Transcript Document
R T U New York State Center of Excellence in Bioinformatics & Life Sciences MIE Tutorial Biomedical Ontologies: The State of the Art (Part 2) Introduction to Referent Tracking August 30, 2009 Sarajevo, Bosnia - Herzegovina Werner CEUSTERS Center of Excellence in Bioinformatics and Life Sciences Ontology Research Group University at Buffalo, NY, USA R T U New York State Center of Excellence in Bioinformatics & Life Sciences Tutorial overview • Setting the scene: a rough description of what Referent Tracking is and why it is important • Review the basics of BFO relevant to RT • The crucial distinction between representations and what they represent • Implementation of RT systems • Examples of use R T U New York State Center of Excellence in Bioinformatics & Life Sciences Prologue: Referent Tracking: What and Why ? R T U New York State Center of Excellence in Bioinformatics & Life Sciences What is 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, not only particulars, but also universals. R T U New York State Center of Excellence in Bioinformatics & Life Sciences Source of all data Reality ! R T U New York State Center of Excellence in Bioinformatics & Life Sciences Ultimate goal of Referent Tracking A digital copy of the world R T U New York State Center of Excellence in Bioinformatics & Life Sciences Requirements for this digital copy • R1: • R2 A faithful representation of reality … of everything that is digitally registered, what is generic scientific theories what is specific what individual entities exist and how they relate • R3: • R4 … throughout reality’s entire history, … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ... R T U New York State Center of Excellence in Bioinformatics & Life Sciences In fact … the ultimate crystal ball R T U New York State Center of Excellence in Bioinformatics & Life Sciences The ‘binding’ wall I don’t want a cartoon of the world R T U New York State Center of Excellence in Bioinformatics & Life Sciences Terminologies for ‘unambiguous representation’ ??? PtID Date ObsCode Narrative 5572 04/07/1990 26442006 closed fracture of shaft of femur 5572 04/07/1990 81134009 Fracture, closed, spiral 5572 12/07/1990 26442006 closed fracture of shaft of femur 5572 12/07/1990 9001224 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 2309 21/03/1992 9001224 Accident in public building (supermarket) 47804 03/04/1993 58298795 Other lesion on other specified region 5572 17/05/1993 79001 Essential hypertension 298 22/08/1993 2909872 Closed fracture of radial head 298 22/08/1993 9001224 Accident in public building (supermarket) 5572 01/04/1997 26442006 closed fracture of shaft of femur 5572 01/04/1997 79001 Essential hypertension 0939 20/12/1998 255087006 malignant polyp of biliary tract R T U New York State Center of Excellence in Bioinformatics & Life Sciences Terminologies for ‘unambiguous representation’ ??? PtID Date ObsCode Narrative 5572 04/07/1990 26442006 closed fracture of shaft of femur 5572 04/07/1990 81134009 Fracture, closed, spiral 5572 12/07/1990 26442006 closed fracture of shaft of femur 5572 12/07/1990 9001224 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 2309 21/03/1992 9001224 47804 03/04/1993 58298795 5572 17/05/1993 79001 298 22/08/1993 2909872 298 22/08/1993 9001224 5572 01/04/1997 26442006 closed fracture of shaft of femur 5572 01/04/1997 79001 Essential hypertension 0939 20/12/1998 255087006 malignant polyp of biliary tract If two different fracture codes Accident in public building (supermarket) are used in relation to Other lesion on other specified region observations made on the same Essential hypertension day for the same patient, do they Closed fracture of radial head denote the same fracture ? Accident in public building (supermarket) R T U New York State Center of Excellence in Bioinformatics & Life Sciences Terminologies for ‘unambiguous representation’ ??? PtID Date ObsCode Narrative 5572 04/07/1990 26442006 closed fracture of shaft of femur 5572 04/07/1990 81134009 Fracture, closed, spiral 5572 12/07/1990 26442006 closed fracture of shaft of femur 5572 12/07/1990 9001224 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 2309 21/03/1992 9001224 47804 03/04/1993 58298795 5572 17/05/1993 79001 298 22/08/1993 2909872 298 22/08/1993 9001224 If the same fracture closed fracturecode of shaft of isfemur used for the Accident in public building (supermarket) same patient on Other lesion on other specified region different dates, can Essential hypertension these codes Closed fracture of radial head denote the Accident in public same building (supermarket) fracture? 