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Ontology Design Patterns and Semantic Abstractions in Ontology Integration     (1A)

Team Leads: Mike Bennett and Gary Berg-Cross     (1A1)

Post-event updates     (1A2)

Short report, also provided to Summit community on 2014-04-01 by discussion list     (1A2A)

The hackathon had participants from (reading from right to left): Australia, Russia, Italy, France, England and the US (East and West coast).     (1A2A1)

The following participated actively in the hackathon:     (1A2A2)

Activities     (1A2A11)

Work was a combination of on screen discussion using shared diagrams and ontology visualization tool, and off-line working on individual ontologies in Prot��g�� by the different participants. Other participants researched possible ontologies and data sources to use, and this initial research was used to decide what area of risk to focus on for this application. The plan was to have enough information to formally specify an ��app�� which might be used on mobile devices. We chose the context of travel risk. The application would provide comparative risk figures for a range of transportation modes against a single specified goal. In the example, the goal was to get from the user��s home in Washington DC to a conference venue in Austin, Texas by 9am on a given day. A number of different options were given for completing this goal. Risks would then be calculated as a product of probability and impact on that goal, with probability being determined as a simple actuarial application of historical data to present probabilities.     (1A2A11A)

We combined concepts in the following areas:     (1A2A11B)

1. Trip data (using an existing Trajectory ontology);     (1A2A11C)

2. Common risk concepts (context-neutral) derived from an existing risk ontology for open source development;     (1A2A11D)

3. Risk Assessment (impacts etc.) �� also extended for positive versus negative outcomes of an event;     (1A2A11E)

4. Travel Adverse Events based on available sources of historical statistical data     (1A2A11F)

(1), (2), (3) For Trip, Common Risk and Risk Assessment, the participants created or adapted formal OWL ontologies in Prot��g��. (2) and (3) were then ingested into the Visual Ontology Modeler (VOM) tool from Thematix Partners. All ontologies were in OWL. Syntaxes used were N3, Turtle and RDF/XML. Diagrams were created in the VOM tool for each ontology to better understand the content, and these were laid out along similar lines to the available conceptual diagrams in the reference sources for this work. The aim was to create an integrating ontology which would import these and define the overall application ontology.     (1A2A11G)

(4) Travel Adverse Events was a bottom-up creation of the ontology directly from the available data. This ontology is very extensive and covers multiple modes of transport and multiple ultimate causes of delays, accidents and the like. A second round of work involved layering the common risk concepts such as for risk event consequences and impacts. This was then ingested into VOM and a set of diagrams created for the main concepts.     (1A2A11H)

We used the on-line sessions to compare thinking about the core risk model and converged on a common conceptual framework which was implemented in whole or in part in the travel events, common concepts and risk assessment ontologies, each of which contained refinements and extensions to that model. The concepts in the Trip ontology were segregated between instance data for the example application, and common concepts for modes of transport (��trains, planes and automobiles��). Most of those common concepts were already in the Travel Adverse Events ontology, while some remained to be added. Those additional concepts were for types of rental car, types of aircraft body and other variables which were assumed to be related to the real-world risk of those travel modes. As a future exercise, once the ontology of these additional concepts is defined, it forms a checklist of sets of historical data to look for. Thus the top-down appreciation of risk factors meets the bottom-up modeling of actual available risk statistics which was carried out during the hackathon.     (1A2A11I)

At the completion of the hackathon, the following things are left as ��an exercise for the reader��:     (1A2A12A)

1. Integrating the concepts into a single ontology; in the end all the concepts and patterns were agreed and incorporated in the individual ontologies and so this exercise would be a relatively simple matter of creating equivalent class assertions. If we were to do this as a commercial product we would re-define the modular structure of the complete set of ontologies to reflect the separate concerns.     (1A2A12B)

2. Additional risk factors in the Trip ontology (rental car types, aircraft body types etc.) which would then form the basis for looking for statistical data sets about these risks.     (1A2A12C)

