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R T U New York State Center of Excellence in Bioinformatics & Life Sciences OIC-2007 - ONTOLOGY FOR THE INTELLIGENCE COMMUNITY: Towards Effective Exploitation and Integration of Intelligence Resources How to Keep Track of Absolutely Everything Columbia, MD - November 28, 2007 Werner CEUSTERS Center of Excellence in Bioinformatics and Life Sciences University at Buffalo, NY, USA http: //www. org. buffalo. edu/RTU
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 • R 1: • R 2 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 • R 3: • R 4 … 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 tr i o o H d to w ? ht ig
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Requirements for a digital copy of the world • R 1: • R 2 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 • R 3: • R 4 … 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 R 1: A faithful representation of reality … … recognizes three levels: 1. The (first order) reality which exists ‘as it is’ prior to a cognitive agent’s perception thereof; 2. the cognitive representations of this reality embodied in observations and interpretations on the part of cognitive agents; 3. the publicly accessible concretizations constructed through cognitive insights as artifacts representing first order reality of which ontologies, terminologies and data repositories are examples. 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, November 8, 2006, Baltimore MD, USA
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Three levels of reality B RU 1 B 1 RU 1 O 1 O R #1 • Both RU 1 B 1 and RU 1 O 1 are representational units referring to #1; • RU 1 O 1 is NOT a representation of RU 1 B 1; • RU 1 O 1 is created through concretization of RU 1 B 1 in some medium.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Faithfulness through the right philosophy 1. Granular Partition Theory
R T U New York State Center of Excellence in Bioinformatics & Life Sciences 2. Basic Formal Ontology (BFO) • An ontology which is – Realist: There is only one reality and its constituents exist independently of our (linguistic, conceptual, theoretical, cultural) representations thereof, – Fallibilist: theories and classifications can be subject to revision, – Perspectivalist: there exists a plurality of alternative, equally legitimate perspectives on that one reality – Adequatist: these alternative views are not reducible to any single basic view.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Get down that wall Basic Formal Ontology: Granular Partition Theory: teaches us how to build an adequate grid. relates the copy to reality.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences The BFO view of the world • The world consists of – entities that are • Either particulars or universals; • Either occurrents or continuants; and, – relationships between these entities of the form • Either dependent or independent; •
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Particulars versus Universals Ontology universals air plane philosopher airport president JFK George Bush instance of… Enola Gay particulars Barry Smith Inventory
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Continuants versus Occurents t occurrents flying meeting has-participant at time … Enola Gay continuants Barry Smith JFK George Bush
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Instantiation for continuants universals child adult philosopher president t Instance-of at t Barry Smith Continuant particulars George Bush
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Continuants undergo changes while keeping identity Transformation-of child adult Is-a president t Instance-at t particulars Barry Smith George Bush
R T U New York State Center of Excellence in Bioinformatics & Life Sciences General principle about relationships All universal level relationships are defined on the basis of particular level relationships Smith B, Ceusters W, Klagges B, Koehler J, Kumar A, Lomax J, Mungall C, Neuhaus F, Rector A, Rosse C. Relations in biomedical ontologies, Genome Biology 2005, 6: R 46.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Is_a is defined over instance-of For continuants • C is_a C 1 = [definition] for all c, t, if c instance_of C at t then c instance_of C 1 at t. For occurrents • P is_a P 1 = [definition] for all p, if p instance_of P then p instance_of P 1.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Primitive instance-level relationships (RO) • c part_of c 1 at t - a primitive relation between two continuant instances and a time at which the one is part of the other • p part_of p 1, r part_of r 1 - a primitive relation of parthood, holding independently of time, either between process instances (one a subprocess of the other), or between spatial regions (one a subregion of the other) • c located_in r at t - a primitive relation between a continuant instance, a spatial region which it occupies, and a time • r adjacent_to r 1 - a primitive relation of proximity between two disjoint continuants • t earlier t 1 - a primitive relation between two times • c derives_from c 1 - a primitive relation involving two distinct material continuants c and c 1 • p has_participant c at t - a primitive relation between a process, a continuant, and a time • p has_agent c at t - a primitive relation between a process, a continuant and a time at which the continuant is causally active in the process Smith B, Ceusters W, Klagges B, Koehler J, Kumar A, Lomax J, Mungall C, Neuhaus F, Rector A, Rosse C. Relations in biomedical ontologies, Genome Biology 2005, 6: R 46.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences A division of labor Ontology What is generic Instance-of What is specific Referent Tracking
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 statements about facts and beliefs • Referent Tracking Datastore: • IUI repository A collection of globally unique singular identifiers denoting particulars • Referent Tracking Database A collection of facts and beliefs 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 Requirements for a digital copy of the world • R 1: • R 2 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 • R 3: • R 4 … 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 The reality: a digital copy of part of the world Applying the grid does not give a distorted representation of reality, but only an incomplete representation !!!
