since fall on floor Constant closed fracture of shaft of femur fracture, closed, spiral Replaced by the IUI for the patient’s left upper leg That IUI might be found by using “left upper leg” as a search term to query the RTDB Both replaced by the IUI for that fracture By means of PTCO statements is the IUI related to the SNOMED-codes

70 Advantage: better reality representation /07/ closed fracture of shaft of femur /07/ Fracture, closed, spiral /07/ closed fracture of shaft of femur /07/ Accident in public building (supermarket) /07/ Essential hypertension /12/ benign polyp of biliary tract /03/ closed fracture of shaft of femur /03/ Accident in public building (supermarket) /04/ Other lesion on other specified region /05/ Essential hypertension 29822/08/ Closed fracture of radial head 29822/08/ Accident in public building (supermarket) /04/ closed fracture of shaft of femur /04/ Essential hypertension PtIDDateObsCodeNarrative /12/ malignant polyp of biliary tract IUI-001 IUI-003 IUI-004 IUI-005 IUI-007 IUI-002 IUI-012

71 Other Advantages Mappings between ontologies and coding systems created as by-product of tracking –Descriptions about the same particular using different systems e.g. in different hospitals Quality control of ontologies and concept- based systems –Systematically inconsistent descriptions within or across terminologies may indicate poor definition of the respective terms

72 Other advantages credit card transaction records already constitute a referent tracking database can give a global picture of economic patterns in a given society Our proposal will provide for something analogous in the realm of healthcare

73 Other Advantages Referent tracking can be used in decision support when making diagnoses We can consider the results of assignment of different clinical codes to one and the same collection of IUIs assembled over a period (and thereby uncover new patterns of symptoms, e.g. in a case of multiple sclerosis)

74 Conclusion Referent tracking can solve a number of problems in an elegant way. Existing (or emerging) technologies can be used for the implementation. Old technologies can play an interesting role. Big Brother feeling is to be expected, but with adequate measures easy to fight. Pilot is being established

75 Generalizing beyond healthcare 1) intelligence/security: tracking movements of people and goods 2) tracking copies of papers, music-files, over the internet. Numbers can be assigned by producers of the files, but also by the people who forward them (buying and selling numbers) 3) creation of tag-technology for all forms of hardware/collectibles 4) gaming (turning spam into a game): collaborative, distributed story writing 5) gambling/play mixture: a question is asked, and every tenth, twentieth,... person who calls the TV studio is allowed to answer. But calling costs you $1. Referent tracking allows this idea to be realized over /internet.