5572 01/04/1997 26442006 closed fracture of shaft of femur 5572 01/04/1997 79001 Essential hypertension 0939 20/12/1998 255087006 malignant polyp of biliary tract R T U New York State Center of Excellence in Bioinformatics & Life Sciences Terminologies for ‘unambiguous representation’ ??? PtID Date ObsCode Narrative 5572 04/07/1990 26442006 closed fracture of shaft of femur 5572 04/07/1990 81134009 Fracture, closed, spiral 5572 12/07/1990 26442006 closed fracture of shaft of femur 5572 12/07/1990 9001224 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 2309 21/03/1992 9001224 Accident in public building (supermarket) 47804 03/04/1993 58298795 5572 17/05/1993 298 22/08/1993 298 22/08/1993 lesion on other specified region Can the sameOther fracture code used in relation 79001 Essential hypertension to two different patients denote the same 2909872 Closed fracture of radial head 9001224 fracture? Accident in public building (supermarket) 5572 01/04/1997 26442006 closed fracture of shaft of femur 5572 01/04/1997 79001 Essential hypertension 0939 20/12/1998 255087006 malignant polyp of biliary tract R T U New York State Center of Excellence in Bioinformatics & Life Sciences Terminologies for ‘unambiguous representation’ ??? PtID Date ObsCode Narrative 5572 04/07/1990 26442006 closed fracture of shaft of femur 5572 04/07/1990 81134009 Fracture, closed, spiral 5572 12/07/1990 26442006 closed fracture of shaft of femur 5572 12/07/1990 9001224 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 2309 21/03/1992 9001224 Accident in public building (supermarket) 47804 5572 03/04/1993 58298795 Otherused lesion on other specified region Can two different tumor codes 17/05/1993 Essential hypertension in relation79001 to observations made on different 22/08/1993 2909872 Closed fracture of radial head dates for the same patient, 22/08/1993 9001224 Accident in public building (supermarket) denote same tumor ? 01/04/1997 the 26442006 closed fracture of shaft of femur 5572 01/04/1997 79001 Essential hypertension 0939 20/12/1998 255087006 malignant polyp of biliary tract 5572 298 298 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Terminologies for ‘unambiguous representation’ ??? PtID Date 5572 04/07/1990 5572 04/07/1990 5572 12/07/1990 5572 12/07/1990 5572 ObsCode Narrative closed of shaft of femur for the Do three references offracture ‘hypertension’ 81134009 Fracture, closed, spiral the same same patient denote three times 26442006 closed fracture of shaft of femur disease? 26442006 9001224 Accident in public building (supermarket) 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 2309 21/03/1992 9001224 Accident in public building (supermarket) 47804 03/04/1993 58298795 Other lesion on other specified region 5572 17/05/1993 79001 Essential hypertension 298 22/08/1993 2909872 Closed fracture of radial head 298 22/08/1993 9001224 Accident in public building (supermarket) 5572 01/04/1997 26442006 closed fracture of shaft of femur 5572 01/04/1997 79001 Essential hypertension 0939 20/12/1998 255087006 malignant polyp of biliary tract R T U New York State Center of Excellence in Bioinformatics & Life Sciences Can the same type of location code used in relation to three different ??? Terminologies for ‘unambiguous representation’ events denote the same location? PtID Date ObsCode Narrative 5572 04/07/1990 26442006 closed fracture of shaft of femur 5572 04/07/1990 81134009 Fracture, closed, spiral 5572 12/07/1990 26442006 closed fracture of shaft of femur 5572 12/07/1990 9001224 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 2309 21/03/1992 9001224 Accident in public building (supermarket) 47804 03/04/1993 58298795 Other lesion on other specified region 5572 17/05/1993 79001 Essential hypertension 298 22/08/1993 2909872 Closed fracture of radial head 298 22/08/1993 9001224 Accident in public building (supermarket) 5572 01/04/1997 26442006 closed fracture of shaft of femur 5572 01/04/1997 79001 Essential hypertension 0939 20/12/1998 255087006 malignant polyp of biliary tract R T U New York State Center of Excellence in Bioinformatics & Life Sciences How will we ever know ? PtID Date ObsCode Narrative 5572 04/07/1990 26442006 closed fracture of shaft of femur 5572 04/07/1990 81134009 Fracture, closed, spiral 5572 12/07/1990 26442006 closed fracture of shaft of femur 5572 12/07/1990 9001224 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 2309 21/03/1992 9001224 Accident in public building (supermarket) 47804 03/04/1993 58298795 Other lesion on other specified region 5572 17/05/1993 79001 Essential hypertension 298 22/08/1993 2909872 Closed fracture of radial head 298 22/08/1993 9001224 Accident in public building (supermarket) 5572 01/04/1997 26442006 closed fracture of shaft of femur 5572 01/04/1997 79001 Essential hypertension 0939 20/12/1998 255087006 malignant polyp of biliary tract R T U New York State Center of Excellence in Bioinformatics & Life Sciences The problem in a nutshell • Generic terms used to denote specific entities do not have enough referential capacity – Usually enough to convey that some specific entity is denoted, – Not enough to be clear about which one in particular. • For many ‘important’ entities, unique identifiers are used: – – – – UPS parcels Patients in hospitals VINs on cars … R T U New York State Center of Excellence in Bioinformatics & Life Sciences Fundamental goals of ‘our’ Referent Tracking 1. explicit reference to the concrete individual entities relevant to the accurate description of some portion of reality, ... Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78. R T U New York State Center of Excellence in Bioinformatics & Life Sciences Method: numbers instead of words – Introduce an Instance Unique Identifier (IUI) for each relevant particular (individual) entity 78 Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78. R T U New York State Center of Excellence in Bioinformatics & Life Sciences Codes for ‘types’ AND identifiers for instances PtID Date ObsCode Narrative 5572 04/07/1990 26442006 IUI-001 closed fracture of shaft of femur 5572 04/07/1990 81134009 IUI-001 Fracture, closed, spiral 5572 12/07/1990 26442006 IUI-001 closed fracture of shaft of femur 5572 12/07/1990 9001224 IUI-007 Accident in public building (supermarket) 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 2309 21/03/1992 9001224 IUI-007 Accident in public building (supermarket) 47804 03/04/1993 58298795 IUI-006 Other lesion on other specified region 5572 17/05/1993 79001 IUI-005 Essential hypertension 298 22/08/1993 2909872 IUI-003 Closed fracture of radial head 298 22/08/1993 9001224 IUI-007 Accident in public building (supermarket) 5572 01/04/1997 26442006 IUI-012 closed fracture of shaft of femur 5572 01/04/1997 79001 IUI-005 Essential hypertension IUI-004 malignant polyp of biliary tract 0939 20/12/1998 255087006 7 distinct disorders R T U New York State Center of Excellence in Bioinformatics & Life Sciences Therefore: Part 1: the Basics No (good) Referent Tracking without (good) Realism-based Ontology R T U New York State Center of Excellence in Bioinformatics & Life Sciences Basic axioms 1. There is an external reality which is ‘objectively’ the way it is; 2. That reality is accessible to us; 3. We build in our brains cognitive representations of reality; 4. 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 R T U New York State Center of Excellence in Bioinformatics & Life Sciences What is there ? The parts of BFO relevant for Referent Tracking (1) some universal instanceOf … some particular R T U New York State Center of Excellence in Bioinformatics & Life Sciences The shift envisioned • From: – ‘this human being is a 40 year old patient with a stomach tumor’ • To (something like): – ‘this-1 on which depend this-2 and this-3 has this-4’, where • • • • • • • • • • this-1 this-2 this-2 this-3 this-3 this-4 this-4 this-5 this-5 … instanceOf instanceOf qualityOf instanceOf roleOf instanceOf partOf instanceOf partOf human being … age-of-40-years … this-1 … patient-role … this-1 … tumor … this-5 … stomach … this-1 … R T U New York State Center of Excellence in Bioinformatics & Life Sciences The shift envisioned • From: – ‘this man is a 40 year old patient with a stomach tumor’ • To (something like): – ‘this-1 on which depend this-2 and this-3 has this-4’, where • • • • • • • • • • this-1 this-2 this-2 this-3 this-3 this-4 this-4 this-5 this-5 … instanceOf instanceOf qualityOf instanceOf roleOf instanceOf partOf instanceOf partOf human being … age-of-40-years … this-1 … patient-role … this-1 … tumor … this-5 … stomach … this-1 … denotators for particulars R T U New York State Center of Excellence in Bioinformatics & Life Sciences The shift envisioned • From: – ‘this man is a 40 year old patient with a stomach tumor’ • To (something like): – ‘this-1 on which depend this-2 and this-3 has this-4’, where • • • • • • • • • • this-1 this-2 this-2 this-3 this-3 this-4 this-4 this-5 this-5 … instanceOf instanceOf qualityOf instanceOf roleOf instanceOf partOf instanceOf partOf human being … age-of-40-years … this-1 … patient-role … this-1 … tumor … this-5 … stomach … this-1 … denotators for appropriate relations R T U New York State Center of Excellence in Bioinformatics & Life Sciences The shift envisioned • From: – ‘this man is a 40 year old patient with a stomach tumor’ • To (something like): – ‘this-1 on which depend this-2 and this-3 has this-4’, where • • • • • • • • • • this-1 this-2 this-2 this-3 this-3 this-4 this-4 this-5 this-5 … instanceOf instanceOf qualityOf instanceOf roleOf instanceOf partOf instanceOf partOf human being age-of-40-years this-1 patient-role this-1 tumor this-5 stomach this-1 … … … … … … … denotators for universals … … or particulars R T U New York State Center of Excellence in Bioinformatics & Life Sciences Relevance: the way RT-compatible systems ought to interact with representations of generic portions of reality instance-of at t caused #105 by R T U New York State Center of Excellence in Bioinformatics & Life Sciences What is there ? The parts of BFO relevant for Referent Tracking (2) some