Ontology-based Representation and Reasoning about the History of Science

1. Ontology-based Representation and Reasoning about the History of Science Ilaria Corda Msc by research student School of Computing University of Leeds Supervisors: Dr. Vania Dimitrova Dr. Brandon Bennett

2. Ontology-based Representation and Reasoning about the History of Science Outline Thesis’s goal Research questions Motivating scenario Research methodology and approach Reasoning examples Achievements and limitations Further work

3. Ontology-based Representation and Reasoning about the History of Science Thesis's goal “The main goal of this research is to conceptualise (part of) the History of Science by focusing on modeling time and reasoning about time dependencies”

4. Ontology-based Representation and Reasoning about the History of Science Research questions Can ontological structures appropriately represent temporal specifications in History of Science? Which methodological principles can be followed for the developing of a History of Science ontology? What time concepts should be integrated? How can time specifications be added to relations and descriptions of events? How can an ontology-based representation efficiently support reasoning on historical domains?

5. Ontology-based Representation and Reasoning about the History of Science Motivating scenario Main scientific models: Which theories extended the Copernican theory during the sixteen century? Which theories explained the phenomenon of the tides? Main scientific events: Where was the inventor of the telescope from? By whom was the supernova observed during the Scientific Revolution? Major contributors and their research activities: What did Galileo write? What did he invent? Social network relationships: Who influenced Brahe? Who worked with Kepler?

6. Ontology-based Representation and Reasoning about the History of Science Initial stage: search for ontology • Existing ontologies in which temporal concepts area taken into account • Upper ontologies(Cyc, Sowa) • Time ontologies(OWL time, KSL ontology) • Existing ontologies for historical domains • Vicodi ontology,SWHI, HICO and TELOS We need to build an ontology for the domain of History of Science

7. Ontology-based Representation and Reasoning about the History of Science Modeling challenges addressed • General coverage of the domain • Main relations and common rules for History of Science exemplified in a specific area (Scientific Revolution in Europe) • Time-space dependence • When and where did a particular event happen? • What happened in historical period H? • Social dependence • Who did influence X? • Who did work with X?

8. Ontology-based Representation and Reasoning about the History of Science Methodology for aHistory of Science ontology • Characteristics: • The domain expert acted as ontologist as well • Time and expertise constraints • Existing methodologies and method reviewed: • METHONTOLOGY (Gomez-Perez, Fernandez-Lopez and Corcho, 2003). • Gruninger and Fox’s methodology(Gruninger and Fox, 1995). • Ordnance Survey’s methodology (Kovacs et al., 2006). • Uschold and King’s method (Uschold and King, 1995). • Developing of a 3-phases methodology: • Pre-conceptualization • Conceptualization • Logical representation and coding

9. Ontology-based Representation and Reasoning about the History of Science Pre-conceptualization phase • Providing a high level description of the domain and its characteristics • Investigating existing projects involving the use of ontologies in historical domains • Building a scenario • Identifying a range of potential informal competency questions to be addressed

10. Ontology-based Representation and Reasoning about the History of Science Conceptualization phase Activity 1: identifying main concepts and relations Activity 2: Identifying time concepts and including time dimensions in relations Activity 1: • Search for related ontologies and re-usable ontologies • Acquiring knowledge from different sources • Drafting a concept tree and relations in the form of triples • Building separated tables for concepts and relations • Competency questions throughout all ontology design process

11. Ontology-based Representation and Reasoning about the History of Science Logical representation and coding • Choosing the ontology language(OWL, RDF, Prolog, etc) • Converting glossary knowledge into formal representation • Querying and reasoning about the domain

12. Ontology-based Representation and Reasoning about the History of Science Coding the domain: Prolog • Prolog as ontology language.Separation between data model (how knowledge is represented) and data description (actual data). • Classesclass(model). subclass(theory, model). • Upper relationsrelation_type(explain, theory, phenomenon). • Instantiated relationsfact_relation(explain, 'galilean theory of tides' tides). • Instancesfact_instance_of('galilean theory of tides', theory).

13. Ontology-based Representation and Reasoning about the History of Science Adding time: initial approach By identifying two forms of time occurring at the relation level: • Repeatable (using time interval)relation_type(extend, theory, theory, 'time interval').relation_type(explain, model, phenomenon, 'time interval'). • Non-repetable (using time point)relation_type('was born at', person, 'time point').relation_type(invent, person, invention). What happen if we need to add different refinements (e.g. Location)? Do we need to consider different relations?

14. Ontology-based Representation and Reasoning about the History of Science Adding time: type/token distinction Type: abstract entities (e.g. invention) Token: particular physical manifestation of types (Galilean telescope) Type-Type (parameters are only types) relation_type(relate, model, 'field of study'). relation_type(extend, theory, theory). Token-Type (a token and a type) relation_type(invent, person, invention). relation_type(observe, person, phenomenon). Token-Token (parameters are only token) relation_type(influence, person, person). relation_type('work with somebody', person, person).

