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Sharing Data while Keeping Control

This article explores the ontology of data and the importance of keeping track of what is generic and specific in data organization. It discusses referent tracking and the challenges of representing data accurately. The article emphasizes the need for a realism-based ontology and the distinctions between data and what data are about. It also discusses the crucial role of referent tracking in maintaining control and accuracy in data sharing.

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Sharing Data while Keeping Control

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  1. Sharing Data while Keeping Control Werner CEUSTERS, MD Director, Ontology Research Group Center of Excellence in Bioinformatics and Life Sciences University at Buffalo, NY, USA

  2. 1959 - 2010 Short personal history ? 1977 2006 2004 1989 1992 2002 1995 1998 1993

  3. Outline • The ontology of data • representations of reality • Realism-based ontology • keeping track of what is generic • Referent Tracking • keeping track of what is specific • Referent Tracking for data management • keeping track of data and of what they are about

  4. data organization model development further R&D (instrument and study optimization) add verify use Δ= outcome Generic beliefs application Data generation and use observation & measurement

  5. data organization First- Order Reality is about model development Representation further R&D (instrument and study optimization) add verify use Δ= outcome Generic beliefs application A crucial distinction: data and what they are about observation & measurement

  6. A non-trivial relation Referent Reference

  7. A non-trivial relation Concept? Referent Reference

  8. Some key questions • What referents, if any at all, are depicted by a putative reference? • How do changes at the level of the referents correspond with changes in the collection of references? • If references are transmitted, how can the receiver know what referents are depicted? Referent Reference

  9. Realism-based Ontology Some answers are in Realism-based Ontology • There is an external reality which is ‘objectively’ the way it is; • That reality is accessible to us; • We build in our brains cognitive representations of reality; • We communicate with others about what is there, and what we believe there is there. Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, Biomedical Ontology in Action, November 8, 2006, Baltimore MD, USA

  10. Realism makes crucial distinctions • Between data and what data are about: • Level 1 entities (L1): • everything what exists or existed • some are referents (‘are’ used informally) • some are L2, some are L3, none are L2 and L3 • Level 2 entities (L2): beliefs • all are L1 • some are about other L1-entities but none about themselves • Level 3 entities (L3): expressions • all are L1, none are L2 • some are about other L1-entities and some about themselves

  11. Realism makes crucial distinctions • Between data and what data are about; • Between continuants and occurrents: • obvious differences: • a person versus his life • an elevator versus his going up and down • space versus time • more subtle differences (inexistent for flawed models e.g. HL7-RIM): • observation (data-element) versus observing • diagnosis versus making a diagnosis • message versus transmitting a message

  12. Realism makes crucial distinctions • Between data and what data are about; • Between continuants and occurrents; • Between what is generic and what is specific …

  13. data organization First- Order Reality is about model development Representation further R&D (instrument and study optimization) add verify use Δ= outcome Generic beliefs application Data and what they are about observation & measurement

  14. Generic versus specific referents data organization is about model development observation & measurement specific is about add verify use generic Δ= outcome Generic beliefs is about

  15. PtID Date SNOMED CT code Narrative 5572 5572 5572 298 5572 5572 298 2309 47804 5572 5572 12/07/1990 01/04/1997 12/07/1990 17/05/1993 22/08/1993 21/03/1992 22/08/1993 04/07/1990 01/04/1997 04/07/1990 03/04/1993 81134009 9001224 26442006 9001224 79001 79001 9001224 26442006 2909872 58298795 26442006 Essential hypertension Accident in public building (supermarket) Closed fracture of radial head closed fracture of shaft of femur Essential hypertension Accident in public building (supermarket) Other lesion on other specified region closed fracture of shaft of femur Fracture, closed, spiral closed fracture of shaft of femur Accident in public building (supermarket) 5572 04/07/1990 79001 Essential hypertension 0939 24/12/1991 255174002 benign polyp of biliary tract 2309 21/03/1992 26442006 closed fracture of shaft of femur 0939 20/12/1998 255087006 malignant polyp of biliary tract Using generic representations for specific entities is inadequate

  16. ‘person’ ‘drug’ ‘insulin’ ‘W. Ceusters’ ‘my sugar’ DIAGNOSIS my doctor’s work plan my doctor’s diagnosis INDICATION my doctor’s computer my doctor PATHOLOGICAL STRUCTURE PERSON me my NIDDM DISEASE DRUG my blood glucose level PORTION OF INSULIN MOLECULE Basic Formal Ontology Referent Tracking The representational square Generic Generic Specific Specific L3. Representation L2. Beliefs (knowledge) L1. First-order reality

  17. A division of labor • Basic Formal Ontology (BFO), a specific embodiment of realism-based ontology, aims to represent what is generic. • Referent Tracking aims to represent what is specific.

