CRMsci

1. CRMsci CRMsci: the Scientific Observation Model Chryssoula Bekiari Center for Cultural Informatics, Institute of Computer Science Foundation for Research and Technology - Hellas CIDOC 2014 Dresden, September 7th, 2014

2. Our motivation To find an ontology for data integration for publishing linked open data about scientific observations in various disciplines To follow the event centric approach of CIDOC CRM and the most common standards used for scientific observations To develop one consistent and generic model with a few disciplinary specialization

3. What is a “class”Some terminology of knowledge representation A class describes a category of items that share one or more commontraitsserving as criteria to identify the items belonging to the class. These traits need not be explicitlyformulated in logical terms, but may be described in a text that refers to a common conceptualisation of domain experts. The sum of these traits is called the intension of the class. A class may be the domain or range of none, one or more properties formally defined in a model. An item that belongs to a class is called an instance (related terms: individuals, tokens etc..)of this class. A class is associated with an open set of real life instances, known as the extension of the class. … “open” is used in the sense that it is generally beyond our capabilities to know all instances of a class in the world and indeed that the future may bring new instances of a class. (related terms: universals, categories, sortal concepts).

4. SubclassSome terminology of knowledge representation • Subclass of a class is a specialization of a class (its superclass). • Specialization is a relationship between two classes ( IsA relationship) and means that: • all instances of the subclass are also instances of its superclass, • the intension of the subclass extends the intension of its superclass, i.e. its traits are more restrictive than that of its superclass • the subclass inherits the definition of all of the properties declared for its superclass without exceptions (strict inheritance), in addition to having none, one or more properties of its own. • A subclass can have more than one immediate superclass and consequently inherits the properties of all of its superclasses (multiple inheritance). • The IsA relationship or specialization between two or more classes gives rise to a structure known as a class hierarchy. • The IsA relationship is transitive and may not be cyclic. • In some contexts (e.g. the programming language C++) the term “derived class “is used synonymously with subclass.

5. ExamplesSome terminology of knowledge representation For example: Every Person IsA Biological Object, or Person is a subclass of Biological Object. Also, every Person IsA Actor. A Person may die. However other kinds of Actors, such as companies, don’t die. Every Biological Object IsA Physical Object. A Physical Object can be moved. Hence a Person can be moved also. Physical Object Actor Biological Object Person

6. PropertySome terminology of knowledge representation “Property” (or “relationship”) is regarded any information element between two classes, … serves to define a relationship of a specific kind between two classes. ... A property plays a role analogous to a grammatical verb, in that it must be defined with reference to both its domain and range, which are analogous to the subject and object in grammar. …a property can be interpreted in both directions, with two distinct, but related interpretations. Properties may themselves have properties that relate to other classes. Properties can also be specialized in the same manner as classes, resulting in IsA relationships between subproperties and their superproperties. In some contexts, the terms “attribute”, “reference”, “link”, “role” or “slot” are used synonymously with property.

7. Example Identifier is identified by (identifies) Physical Object Place occupies (is occupied by) has residence (is residence of) possesses (is possessed by) Rights space-time volume Actor Biological Object has contact point (provides access to) Contact Point has parent (is parent of) Person Tom

8. Example con’t Appellation is identified by (identifies) Physical Object Place occupies (is occupied by) has residence (is residence of) possesses (is possessed by) Rights space-time volume Actor Biological Object has contact point (provides access to) Contact Point has parent (is parent of) Person has residence(is residence of) has parent (is parent of) Martin Tom Athens has residence(is residence of) Heraklion

9. ontologySome terminology of knowledge representation • An ontology is a logical theory accounting for • the kinds and structures of objects, properties, events, processes and relations in every area of reality ( ontological commitment to a particular conceptualization of a part of the world) • ontologies provide models of possible states of affairs in some “universe of discourse” • Ontologies pertains to a perceived truth defined, typically by a group of experts. • Any information system compromises perceived reality with what can be represented on a database (dates!). • An ontology can be implemented in RDF, OWL and others as database schemata.