continuant universal instanceOf at some continuant particular some occurrent universal t instanceOf some occurrent particular R T U New York State Center of Excellence in Bioinformatics & Life Sciences The importance of temporal indexing malignant tumor benign tumor instanceOf at t1 instanceOf at t2 partOf at t1 this-4 partOf at t2 stomach instanceOf at t2 instanceOf at t1 this-1’s stomach R T U New York State Center of Excellence in Things&do change Bioinformatics Life Sciences indeed child adult vampire person t Living creature animal caterpillar butterfly R T U New York State Center of Excellence in Bioinformatics & Life Sciences The continuants relevant for Referent Tracking spatial region independent continuant dependent continuant specifically dependent continuant material object generically dependent continuant site information content entity … terminology ontology R T U New York State Center of Excellence in Bioinformatics & Life Sciences The occurrents relevant for Referent Tracking spatiotemporal region temporal region contiguous temporal region time instant time interval process scattered temporal region history R T U New York State Center of Excellence in Bioinformatics & Life Sciences Sorts of relations UtoU: isa, partOf(UU), … U1 U2 PtoU: instanceOf, lacks, denotes(PU)… P1 PtoP: partOf, denotes, … P2 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Putting the pieces together: what is there to track? dependent continuant material object t spacetime region history instanceOf t occupies my life some quality me … at t located-in at t spatial region temporal region t my 4D STR projectsOn at t some spatial region some temporal region R T U New York State Center of Excellence in Bioinformatics & Life Sciences Part 2: Let’s get more serious about ‘representation’ (in general) Beware !!! Colors don’t really matter but in what follows I used them in different ways than before. R T U New York State Center of Excellence in Bioinformatics & Life Sciences ‘Marriage’ … createdBy marriage of Bill and Hillary instanceOf marriage husbandIn spouseIn Bill Clinton husbandOf spouseOf instanceOf Hillary Clinton instanceOf human being R T U New York State Center of Excellence in Bioinformatics & Life Sciences Time and the Bill-Hillary marriage: what about the various some t’s ? … createdBy at some t exists at some t at some t marriage of Bill and Hillary instanceOf exists at some t marriage exists at some t at some t husbandIn at some t exists at some t spouseIn Bill Clinton exists at some t husbandOf spouseOf at some t at some t at some t instanceOf Hillary Clinton at some t exists at some t instanceOf human being R T U New York State Center of Excellence in Bioinformatics & Life Sciences Representation of the Bill-Hillary marriage … createdBy at some t exists at some t ‘instanceOf , ‘marriage of Bill and Hillary’ at some t exists at some t ‘marriage’ exists at some t ‘husbandIn at some t , ‘Bill Clinton’ exists at some t husbandOf spouseOf at some t at some t , ‘spouseIn at some t exists at some t at some t instanceOf ‘Hillary Clinton’ at some t exists at some t instanceOf ‘human being’ R T U New York State Center of Excellence in Bioinformatics & Life Sciences Representation and what it is about ? at some t R T U New York State Center of Excellence in Bioinformatics & Life Sciences Representations as first order entities (1) at some t instanceOf at some t instanceOf ?1 ?2 isa ?3 isa R T U New York State Center of Excellence in Bioinformatics & Life Sciences Representations as first order entities (2) L1 about R at some t instanceOf at some t instanceOf about ontology R T U New York State Center of Excellence in Bioinformatics & Life Sciences Two sorts of representations L1 R L2 L3 symbolizations beliefs ‘about’ R T U New York State Center of Excellence in Bioinformatics & Life Sciences Three levels of reality R T U New York State Center of Excellence in Bioinformatics & Life Sciences Diseases : L1 Diagnoses L2/L3 Diagnosis: Disease • A configuration of representational units; isa • Believed to mirror the Pneumococcal pneumonia person’s disease; • Believed to mirror the Instance-of at t1 disease’s cause; • Refers to the universal of which the disease is #78 #56 caused John’s portion John’s believed to be an by of pneumococs Pneumonia instance. R T U New York State Center of Excellence in Bioinformatics & Life Sciences Some motivations and consequences (1) • The same diagnosis can be expressed in various forms. Disease isa Pneumococcal pneumonia Instance-of at t1 #78 caused by #56 Portion of pneumococs caused by isa Pneumonia Instance-of Instance-of at t1 at t1 #56 caused by #78 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Some motivations and consequences (2) • A diagnosis can be of level 2 or level 3, i.e. either in the mind of a cognitive agent, or in some physical form. • Allows for a clean interpretation of assertions of the sort ‘these patients have the same diagnosis’: The configuration of representational units is such that the parts which do not refer to the particulars related to the respective patients, refer to the same portion of reality. R T U New York State Center of Excellence in Bioinformatics & Life Sciences Distinct but similar diagnoses Pneumococcal pneumonia Instance-of at t1 #78 John’s portion of pneumococs caused by Instance-of at t2 #56 #956 John’s Pneumonia Bob’s pneumonia caused by #2087 Bob’s portion of pneumococs R T U New York State Center of Excellence in Bioinformatics & Life Sciences Some motivations and consequences (3) • Allows evenly clean interpretations for the wealth of ‘modified’ diagnoses: – With respect to the author of the representation: • ‘nursing diagnosis’, ‘referral diagnosis’ – When created: • ‘post-operative diagnosis’, ‘admitting diagnosis’, ‘final diagnosis’ – Degree of the belief: • ‘uncertain diagnosis’, ‘preliminary diagnosis’ R T U New York State Center of Excellence in Bioinformatics & Life Sciences Reality and representation: both in evolution t U1 U2 Reality p3 IUI-#3 O-#0 Repr. O-#2 O-#1 = “denotes” = what constitutes the meaning of representational units …. Therefore: O-#0 is meaningless R T U New York State Center of Excellence in Bioinformatics & Life Sciences Changes in SNOMED R T U New York State Center of Excellence in Bioinformatics & Life Sciences Reality versus representations, both in evolution t U1 U2 L1 p3 IUI-#3 O-#0 L2 O-#2 O-#1 Several types of mismatches between reality and representations R T U New York State Center of Excellence in Bioinformatics & Life Sciences Mistakes, discoveries, being lucky, having bad luck Mistakes t U1 U2 L1 p3 IUI-#3 O-#0 L2 O-#2 O-#1 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Mistakes, discoveries discoveries, being lucky, having bad luck t U1 U2 L1 p3 IUI-#3 O-#0 L2 O-#2 O-#1 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Mistakes, discoveries, being lucky, having bad luck t U1 U2 L1 p3 IUI-#3 O-#0 L2 O-#2 O-#1 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Mistakes, discoveries, being lucky, having bad luck t U1 U2 L1 p3 IUI-#3 O-#0 L2 O-#2 O-#1 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Part 3: Representation in Referent Tracking R T U New York State Center of Excellence in Bioinformatics & Life Sciences Portion of Reality Entity Configuration represents Relation Universal Particular contains is about Non-referring particular class Information content ent. denotes corresponds-to Representation RT-tuple Representational unit Defined class … … … Extension Denotator CUI IUI UUI RUI denotes denotes denotes Representations in Referent Tracking R T U New York State Center of Excellence in Bioinformatics & Life Sciences Extensions – Defined Classes R T U New York State Center of Excellence in Bioinformatics & Life Sciences Referent Tracking System R T U New York State Center of Excellence in Bioinformatics & Life Sciences Referent Tracking System Components • Referent Tracking Software Manipulation of assertions about L1 • Referent Tracking Datastore: • IUI repository A collection of globally unique singular identifiers denoting particulars • Referent Tracking Database A collection of assertions about the particulars denoted in the IUI repository Manzoor S, Ceusters W, Rudnicki R. Implementation of a Referent Tracking System. International Journal of Healthcare Information Systems and Informatics 2007;2(4):41-58. R T U New York State Center of Excellence in Bioinformatics & Life Sciences Essentials of Referent Tracking • Generation of universally unique identifiers; • deciding what particulars should receive a IUI; • finding out whether or not a particular has already been assigned a IUI (each particular should receive maximally one IUI); • using IUIs in the EHR, i.e. issues concerning the syntax and semantics of statements containing IUIs; • determining the truth values of statements in which IUIs are used; • correcting errors in the assignment of IUIs. R T U New York State Center of Excellence in Bioinformatics & Life Sciences IUI assignment • = an act carried out by the first ‘cognitive agent’ feeling the need to acknowledge the existence of a particular it has information about by labeling it with a UUID. • ‘cognitive agent’: – A person; – An organization; – A device or software agent, e.g. • Bank note printer, • Image analysis software. R T U New York State Center of Excellence in Bioinformatics & Life Sciences Criteria for IUI assignment (1) • The particular’s existence must be determined: – – Easy for persons in front of you, body parts, ... Easy for ‘planned acts’: they do not exist before the plan is executed ! • – More difficult: subjective symptoms • – Only the plan exists and possibly the statements made about the future execution of the plan But the statements the patient makes about them do exist ! However: • • no need to know