  18. Referent Tracking • A paradigm under development since 2005, • based on Basic Formal Ontology, • designed to keep track of relevant portions of reality and what is believed and communicated about them, • enabling adequate use of realism-based ontologies, terminologies, thesauri, and vocabularies, • originally conceived to track particulars on the side of the patient and his environment denoted in his EHR, • but since then studied in and applied to a variety of domains, • and now evolving towards tracking absolutely everything.

  19. Stead and Lin’s ‘Principles for Success’ in Health IT • Evolutionary change • Radical change: • Principle 6: Architect Information and Workflow Systems to Accommodate Disruptive Change • Organizations should architect health care IT for flexibility to support disruptive change rather than to optimize today’s ideas about health care. • Principle 7: Archive Data for Subsequent Re-interpretation • Vendors of health care IT should provide the capability of recording any data collected in their measured, uninterpreted, original form, archiving them as long as possible to enable subsequent retrospective views and analyses of those data.NOTE NOTE: ‘See, for example, Werner Ceusters and Barry Smith, “Strategies for Referent Tracking in Electronic Health Records” Journal of Biomedical Informatics 39(3):362-378, June 2006.’ Willam W. Stead and Herbert S. Lin, editors; Committee on Engaging the Computer Science Research Community in Health Care Informatics; National Research Council. Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions (2009)

  20. Key feature of Referent Tracking • The assignment of an Instance Unique Identifier (IUI) to each entity in reality (i.e. a referent) about which a representation (i.e. a reference) is maintained in some system. • Representations are linked by means of these IUIs following principles established in realism-based ontology.

  21. PtID Date SNOMED CT Code Narrative IUI-001 5572 5572 5572 298 2309 47804 5572 298 5572 5572 5572 03/04/1993 04/07/1990 04/07/1990 01/04/1997 12/07/1990 01/04/1997 22/08/1993 22/08/1993 21/03/1992 17/05/1993 12/07/1990 9001224 9001224 26442006 9001224 26442006 26442006 79001 79001 2909872 81134009 58298795 closed fracture of shaft of femur Essential hypertension Accident in public building (supermarket) closed fracture of shaft of femur Essential hypertension Accident in public building (supermarket) Accident in public building (supermarket) closed fracture of shaft of femur Closed fracture of radial head Fracture, closed, spiral Other lesion on other specified region IUI-001 IUI-001 IUI-007 5572 04/07/1990 79001 IUI-005 Essential hypertension 0939 24/12/1991 255174002 IUI-004 benign polyp of biliary tract 2309 21/03/1992 26442006 IUI-002 closed fracture of shaft of femur IUI-007 IUI-006 IUI-005 IUI-003 IUI-007 IUI-012 IUI-005 0939 20/12/1998 255087006 IUI-004 malignant polyp of biliary tract Codes for ‘types’ AND identifiers for instances 7 distinct disorders

  22. The shift envisioned • From: • ‘this human being is a 40 year old patient with a stomach tumor’ • To (something like): • ‘this-1 on which depends this-2 and this-3 has this-4’, where • this-1 instanceOf human being at t1 • this-2 instanceOf age-of-40-years at t2 • this-2 qualityOf this-1 at t2 • this-3 instanceOf patient-role at t3 • this-3 roleOf this-1 at t3 • this-4 instanceOf tumor at t4 • this-4 partOf this-5 at t6 • this-5 instanceOf stomach at t7 • this-5 partOf this-1 at t8 • …

  23. The shift envisioned • From: • ‘this human being is a 40 year old patient with a stomach tumor’ • To (something like): • ‘this-1 on which depends this-2 and this-3 has this-4’, where • this-1 instanceOf human being at t1 • this-2 instanceOf age-of-40-years at t2 • this-2 qualityOf this-1 at t2 • this-3 instanceOf patient-role at t3 • this-3 roleOf this-1 at t3 • this-4 instanceOf tumor at t4 • this-4 partOf this-5 at t6 • this-5 instanceOf stomach at t7 • this-5 partOf this-1 at t8 • … denotators forparticulars(specific entities)