10. MappingSome terminology of knowledge representation • “Mapping” is the process of defining how each element of a data structure A can be re-encoded in terms of a data structure B minimizing loss of meaning by an automated procedure. • In general, only KR models (ontologies) can be used to integrate and generalize over different data structures so that all data can still be accessed. • This is achieved by mapping from source models (e.g. expressed in XML) to a common ontology, but we can create compatible source models from ontologies.

11. The context • Theories are formalized sets of concepts that organize observations and predict and explain phenomena and demand a solid empirical base of evidence • Raw data provided by the data sets per se are of little use • Scientific observation forms the basis for understanding the phenomena being studied and it is a process by which we advance our understanding of the world. • It is common to all sciences the workflow of forming of a hypothesis to perform and explain observations that are made, the gathering of data, and the drawing of conclusions that confirm or deny the original hypothesis.

12. the scientific observation workflowEpistemological Considerations • Form of a hypothesis to perform an observation (select parameters, properties, signals and the way of converting these to data) • Perform the observations. (They are only concerned with objects or events that are observable, either directly or indirectly ) • Explain the observations made and gather the data • Draw conclusions based upon this data, (make a scientific hypothesis - tentative explanations about the observations made) • Deduce the implications (test them through further observation, compare the results) • Confirm, deny, re-evaluate the original hypothesis • Formulate valid theories (allow others to repeat the observations)

13. Requirements • The scientific data cannot be understood without knowledge about the meaning of the data and the ways and circumstances of their creation. • Scientific data and metadata can be considered as historical records. Therefore relevant observation data cannot be found and understood without metadata about their context. • Scientific observation and machine-supported processing is initiated on behalf of and controlled by human activity. • Things, data, people, times and places in their contexts are causally related by events. • Data Evaluation is based on observation records and hypotheses • Data Simulation may be based on initial observation records or data evaluation.

14. The CRMsci - overview • It facilitates the management, integration, mediation, interchange and access to research data • It provides the appropriate concepts and relationships for monitoring the events and activities • It comprises concepts and relationships for describing metadata about • The human observer, The objectof observation (a “thing”, “something”, a process or a state?), The observation hypothesis(choice of parameters), The identityof the object, if any, The environment, time and location • The conditionof the thing, The instrumentation and methodused • The identity, authenticity and transmission of the produced records

15. Events and Activities …includes complex, composite and long-lasting actions intentionally carried out by Actors resulted in changes of state in the cultural, social, or physical systems documented. changes of states in cultural, social or physical systems, regardless of scale, brought about by a series or group of coherent physical, cultural, technological or legal phenomena. E5 Event E7 Activity S18 Alteration E13 Attribute Assignment E63 Beginning of Existence S5 Inference Making S4 Observation S6 Data Evaluation S8 Categorical Hypothesis Building S17 Physical Genesis S7 Simulation-Prediction E11 Modification S1 Matter Removal E16/S21 Measurement S2 Sample Taking S19 Encounter Event E12 Production E80 Part removal S3 Measurement by Sampling 16

16. Observable Entity E1 CRM Entity …comprises items(E77) or phenomena (E2) that can be observed such as physical things, their behavior, states and interactions or events, either directly by human sensory impression, or enhanced with tools and measurement devices,. S15 Observable Entity E2 Temporal Entity E77 Persistent Item E70 Thing S16 State E5 Event S10 Material Substantial E3 Condition State E53 Place E18 Physical Thing S14 Fluid Body S11 Amount of Matter E55 Type S20 / E26 Physical Feature S12 Amount of Fluid S13 Sample S9 Property Type E25 Man-Made Feature E27 Site S22 Segment of Matter

17. Documenting scientific activities S1 Matter Removal Activities that result in an instance of S10 Material Substantial being decreased by the removal of an amount of matter. S10 Material Substantial comprises constellations of matter with a relative stability of any form sufficient to associate them with a persistent identity, such as being confined to certain extent, having a relative stability of form or structure, or containing a fixed amount of matter. … It is an abstraction of physical substance for solid and non-solid things of matter. E7 Activity S19 Observable Entity E77 Persistent Item S1 Matter Removal O1 diminished O7 contains or confines S10 Material Substantial O2 removed E53 Place O15 occupied S11 Amount of Matter comprises fixed amounts of matter specified as some air, some water, some soil, etc., defined by the total and integrity of their material content. P156 occupies S11 Amount of Matter E18 Physical Thing S14 Fluid Body

