1. Co-funded by the European Union under FP7-ICT-2009-6 Co-ordinated by aparsen.eu #APARSEN Provenance Interoperability and Reasoning Yannis Tzitzikas Assistant Professor, Computer Science Dep. University of Crete, and FORTH-ICS Webinar, July 2012

2. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Outline Provenance (why it is important) Provenance Interoperability Provenance-based Inference Rules 1/10/2016Yannis Tzitzikas, FORTH-ICS2

3. July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Why is Provenance Important? anon4877_base_20060331.jpganon4877_lesion_20060401.jpg How were these images created? Was any pre-processing applied to the raw data? What’s the difference? Who created them? Are they really from the same patient? Reproducibility Data quality Attribution Informational

4. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Provenance & Interoperability (1/2) Motivation There are several conceptual models for representing provenance. The availability of mappings between these models is crucial for interoperability, e.g. for exchanging and integrating provenance information (in the context of mediator or warehouse approach) Several mappings have been defined by the W3C Provenance Incubator group: –Provenir ontology, Provenance Vocabulary, Proof Markup Language, Dublin Core, PREMIS, WOT Schema, SWAN Provenance Ontology, Semantic Web Publishing Vocabulary, Changeset Vocabulary, OPM (Open Provenance Model) –OPM is used as the reference model 1/10/2016Yannis Tzitzikas, FORTH-ICS

5. July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Provenance & Interoperability (2/2) CIDOC CRM DIGITAL ISO 21127:2006 OPM Our Objective –Define mappings between OPM and CRM Dig. CRMdig is an extension of the ISO 21127 (CIDOC CRM ontology) for capturing digital objects. CIDOC CRM contains 82 classes and 146 properties, while its extension CRMdig currently contains 31 classes and 70 properties. Both (OPM and CRM Dig) are very good hubs (mappings to other models exist) APARSEN Contribution

6. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu PROVENANCE-BASED INFERENCE RULES

7. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Motivation (general) Time Storage Space Data Production Extra data for digital preservation Adoption of Inference

8. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Provenance-based Inference Rules Motivation –Reduce the amount of provenance information that has to be recorded (in various workflow systems) Additional benefits: reduction of the required storage space, easier error correction The Approach –Identify and specify some basic provenance-based inference rules –In addition, tackle the knowledge evolution requirements The rising question is how we can satisfy update requests while still supporting the aforementioned (application specific) provenance-based inference rules. Our Results –Three basic inference rules were identified (R1-R3). In brief they involve: carriedOut(Actor, Activity), wasUsedFor(Device,Activity), wasPresentAt(InformationObject,Event, PhysicalObject) –We specified a set of basic change operations which can tackle the evolution requirements: Operations: Add, Disassociate, Contract Composite operations (e.g. replace) can be defined by synthesizing the basic ones. 1/10/2016Yannis Tzitzikas, FORTH-ICS8

9. July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu The three inference rules E7 Activity E73 Information Object E24 Physical Man-Made Thing P128 carries (is carried by) E5 Event P12 was present at (occurred in the presence of ) P12 was present at (occurred in the presence of ) IsA P9 forms part of (consists of) E39 Actor P14 carried out by (performed) E22 Man-made Object (Device) P16 was used for (used specific object) P46 forms part of (is composed of) IsA The involved part of ISO 21127 (contains classes and properties that are found almost in every provenance model)

10. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu The three inference rules 1/10/2016Yannis Tzitzikas, FORTH-ICS10 R1: If an actor has carried out one activity, then (s)he has carried out all of its subactivities. R2: If an object was used for an event, then all parts of the object were used in that event too R3: If a physical object that carries an information object was present at an event then that information object was present at the event too.

11. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Inference rules and Knowledge Evolution The use of inference rules introduces difficulties with respect to the evolution of knowledge We identified two ways to deal with deletions in this context, based on the philosophical stance against explicit (ingested) knowledge and implicit (inferred) one (foundational and coherence semantics). Based on these we specified a number of update operations that allow knowledge updating under said inference rules. 1/10/2016Yannis Tzitzikas, FORTH-ICS11

12. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu A very small example (of inference rules and knowledge evolution) 1/10/2016Yannis Tzitzikas, FORTH-ICS12 George Writing the paper P14 carried out by Writing 1 st section P9 forms part of P14 carried out by Writing 1 st parag P9 forms part of Writing 2 nd parag P14 carried out by Consider a KB containing the activities of writing a paper George has been propagated to all the subactivities of writing the paper by rule R1 Update request: George was not responsible for writing 1 st parag Two cases: Performer disassociation Performer contraction

13. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Closing Remarks Provenance Interoperability The availability of mappings between provenance models is crucial for interoperability. In the context of WP24 we discussed the mapping between OPM and ISO 21127 (CRMdig). Provenance-based Inference Rules We motivated the need for provenance-based inference rules. We identified three basic rules accompanied by real world examples. Provenance-based Inference Rules and Knowledge Evolution The use of inference rules introduces difficulties with respect to the evolution of knowledge We identified two ways to deal with deletions in this context (foundational and coherence semantics) Based on these we specified a number of update operations that allow knowledge updating under said inference rules. Although we confined ourselves to CRMdig, and to three specific inference rules, the general ideas behind our work (including the discrimination between foundational and coherence semantics of deletion) can be applied to other models and/or sets of inference rules. 1/10/2016Yannis Tzitzikas, FORTH-ICS13

14. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Contributing to the VCoE Expertise in conceptual modeling for provenance, related standards and mappings between them for tackling the fragmentation Expertise in inference rules for provenance (theory, implementation of theory in various technologies) as a means to obtain more complete provenance information, and thus more trust. Expertise in the related implementation issues For more see APARSEN Internal Deliverable ID24.1 Provenance Interoperability and Mappings The publication –C. Strubulis, Y. Tzitzikas, M. Doerr and G. Flouris, Evolution of Workflow Provenance Information in the Presence of Custom Inference Rules, 3rd International Workshop on the role of Semantic Web in Provenance Management (SWPM'12), co-located with ESWC'12, Crete, June 2012 Future Development of best practices for the implementation of such inference rules and change operations over the various existing technologies (RDF triple stores, rule engines and query languages). FORTH is currently doing experiments, the results will be made available.

15. Yannis Tzitzikas, FORTH-ICS July 2012 Co-funded by the European Union under FP7-ICT-2009-6 aparsen.eu Thanks for your attention Information Systems Laboratory