what the particular exactly is, i.e. which universal it instantiates Not always a need to be able to point to it precisely – – One bee out of a particular swarm that stung the patient, one pain out of a series of pain attacks that made the patient worried But: this is not a matter of choice, not ‘any’ out of ... R T U New York State Center of Excellence in Bioinformatics & Life Sciences Criteria for IUI assignment (2) • May not have already been assigned a IUI. • • • • Morning star and evening star Himalaya Multiple sclerosis It must be relevant to do so: • • • Personal decision, (scientific) community guideline, ... Possibilities offered by the EHR system If a IUI has been assigned by somebody, everybody else making statements about the particular should use it R T U New York State Center of Excellence in Bioinformatics & Life Sciences Assertion of assignments • IUI assignment is an act of which the execution has to be asserted in the IUI-repository: – Di = <IUId, Ai, td> (1.0) • IUId IUI of the registering agent • Ai the assertion of the assignment < IUIp, IUIa, tap> » IUIa IUI of the author of the assertion » IUIp IUI of the particular » tap • td time of the assignment time of registering Ai in the IUI-repository • Neither td or tap give any information about when # IUIp started to exist ! That might be asserted in statements providing information about # IUIp . R T U New York State Center of Excellence in Bioinformatics & Life Sciences D-tuples 2.0: dealing with mistakes Validity and availability of information Tuple name D-tuple Attributes Description < IUId, IUIA, td, E, C, S > The particular referred to by IUId registers the particular referred to by IUIA (the IUI for the corresponding A-tuple) at time td. E is either the symbol ‘I’ (for insertion) or any of the error type symbols as defined in [1]. C is the reason for inserting the A-tuple. S is a list of IUIs denoting the tuples, if any, that replace the retired one. A D-tuple is inserted: (1) to resolve mistakes in RTS, and (2) whenever a new tuple other than a D-tuple is inserted in the RTS. [1] Ceusters W. Dealing with Mistakes in a Referent Tracking System. In: Hornsby KS (eds.) Proceedings of Ontology for the Intelligence Community 2007 (OIC-2007), Columbia MA, 28-29 November 2007;:5-8. R T U New York State Center of Excellence in Bioinformatics & Life Sciences Management of the IUI-repository • Adequate safety and security provisions – Access authorisation, control, read/write, ... – Pseudonymisation • Deletionless but facilities for correcting mistakes. • Registration of assertion ASAP after IUI assignment • (virtual, e.g. LSID) central management with adequate search facilities. R T U New York State Center of Excellence in Bioinformatics & Life Sciences PtoP statements - particular to particular • ordered sextuples of the form Ri = <IUIa, ta, r, o, P, tr> IUIa is the IUI of the author of the statement, ta a reference to the time when the statement is made, r a reference to a relationship (available in o) obtaining between the particulars referred to in P, o a reference to the ontology from which r is taken, P an ordered list of IUIs referring to the particulars between which r obtains, and, tr a reference to the time at which the relationship obtains. • P contains as much IUIs as required by the arity of r. In most cases, P will be an ordered pair such that r obtains between the particular represented by the first IUI and the one referred to by the second IUI. • As with A statements, these statements must also be accompanied by a meta-statement capturing when the sextuple became available to the referent tracking system. R T U New York State Center of Excellence in Bioinformatics & Life Sciences PtoU statements – particular to universal Ui = <IUIa, ta, inst, o, IUIp, u, tr> IUIa ta inst o IUIp u tr is the IUI of the author of the statement, a reference to the time when the statement is made, a reference to an instance relationship available in o obtaining between p and cl, a reference to the ontology from which inst and u are taken, the IUI referring to the particular whose inst relationship with u is asserted, the universal in o to which p enjoys the inst relationship, and, a reference to the time at which the relationship obtains. R T U New York State Center of Excellence in Bioinformatics & Life Sciences PtoN-statements Ni=< IUIa, ta, ntj, ni, IUIp, tr, IUIc> • The person referred to by IUIa asserts at time ta that ni is the name of the nametype ntj that designates in the context IUIC in the real world the particular referred to by IUIp at tr. This template will further be referred to as PtoN template. • Would assert that “Werner” is my first name, and “Ceusters” is my last name. R T U New York State Center of Excellence in Bioinformatics & Life Sciences U--tuples: “negative findings” Relation type Type of Negative Finding Examples % C1 <p, u> * he denies abdominal pain; no alcohol abuse; A particular is not related in a specific way to any instance of a no hepatosplenomegaly; he has no children, without any cyanosis universal at some given time 85.4 C2 <p, u> A par ticular is not the instance of which ruled out primary hyperaldosteronism, a given class at some given time nontender, in no apparent distress, Romberg sign was absent , no palpable lymph nodes 12.4 C3 <p, p> A particular is not related to another partic ular in a specific way at some given time this record is not available to me; it is not the intense edema she had before; he has not identified any association with meals. 