18. Documenting scientific activities S1 Matter Removal • Typical scenarios of matter removal includes the: • removal of a component or piece of a physical object • removal of an archaeological or geological layer • taking a tissue sample from a body or a sample of fluid from a body of water • The removed matter may acquire a persistent identity of different nature beyond the act of its removal, such as becoming a physical object in the narrower sense.Such cases should be modeled by using multiple instantiation with adequate concepts of creating the respective items.

19. Documenting scientific activitiesS2 Sample Taking … activities that result in taking an amount of matter as a sample for further analysis from a material substantial. The removed matter (Sample) may acquire a persistent identity of different nature. The place of sampling is used as a reference frame. The sample taken is considered representative for some material qualities of the instance of the material substantial it was taken from. The sample ceases to exist when respective qualities become corrupted such as the purity of water sample etc. . S19 Observable Entity S1 Matter Removal E55 Type O1 diminished E77 Persistent Item O20 sampled from type of part O3 sampled from S2 Sample Taking S10 Material Substantial O2 removed O4 sampled at O5 removed E53 Place S11 Amount of Matter S14 Fluid Body O7 contains or confines O15 occupied S13 Sample Archanes 1lt of water sampled at removed Sampled from The borehole of my village Taking sample on 23/6/2014

20. Documenting scientific activitiesS3 Measurement by Sampling comprises activities of taking a sample and measuring or analyzing it as one managerial unit of activity, in which the sample may not be identified and preserved beyond the context of this activity. Instances of this class are constrained to describe the taking of exactly one sample not further identified, and the dimensions observed by the respective measurement are implicitly understood to describe this particular sample as representative of the place on the instance of S10 Material Substantial from which the sample was taken. S4 Observation S1 Matter Removal O10 observed O11 observedProperty` E55 Type O1 diminished S15 Observable Entity S9 Property Type O20 sampled from type of part S21 Measurement O3 sampled from S10 Material Substantial S2 Sample Taking P40 observed dimension O4 sampled at O5 removed E54 Dimension E53 Place S13 Sample Nitrate dimension O7 contains or confines P90 has value Water part S3 Measurement by Sampling P91 has unit P40 observed dimension 45 percentage concentration Archanes O20 sampled from type of part sampled at nitrate concentration Taking sample on 23/6/2014 O11 observedProperty` O3 sampled from The borehole of my village

21. S2 Sample Taking Documenting scientific activities S19 Observable Entity Argue about authenticity E7 Activity E2 Temporal Entity E77 Persistent Item E55 Type S1 Matter Removal E70 Thing O20 sampled from type of part O1 diminished E3 Condition State E57 Material P46 is composed of P45 consists of P44 has condition O3 sampled from S2 Sample Taking S10 Material Substantial O2 removed O4 sampled at O5 removed E53 Place E18 Physical Thing S11 Amount of Matter S14 Fluid Body O7 contains or confines P156 occupies S13 Sample O15 occupied

22. S17 Physical Genesis Documenting scientific activities E7 Activity particular value range of the properties of a particular thing or things over a time-span O13 triggers “Solar explosions” S4 Observation E5 Event S16 State O14 initializes “Melting ice” E53 Place “depositional features” O21 has found at “petrification” E63 Beginning of Existence S18 Alteration S19 Encounter Event O19 has found object O18 altered E18 Physical Thing S17 Physical Genesis S20 / E26 Physical Feature O17 generated S22 Segment of Matter …comprises physical material in a relative stability of form within a specific spacetime volume. …is subject to a specific interest for and investigations of the geometric arrangement of physical features or parts of them on or within the specified S22 Segment of Matter. …It comes into existence as being an object of discourse through S4 Observation or declaration …exists as long as there is no modification of the geometric arrangement of its particles. O22 partly or completely contains(is part of) P156 is occupied S22 Segment of Matter “deposition layers” O23 is defined by(defines) E92 Space Time Volume