15. Ontology-based Representation and Reasoning about the History of Science Adding time: Davidson-based approach Adapting the concept of event by D. Davidson in order to treat time-embedded relations. class(d_e). % Davidson event: time, place, begin, end, duration class(time). % for all time related concepts relation_type(invent, person, invention). fact_relation(invent, 'Galileo', 'thermometer', d_galileo_invent_thermometer). event_property(begin, d_galileo_invent_thermometer, 1593-00-00). event_property(end, d_galileo_invent_thermometer, 1593-00-00). fact_relation(invent, 'Galileo', telescope, d_galileo_invent_telescope). event_property(begin, d_galileo_invent_telescope, 1609-07-00). event_property(end, d_galileo_invent_telescope, 1609-11-00).

16. Ontology-based Representation and Reasoning about the History of Science Davidson’s approach: further examples Treating historical periods as events: fact_relation(hold, 'scientific revolution', d_e_scientific_revolution). event_property(begin, d_e_scientific_revolution, 1543-00-00). event_property(end, d_e_scientific_revolution, 1750-00-00). Representing two related events: fact_relation(investigate, 'Galileo', sunspot, d_galileo_investigate_sunspot). event_property(begin, d_galileo_investigate_sunspot, 1612-04-00). event_property(end, d_galileo_investigate_sunspot, 1636-00-00). event_property(location, d_galileo_investigate_sunspot, 'Italy'). fact_relation(observe, 'Galileo', sunspot, d_galileo_observe_sunspot). event_property(begin, d_galileo_observe_sunspot, 1611-03-12). event_property(end, d_galileo_observe_sunspot, 1611-03-12). event_property(location, d_galileo_observe_sunspot, 'Rome'). event_relation(sub_event, d_galileo_observe_sunspot, d_galileo_investigate_sunspot)

17. Domain specific questions (exemplification of query modes) Who(Who influenced P?) What(What happened between two time points?) Where(Where was a phenomenon Ph observed?) When(When did P1 and P2 collaborate?) Combined(When, where and by whom was phenomenon Ph observed?) Ontology-based Representation and Reasoning about the History of Science Queries and domain specific questions Query modes (abstract rules) • Concept-based(direct, inferred and indirect relationships). • Relation based(transitive, symmetrical and inverse closures). • Time event-based(inferring and comparing events properties).

18. Queries Direct instances ?-fact instance_of(‘Kepler’, C). astronomer mathematician Inferred instances ?-inferred_instance(‘Galileo’, C). person Indirect instances ?-indirect_instance(microscope, C). event Inference Rules a) Directly encoded b) inferred_instance(X,C):- fact_instance_of(X,C). inferred_instance(X,C):-fact_instance_of(X,C1),inferred_subclass(C1,C). c) indirect_instance(X,C):- inferred_instance(X,C),\+fact_instance_of(X,C). Ontology-based Representation and Reasoning about the History of Science Concept-based mode: instances examples

19. Queries ?-inferred_transitive_relation (extend, X, Y). X='galilean theory',Y='kepler theory'; X='galilean theory',Y='copernican theory‘; X='copernican theory',Y='brahe theory' ; X='brahe theory',Y='ptolemy theory' ; X='galilean theory',Y='brahe theory' ; X='galilean theory',Y='ptolemy theory‘; X='copernican theory',Y='ptolemy theory‘ ?-inferred_transitive_relation (influence, X, Y). X='Hipparcus',Y='Ptolemy'; X='Kepler',Y='Brahe'; X='Copernicus',Y='Kepler'; X='Copernicus',Y='Galileo'; X='Copernicus',Y='Brahe‘ Indicators(encoded in the ontology) transitive_relation(influence) Inference rules (to unify 3 an 4 place relations) get_relation(R,X,Y):- fact_relation(R,X,Y). get_relation(R,X,Y):-fact_relation(R,X,Y,_). (to recursively derive inferred relations) inferred_transitive_relation(R,X,Y):- transitive_relation(R), get relation(R,X,Y). inferred_transitive_relation(R,X,Y):- transitive_relation(R), get_relation(R,X,Y1), inferred_transitive_relation(R,Y1,Y). Ontology-based Representation and Reasoning about the History of Science Relation-based mode: transitive relation example