2.2 * ‘p’ ranges over particulars, ‘u’ over universals Ui = <IUIa, ta, r, o, IUIp, u, tr> The particular referred to by IUIa asserts at time ta that the relation r of ontology o does not obtain at time tr between the particular referred to by IUIp and any of the instances of the universal u at time tr R T U New York State Center of Excellence in Bioinformatics & Life Sciences PtoCO statements: particular to concept code Coi = <IUIa, ta, cbs, IUIp, co, tr> IUIa ta cbs IUIp co tr is the IUI of the author of the statement, a reference to the time when the statement is made, a reference to the concept-based system from which co is taken, the IUI referring to the particular which the author associates with co, the concept-code in cbs which the author associates with p, and, a reference to the time at which the author considers the association appropriate, R T U New York State Center of Excellence in Bioinformatics & Life Sciences Interpretation of PtoCO statements • must be interpreted as simple indexes to terms in a dictionary. • All that such a statement tells us, is that within the linguistic and scientific community in which cbs is used, the terms associated with co may - i.e. are acceptable to - be used to denote p in their determinative version. R T U New York State Center of Excellence in Bioinformatics & Life Sciences A SNOMED-CT example • <IUI-0945, 18/04/2005, SNOMED-CT v0301, IUI-1921, 367720001, forever> • #IUI-0945: author of the statement • #IUI-1921: the left testicle of patient #IUI-78127 • 367720001: 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 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Referent Tracking System Environment User User External Information System Referent Tracking System IUI Component RTS Proxy Peer Referent Tracking System User Interface(s) Referent Tracking Server (Peers) Reasoning Server Referent Tracking Data Access Server RTS Server Proxy Peer Internal Ontology Referent Tracking Data Store Terminology Server Vocabulary or Thesaurus or Nomenclature or Concept System or Realism-based Ontology R T U New York State Center of Excellence in Bioinformatics & Life Sciences Networks of Referent Tracking systems Information System A Information System C Referent Tracking System A Referent Tracking Server A1 Referent Tracking System C RTS Proxy Peer Referent Tracking Server C1 RTS Proxy Peer Referent Tracking Server A2 Referent Tracking Server A3 Referent Tracking Server C2 RTS Server Proxy Peer RTS Server Proxy Peer … Referent Tracking System B Referent Tracking Server B1 Referent Tracking Server C3 … Information System B RTS Server Proxy Peer Referent Tracking Server B2 RTS Proxy Peer Referent Tracking Server B3 … R T U New York State Center of Excellence in Bioinformatics & Life Sciences Part 4: Applications & Projects R T U New York State Center of Excellence in Bioinformatics & Life Sciences eyeGENE (June 2008 - …) R T U New York State Center of Excellence in Bioinformatics & Life Sciences Ontology for Risks Against Patient Safety R T U New York State Center of Excellence in Bioinformatics & Life Sciences Representing particular adverse event cases • Is the generic representation of the portion of reality adequate enough for the description of particular cases? • Example: a patient – born at time t0 – undergoing anti-inflammatory treatment and physiotherapy since t2 – for an arthrosis present since t1 – develops a stomach ulcer at t3. 82 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Anti-inflammatory treatment with ulcer development IUI Description of particular Properties #1 the patient who is treated #1 member_of C1 since t2 #2 #1’s treatment #2 instance_of C3 #2 has_agent #3 since t2 #3 the physician responsible for #2 #3 member_of C4 since t2 #4 #1’s arthrosis #4 member_of C5 since t1 #5 #1’s anti-inflammatory treatment #5 part_of #2 #6 #1’s physiotherapy #6 part_of #2 #7 #1’s stomach #7 member_of C6 since t2 #8 #7’s structure integrity #8 instance_of C8 since t0 #9 #1’s stomach ulcer #9 part_of #7 since t3 #10 coming into existence of #9 #10 has_participant #9 at t3 #11 change brought about by #9 #11 has_agent #9 since t3 #11 instance_of C10 (harm) at t3 #11 has_participant #8 since t3 #12 noticing the presence of #9 #12 has_participant #9 at t3+x #12 has_agent #3 