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Key issue: keeping track of what the bits denote
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Key issue: keeping track of what the bits denote • Images are no good: – Are too complex particulars in their own right that stand in another sort of relation to the part of reality that they depict. • Terms / names ? Mid Ma dle-Ea dag asc st Kat rina ar
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Names are inadequate representational units • “JFK” “Enola Gay” • “Barry Smith” “George Bush”
R T U New York State Center of Excellence in Bioinformatics & Life Sciences IUI: Instance Unique Identifiers denotes 5241 89023 109427 Relationship managed in the RTS
R T U New York State Center of Excellence in Bioinformatics & Life Sciences The IUI-repository • • • 17821 denotes Earth 200896 Madagascar 70567 Antananarivo 9576 Hotel Sunny 509579 the valihaperformance on August 7, 2006 in Hotel Sunny in Antananarivo • …
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Key mechanism: 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 labelling it with a universally unique singular identifier. • ‘cognitive agent’: – A person; – An organisation; – 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) 1. The particular’s existence must be determined: – – Easy for persons in front of you, tools, . . . Easy for ‘planned acts’: they do not exist before the plan is executed ! • – More difficult: a subject’s intensions, emotions • – Only the plan exists and possibly the statements made about the future execution of the plan But the statements observers make about them do exist ! However: • • 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 – – A member of a specific organization 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) 2. The particular’s existence ‘may not already have been determined as the existence of something else’: • • Morning star and evening star / Himalaya 2 observers not knowing they observed the same thing 3. May not have already been assigned a IUI. 4. It must be relevant to do so: • • • Personal decision, (scientific) community guideline, . . . Possibilities offered by the annotation 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 Particulars of interest for Intelligence • • • Persons Credit cards Places Cell phones Organizations Events RFID tags Vehicles Sensors Social networks … • • • Beliefs Opinions Decisions Plans Hypotheses Plots Intentions Predictions Wishes Interpretations Diagnoses. . . • • • Images Sensor data Reports Phone calls Messages …
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: –
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Elementary RTS tuple types Relationships between particulars taken from a realism-based relation ontology Instantiation of a universal Annotation using terms from a nonrealist terminology ‘Negative findings’ such as absences, missing parts, preventions, … Names for a particular
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Without ‘names’: pseudonymized database !
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Management of the Data Store • 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 Dealing with mistakes • This change involves RTS entries becoming assigned IUIs of their own which in the restructured D-template is symbolized by IUITi. • Di =
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Requirements for a digital copy of the world • R 1: • R 2 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 • R 3: • R 4 … 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 Eternal memory
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Accept that everything may change: 1. changes in the underlying reality: • Particulars come, change and go 2. changes in our (scientific) understanding: • The plant Vulcan does not exist 3. reassessments of what is considered to be relevant for inclusion (notion of purpose). 4. encoding mistakes introduced during data entry or ontology development.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Reality and representation: both in evolution t U 1 U 2 Reality p 3 IUI-#3 Repr. O-#0 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 An “optimal” representational artifact • Each representational unit in such a representational artifact would designate – (1) a single portion of reality (POR), which is – (2) relevant to its purposes and such that – (3) the authors intended to use this representational unit to designate this POR, and – (4) there would be no PORs objectively relevant to these purposes that are not referred to in the representational artifact.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Sources of error • assertion errors: sources may be in error as to what is the case in their target domain; • relevance errors: sources and analysts may be in error as to what is objectively relevant to a given purpose; • encoding errors: they may not successfully encode their underlying cognitive representations, so that particular representational units fail to point to the intended PORs.