23. S4 Observation Documenting scientific activities E7 Activity …it is a kind of human activity: at some Place and within some Time-Span, certain Physical Things and their behavior and interactions are observed, either directly by human sensory impression, or enhanced with tools and measurement devices. P2 has type E13 Attribute Assignment E55 Type S5 Inference Making S4 Observation O11 observedProperty O10 observed S9 Property Type S19 Observable Entity O16 described S6 Data Evaluation O24 measured(was measured by) S40 Encounter Event E5 Event S21 Measurement O14 assigned dimension E70 Thing P40 observed dimension O17 has dimension S21 Measurement comprises actions of measuring instances of E2 Temporal Entity or E77 Persistent Items, properties of physical things, or phenomena, states and interactions or events, that can be determined by a systematic procedure. Primary data from measurement devices are regarded to be results of an observation process E54 Dimension S10 Material Substantial E18 Physical Thing

24. S19 Encounter Event Documenting scientific activities comprises activities of S4 Observation where an E39 Actor encounters an instance of E18 Physical Thing of a kind relevant for the mission of the observation or regarded as potentially relevant for some community. This observation produces knowledge about the existence of the respective thing at a particular place in or on surrounding matter. …The observer may recognize or assign an individual identity of the thing encountered or regard only the type as noteworthy in the associated documentation or report.  In archaeology there is a particular interest if an object is found “in situ”, i.e. … The surrounding matter with the relative position of the object in it as well as the absolute position and time of the observation may be recorded in order to enable inferences about the history of the E18 Physical Thing.  In Biology, additional parameters may be recorded like the kind of ecosystem, if the biological individual survives the observation, what detection or catching devices have been used or if the encounter event supported the detection of a new biological kind (“taxon”). It generalizes over the Darwin Core notion of Occurrence and the archaeological concept of “finds”. Whereas the definition of “find” is relative to a state of knowledge, encounter is objective.

25. S19 Encounter Event Documenting scientific activities E18 Physical ThingSphaero-levantina-003 O32 has found object E21 Person Sarah Faulwetter E53 PlaceIsrael O7 contains or confines (is contained or confined) P14 carried out by S40 Encounter Event urn:catalog:IOL:POLY:Sphaerosyllis-levantina-ALA-IL-7-Oct.2009 E53 Place Haifa Bay Ecosystem Station 1 O21 has found at(witnessed) E55 Type P2 has type P4 has timespan Ecosystem Typesandy - muddy sediments E52 Timespan 7 October 2009 P125 used object of type P127 has broader term Equipment TypeWA265/SS214 Equipment TypeVan Veen Grab

26. Making assertionsS5 Inference Making E1 CRM Entity comprises the action of making propositions and statements about particular states of affairs in reality or in possible realities or categorical descriptions of reality by using inferences from other statements based on hypotheses and any form of formal or informal logic. P16 usedspecificobject (wasusedfor) E70 Thing P15was influenced by (influenced ) P17wasmotivatedby (motivated) P33 used specific technique (was used by) E7 Activity E29 Design or Procedure E13 Attribute Assignment 010 Assigned dimension (dimension was assigned by) E54 Dimension S5 Inference Making S6 Data Evaluation 011 described ( was described by) S19 Observable Entity S8 Categorical Hypothesis Building concluding propositions on a respective reality from observational data by making evaluations based on mathematical inference rules and calculations using established hypotheses assumptions developed by “induction” from finite numbers of observation of particular thing. Based on inference rules and theory S7 Simulation-Prediction executing algorithms or software for simulating the reality or not by using mathematical models 27

27. Applications • Informed by the IAM model (argumentation) • EU FP7 - PSPInGeoClouds • European Space Agency: satellite data • EU FP7-INFRASTRUCTURES-2012-1ARIADNE • Supermodel for CRMarchaeo • EU - FP7 - CP & CSA iMarine • Informs and complements MarineTLO • Extended MarineTLO used in LifeWatch Greece, being promoted to LifeWatch

28. Conclusions • Future work: • Needed: Still to be done: Specializations into analytical methods and reference data sets • Links: http://www.ics.forth.gr/isl/CRMext/CRMsci.rdfs