at t3+x #13 cognitive representation in #3 about #9 #13 is_about #9 since t3+x #2 has_participant #1 since t2 #5 member_of C2 since t3 #8 inheres_in #7 since t0 83 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Time line and dependencies (1) t0 t1 t2 t3 #1 the patient (#1) who is treated #7 #1’s stomach #8 #7’s structure integrity C8 structure integrity • At t0, the patient is born, and since that time, his stomach is part of him and a structure integrity (C8) inheres in it: – – – – #1 instance-of person since t0 #7 part-of #1 since t0 #8 instance_of C8 since t0 #8 inheres_in #7 since t0 84 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Time line and dependencies (2) t0 t1 t2 t3 #1 the patient who is treated #7 #1’s stomach #8 #7’s structure integrity C8 structure integrity #4 #1’s arthrosis C5 underlying disease • At t1, the patient acquires arthrosis: – #4 member_of C5 since t1 – #4 inheres_in #1 since t1 85 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Time line and dependencies (3) t0 t1 t2 t3 #1 the patient who is treated C1 subject of care #7 #1’s stomach C6 #8 #7’s structure integrity involved structure C8 structure integrity #4 #1’s arthrosis C5 underlying disease #2 #1’s treatment C3 act of care #6 #1’s physiotherapy #5 #1’s anti-inflammatory treatment • At t2, the patient consults #3 who starts treatment. It is then that the patient becomes a member of the class subject of care (C1) and his stomach a member of the class involved structure (C6) #3 the physician responsible for #2 C4 care giver 86 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Time line and dependencies … t0 t1 t2 t3 #1 the patient who is treated C1 subject of care #7 #1’s stomach C6 #8 #7’s structure integrity involved structure C8 structure integrity #4 #1’s arthrosis C5 underlying disease #2 #1’s treatment C3 act of care #6 #1’s physiotherapy #5 #1’s anti-inflammatory treatment C2 act under scrutiny #9 #1’s stomach ulcer #11 change brought about by #9 C10 harm #12 noticing #9 #13 cognitive representation in #3 about #9 #3 the physician responsible for #2 C4 care giver 87 R T U New York State Center of Excellence in Bioinformatics & Life Sciences Domotics and RFID systems • Avoiding adverse events in a hospital because of insufficient day/night illumination: – Light sensors and motion detectors in rooms and corridors • and representations thereof in an Adverse Event Management System (AEMS) – What are ‘sufficient’ illumination levels for specific sites is expressed in defined classes, – Each change in a detector is registered in real time in the AEMS, – Action-logic implemented in a rule-base system, f.i. to generate alerts. R T U New York State Center of Excellence in Bioinformatics & Life Sciences RT-based representation (1): IUI assignment Reality level 1 #1: that corridor #2: that lamp #3: that motion detector #4: that light detector #5: that RFID reader #6: that patient with RFID #7 #8: that RFID reader #9: this elevator #10: 2nd floor of clinic B R T U New York State Center of Excellence in Bioinformatics & Life Sciences RT-based representation (2): relationships • (Semi-)stable relationships: – – – – – – – – #1 instance-of ReM:Corridor since t1 #2 instance-of ReM:Lamp since t2 #2 contained-in #1 since t3 #6 member-of ReM:Patient since t4 #6 adjacent-to #7 since t4 #18 instance-of ReM:Illumination since t1 #18 inheres-in #1 since t1 … • Semi-stable because of: – lamps may be replaced – persons are not patients all the time – … • keeping track of these changes provides a history for each tracked entity R T U New York State Center of Excellence in Bioinformatics & Life Sciences RT-based representation (3): rule base * • Setting illumination requirements for lamp #2: – #18 member-of ReM:Insufficient illumination during ty • if – tx part-of ReM:Daytime – #y1 instance-of ReM:Motion-detection – #y1 has-agent #3 – ty part-of tx – #y2 instance-of ReM:Illumination measurement – #y2 has-agent #4 – #y2 has-participant #18 – #y2 has-result imrz – imrz less-than 30 lumen at ty at ty at ty at ty • else – tx – … part-of ReM:Night time • endif * Exact format to be discussed with ReMINE partners R T U New York State Center of Excellence in Bioinformatics & Life Sciences RT-based representation of events • Imagine #6 (with RFID #7) walking through #1 – – – – – – #2345 instance-of ReM:Motion-detection #2345 has-agent #3 at t4 #2346 instance-of ReM:RFID-detection #2346 has-agent #5 at t4 #2346 has-participant #7 at t4 … • Here, the happening of #2345 fires the rule explained on the previous slide. • If imrz turns out to be too low, that might invoke another rule which sends an alert to the ward that lamp #2 might be broken. • #2346 might trigger yet another rule, namely an alert for imminent danger for AE with respect to patient #6 • … R T U New York State Center of Excellence in Bioinformatics & Life Sciences Making existing EHR systems RT compatible