R T U New York State Center of Excellence in Typology of expressions included in and excluded from an Bioinformatics & Life Sciences ontology in light of relevance and relation to external reality
R T U New York State Center of Excellence in Typology of expressions included in and excluded from an Bioinformatics & Life Sciences ontology in light of relevance and relation to external reality Valid presence in the representation Valid absence in the representation
R T U New York State Center of Excellence in Typology of expressions included in and excluded from an Bioinformatics & Life Sciences ontology in light of relevance and relation to external reality Unjustified presence in the representation Unjustified absence in the representation But sometimes you are lucky …
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Key requirement for updating Any change in an ontology or data repository should be associated with the reason for that change to be able to assess later what kind of mistake has been made ! Ceusters W, Smith B. A Realism-Based Approach to the Evolution of Biomedical Ontologies. Proceedings of AMIA 2006, Washington DC, 2006; : 121 -125.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Updating is an active process • authors assume in good faith that – all included representational units are of the P+1 type, and – all they are aware of, but not included, of A+1 or A+2. • If they become aware of a mistake, they make a change under the assumption that their changes are also towards the P+1, A+1, or A+2 cases. • Thus at that time, they know of what type the previous entry must of have been under the belief what the current one is, and the reason for the change.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Possible evolutions through updates
R T U New York State Center of Excellence in Bioinformatics & Life Sciences This leads to a calculus … • NOT: – to demonstrate how good an individual version representation is faithful to reality, • But rather – to measure how much it improved (hopefully) as compared to its predecessors. – How well the authors of the representation are doing • Principle: recursive belief revision
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Requirements for a digital copy of the world • R 1: • R 2 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 • R 3: • R 4 … 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 RTS architecture
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Data store
R T U New York State Center of Excellence in Bioinformatics & Life Sciences RT templates RDFS schema diagram
R T U New York State Center of Excellence in Bioinformatics & Life Sciences RTS example graph
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Performance tests On desktop running all servers and services
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Reasoning over instances and universals instance-of at t caused #105 by
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Summary (1) • Referent Tracking: – Uses IUIs to denote particulars, – Uses realism-based ontologies (3 D and 4 D) to describe these particulars in relation to each other and to universals. • Particulars include: – Me, this laptop, this room – My beliefs and wishes about the former – Statements registered in the RT Datastore
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Summary (2) • An RT system comes with services to: – Assign IUIs – Annotate reality – Track changes in reality, in our beliefs, and in the status of the RT Data store itself – Reason over instances with or without additional use of computable ontologies.