  24. The shift envisioned • From: • ‘this human being is a 40 year old patient with a stomach tumor’ • To (something like): • ‘this-1 on which depends this-2 and this-3 has this-4’, where • this-1instanceOf human being at t1 • this-2instanceOf age-of-40-years at t2 • this-2qualityOf this-1 at t2 • this-3instanceOf patient-role at t3 • this-3roleOf this-1 at t3 • this-4instanceOf tumor at t4 • this-4partOf this-5 at t6 • this-5instanceOf stomach at t7 • this-5partOf this-1 at t8 • … denotators for appropriaterelations

  25. The shift envisioned • From: • ‘this human being is a 40 year old patient with a stomach tumor’ • To (something like): • ‘this-1 on which depends this-2 and this-3 has this-4’, where • this-1instanceOfhuman being at t1 • this-2instanceOfage-of-40-years at t2 • this-2qualityOfthis-1 at t2 • this-3instanceOfpatient-role at t3 • this-3roleOfthis-1 at t3 • this-4instanceOftumor at t4 • this-4partOfthis-5 at t6 • this-5instanceOfstomach at t7 • this-5partOfthis-1 at t8 • … denotators foruniversals or classes (what is generic)or particulars

  26. The shift envisioned • From: • ‘this human being is a 40 year old patient with a stomach tumor’ • To (something like): • ‘this-1 on which depends this-2 and this-3 has this-4’, where • this-1instanceOfhuman beingat t1 • this-2instanceOfage-of-40-yearsat t2 • this-2qualityOfthis-1at t2 • this-3instanceOfpatient-roleat t3 • this-3roleOfthis-1at t3 • this-4instanceOftumorat t4 • this-4partOfthis-5at t6 • this-5instanceOfstomachat t7 • this-5partOfthis-1at t8 • … time periods (for continuants) when the relationships hold

  27. instance-of at t caused by #105 Relevance: the way RT-representations interact with representations of generic portions of reality

  28. Referent Tracking based data warehousing

  29. Referent Tracking System Environment

  30. Networks of Referent Tracking systems

  31. General principles of RT-enabled data warehousing (1) • Unique identifier for: • each data-element and combinations thereof (L3), • what the data-element is about (L1), • each generated copy of an existing data-element (L3), • each transaction involving data-elements (L1); • Identifiers centrally managed in RTS; • Exclusive use of ontologies for type descriptions following OBO-Foundry principles; • Centrally managed data dictionaries, data-ownership, exchange criteria.

  32. General principles of RT-enabled data warehousing (2) • Central inventory of ‘attributes’ but peripheral maintenance of ‘values’; • Identifiers function as pseudonyms: • centrally known that for person IUI-1 there are values about instances of UUI-2 maintained by researcher/clinician IUI-3 for periods IUI-4, IUI-5, … • Disclosure of what the identifiers stand for based on need and right to know; • Generation of off-line datasets for research with transaction-specific identifiers for each element.

  33. Feedback to clinical care • Finding ‘similar’ patient cases: • suggestions for prevention, investigation, treatment; • ‘Outbreak’ detection; • Comparing outcomes; • related to disorders, providers, treatments, … • Links to literature; • Clinical trial selection; • …

  34. Assigning IUIs #8: this spreadsheet #9: this column of #8 #1: this lady #10: format of entries in #9 #7: #1’s last name #2: “Simpson” #5: representation of #4’ at 2010-03-31:08.30 #4: #1’s mass #3: “Smith” #6: representation of #4’ at 2010-04-14:09.57 #11: owner of #8 #12: copy of #8 send to #13 …

  35. Using IUIs #8: this spreadsheet #9: this column of #8 #1 has-name #7 at … #10: format of entries in #9 #7 represented-by #2 at t1 #2: “Simpson” #5: representation of #4’ at 2010-03-31:08.30 #7 represented-by #3 at t2 #3: “Smith” #6: representation of #4’ at 2010-04-14:09.57 #4 inheres-in #1 since … #11: owner of #8 #4 represented by #5 since … #12: copy of #8 send to #13 …

  36. Conclusion: a general framework for unambiguous representation L1 R L2 L3 symbolizations beliefs ‘about’

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