20. Queries Time point before ?-timepoint_before(1633-07-14, 1636-06-18). ?-timepoint_before(1609-07-00, 1609-11-00) ?-timepoint_before(1609-07-19, 1609-07-22). Time point same ?-timepoint_same(1543-05-10, 1543-05-10). ?-timepoint_same(1543-05-00, 1543-05-10). ?-timepoint_same(1543-0-0, 1543-10-10). Rules (to compare time points) timepoint_before(Y1-_-_, Y2-_-_):-Y1<Y2,!. timepoint_before(Y-M1-_, Y-M2-_):-M1<M2,!. timepoint_before(Y-M-D1,Y-M-D2):-D1<D2,!. timepoint_same(Y-M-D,Y-M-D). timepoint_same(Y-M-0, Y-M-_). timepoint_same(Y-0-0, Y-_-_). O/00= date unknown _= variable which can be instantiate to any value Ontology-based Representation and Reasoning about the History of Science Time-event based mode:arithmetical operators

21. To compare events based on their start and end points ?-happen_before(d_brahe_publish_novastella, E2 ). E2=d_galileo_write_discourse; E2=d_galileo_publish_assayer; E2=d_galileo_invent_thermomete E2=d_galileo_read_elements; ?-happen_during(d_kepler_publish_harmonice, E2). E2=d_galileo_investigate_sunspot; E2=d_e_scientific_revolution happen_before(E1, E2 ) :- event_property(end, E1, T_E1e ), event_property(begin, E2, T_E2s ),timepoint_before( T_E1e, T_E2s). happen_during(E1,E2):- event_property(begin, E1, T_E1s ),event_property(end, E1, T_E1e), event_property(begin, E2, T_E2s), event_property(end, E2, T_E2e), timepoint_before(T_E2s, T_E1s),timepoint_before(T_E1e, T_E2e). Ontology-based Representation and Reasoning about the History of Science Time-event based mode:Allen relations

22. Queries Who questions ?-who_influenced('Brahe'). ['Kepler', 'Copernicus'] ?-who_worked_with('Kepler'). ['Brahe', 'Wallenstein'] What questions ?-which_theory_extend('galilean theory'). ['brahe theory','ptolemy theory'] Rules (application of inferred_transitive_relation) who_influenced(P):-setof(P1,inferred_transitive_relation(influence,P1,P),All), showlist( All ). which_theory_extend(T):-setof(X,inferred_transitive_relation(extend, T, X), All ), showlist( All ). Ontology-based Representation and Reasoning about the History of Science Domain oriented questions: who and what

23. Involve more than one type of questions (when/where) ?-when_where_was_born('Ptolemy'). [was born, Ptolemy, [85-00-00, 85-00-00, Alexandria]] (who/when/where) ?-who_when_where_observed (supernova). [[observe, 'Brahe', supernova, [1572-00-00, 1572-00-00, Germany]], [observe, 'Bevis', supernova, [1731-00-00, 1731-00-00, England]]] Rules when_where_was_born(P):- fact_relation('was born', P, E), event_properties_detail(E,P_e), showlist(P_e). who_when_where_observed(Ph):- findall(P_e, (fact_relation(observe,P,Ph,E), event_properties_detail(E,P_e) ), All), showlist(All). Ontology-based Representation and Reasoning about the History of Science Domain oriented questions: combined examples

24. Ontology-based Representation and Reasoning about the History of Science Use of domain oriented questions • To exemplify the query modes • To verify and expand the ontology: • Syntax errors(mispelled words, inconsistencies in naming relations) • Hierarchical inconsistencies(inconsistent inheritance behaviour) • Ontology population for answer the queries(unpopulated or insufficiently populated part of the ontology e.g. symmetrical relations)

25. Ontology-based Representation and Reasoning about the History of Science Achievements • Development of a three-phase methodology • Development of a framework for adding temporal specification (Davidson's approach) • Development of a corpus of rules for reasoning on the domain (Allen's predicates)

26. Ontology-based Representation and Reasoning about the History of Science Limitations • Methodology scope(applicable in different case studies) • Ontology population(further facts and relations) • Reasoning limitations(additional query modes combining specific rules automatically, systematic approach for identifying domain questions) • Ontology validation(missing validation performed by external experts)

27. Ontology-based Representation and Reasoning about the History of Science Possible enhancements • Application of the ontology scenario(prototype) • Dissemination and interoperability of the data model(e.g. OWL and SPARQL) • Expand time representation • Applying interval approach for historical period • Improving accuracy in dating mechanism • Defining geopolitical naming convention

28. Ontology-based Representation and Reasoning about the History of Science Future work Extend in a PhD project : • Focus on subjectivity and vagueness in historical domains • Link to ontology-based search in digital libraries

29. Ontology-based Representation and Reasoning about the History of Science Summary • The problem • How the use of ontologies can improve access through digital resources in historical domains • Approach and methodology • Developing a history ontology by considering existing ontologies, methodologies and formal representation of temporal information (e.g. Davidson’s and Allen’s approaches). • Outcomes • Elaborating a methodology taking into account the double role of domain expert and ontologist. • Temporal framework for adding temporal concepts and reasoning on events. • Limitations • Limited methodology scope • Ontology population and validation • Reasoning limitations • Future work • Vagueness and subjectivity in historical domains • Digital library scenario