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Further reading • Background material • [Smith et al. 2005 a] Smith B, Ceusters W, Klagges B, Koehler J, Kumar A, Lomax J, Mungall C, Neuhaus F, Rector A, Rosse C. Relations in biomedical ontologies, Genome Biology 2005, 6: R 46. [Smith & Ceusters 2005 b] Smith B, Ceusters W. An Ontology-Based Methodology for the Migration of Biomedical Terminologies to Electronic Health Records. AMIA 2005, October 22 -26, Washington DC; : 669 -673. (draft). [Smith & Ceusters 2006 a] Smith B, Ceusters W. Ontology as the Core Discipline of Biomedical Informatics: Legacies of the Past and Recommendations for the Future Direction of Research, forthcoming in Gordana Dodig Crnkovic and Susan Stuart (eds. ) Computing, Philosophy, And Cognitive Science, Cambridge: Cambridge Scholars Press, 2006. (full paper). [Smith et al. 2006] 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 (draft) • • Theoretical aspects of referent tracking • [Ceusters 2007] Ceusters W. Dealing with Mistakes in a Referent Tracking System. Accepted for Ontology for the Intelligence Community 2007 (OIC-2007), Columbia MA, 28 -29 November 2007. (Extended abstract) [Ceusters et al. 2007 a] Ceusters W, Elkin P, Smith B. Negative Findings in Electronic Health Records and Biomedical Ontologies: A Realist Approach. International Journal of Medical Informatics 2007; 2007: 326 -333. (draft, abstract, full paper). [Ceusters et al. 2006 a] Ceusters W, Elkin P, Smith B. Referent Tracking: The Problem of Negative Findings, Stud Health Technol Inform. 2006; 124: 741 -6. (Presented at MIE 2006) (draft paper, slides) [Ceusters & Smith 2006 a] Ceusters W, Smith B. A Realism-Based Approach to the Evolution of Biomedical Ontologies. Proceedings of AMIA 2006, Washington DC, November 11 -15, 2006, pp 121 -125. (draft) [Ceusters 2006] Ceusters W. Towards A Realism-Based Metric for Quality Assurance in Ontology Matching. In: Bennett B, Fellbaum C. (eds. ) Formal Ontology in Information Systems, IOS Press, Amsterdam, 2006; : 321 -332. Proceedings of FOIS-2006, Baltimore, Maryland, November 9 -11, 2006. (draft) [Ceusters & Smith, 2005 a] Ceusters W. and Smith B. Tracking Referents in Electronic Health Records. In: Engelbrecht R. et al. (eds. ) Medical Informatics Europe, IOS Press, Amsterdam, 2005; : 71 -76. (draft, slides) [Ceusters & Smith, 2005 b] Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun; 39(3): 362 -78. (e. Pub 2005 Sep 9, draft, slides presented during the IMIA WG 6 workshop Ontology and Biomedical Informatics, Rome, Italy, April 29 - Mai 1, 2005) Applying referent tracking in specific contexts • •
R T U New York State Center of Excellence in Bioinformatics & Life Sciences Further reading • Applying in contexts • [Ceusters et al. 2007 b] Ceusters W, Spackman KA, Smith B. Would SNOMED CT benefit from Realism-Based Ontology Evolution? Accepted for American Medical Informatics Association 2007 Annual Symposium (AMIA 2007) Proceedings, Chicago IL, 10 -14 November 2007. (abstract, draft) [Ceusters & Smith 2007 b] Ceusters W, Smith B. Referent Tracking and its Applications. In: Proceedings of the WWW 2007 Workshop i 3: Identity, Identifiers, Identification. Banff, Canada, May 8, 2007, CEUR Workshop Proceedings, ISSN 1613 -0073, online http: //ceurws. org/Vol-249/submission_105. pdf. [Ceusters & Smith 2007 a] Ceusters W, Smith B. Referent Tracking for Corporate Memories. In: Rittgen P. (ed. ) Handbook of Ontologies for Business Interaction. IDEA Group Publishing, 2007 (forthcoming). [Ceusters & Smith 2006 b] Ceusters W, Smith B. Referent Tracking for Treatment Optimisation in Schizophrenic Patients. Journal of Web Semantics 4(3) 2006: 229 -36; Special issue on semantic web for the life sciences. (Long draft, official preprint, published paper) [Ceusters & Smith 2006 c] Ceusters W, Smith B. Referent Tracking for Digital Rights Management. International Journal of Metadata, Semantics and Ontologies 2007; 2(1): 45 -53. (draft, published version) • • • Implementation • [Rudnicki et al. 2007 a] Rudnicki R, Ceusters W, Manzoor S, Smith B. What Particulars are Referred to in EHR Data? A Case Study in Integrating Referent Tracking into an Electronic Health Record Application. Accepted for American Medical Informatics Association 2007 Annual Symposium (AMIA 2007) Proceedings, Chicago IL, 10 -14 November 2007. (abstract, draft) [Manzoor et al. 2007 b] Manzoor S, Ceusters W, Rudnicki R. A Middleware Approach to Integrate Referent Tracking in EHR Systems. Accepted for American Medical Informatics Association 2007 Annual Symposium (AMIA 2007) Proceedings, Chicago IL, 10 -14 November 2007. (abstract, draft) [Manzoor et al. 2007 a] 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. (summary, full paper). • •