3. Rolling up types of travel event for which there are statistics (such as bridge strikes, traffic jams) into broader events which are elements of the trajectory itself so as to describe events in terms of missed connections, failure to complete a leg of the journey etc.     (1A2A12D)

As things stand we have sufficient information to specify the ontology and design for a simple travel risk mobile application in which the user may enter a desired time and destination and either enter different travel modes or have these calculated by existing applications which already do this; the application would return comparative risk figures for the different travel options.     (1A2A12E)

An interesting by-product of this work is that there are conceptual similarities between the semantics of the risks in multi-stage journeys, and the semantics of financial credit risk and cashflow payment streams. The journey concepts provide a more accessible way of thinking about these concepts even for the financial industry participants. The similarities between journey trajectories and complex cashflow commitments seems to be amenable to the creation of a common ontology design pattern for the trajectory of cash based on the trajectories ontology.     (1A2A12F)

Post-event commentary on relation of Re-use and ODP hackathon to Ontology Summit 2014 themes and developing synthesis     (1A2B)

...coming     (1A2B1)

Hackathon Details     (1A3)

Participants     (1A3A)

STATUS as at 5pm EDT / 10pm CET 29 March     (1A4)

We have finished for the day and will re-convene tomorrow 30 March at 8am EDT / 1pm CET     (1A4A)

We selected an area of risk to work in, which is the risks of getting from A to B via various means of transport. Team members have identified, built or adapted ontologies for the different dimensions of the problem (trajectory modeling, transport, events which may occur along the way, impacts, core risk concepts and event ontology). Some ontologies were created from scratch from sample data sets, while others were adapted or re-used. We have imported most of the ontologies into our working set of integrated ontologies in the Visual Ontology Modeler tool, and we have made a start in identifying common concepts and differences between concepts in the different ontologies.     (1A4B)

Tomorrow we will create an integrating ontology which imports the ontologies that were created today and unifies them to describe the different dimensions of the problem area. The end result should be an ontology that could be used in an application for travel risk management, along with a simple specification of the app.     (1A4C)

We will use the same dial-in details as before.     (1A4D)

Logistics     (1A5)

Date: Sunday 30 March 2014     (1A5A1)

Integration of Concepts: 08:00 - 09:30 EDT / 13:00 - 14:30 CET     (1A5A2)

Date: Saturday 29 March 2014     (1A5A3)

Times (US Eastern Daylight Time / Central European Time):     (1A5A4)

1. Introduction and task setting: 08:00 - 09:30 EDT / 13:00 - 14:30 CET     (1A5A5)

2. Work off line during the day /interactive calls as required     (1A5A6)

3. Collate and Integrate: 14:00 - 15:30 EDT / 19:00 - 20:30 CET     (1A5A7)

Dial-in and Screen Sharing     (1A5B)

Dial-in details: 1. Please join my meeting. https://www3.gotomeeting.com/join/406359406     (1A5B1)

2. Use your microphone and speakers (VoIP) - a headset is recommended. Or, call in using your telephone.     (1A5B2)

Access Code: 406-359-406 Audio PIN: Shown after joining the meeting     (1A5B21)

Meeting ID: 406-359-406     (1A5B22)

GoToMeeting�� Online Meetings Made Easy��     (1A5B23)

Description     (1A6)

This hackathon will bring together a number of ontologies, ontology design patterns and high level semantic abstractions to create an ontology around the area of risk. The aim would be to think about what it would take to create a basic risk application, though it is unlikely we would get to the application itself in the hackathon time frame. The ontology would use semantic abstractions of risk itself, combining events, situations, probabilities and impacts, identify ontology design patterns for those subject areas so as to be able to integrate data such as accident statistics which would be usable to support a simple application. We would not expect to meet all of the objectives listed below in the hackathon time frame. A possible outcome would be the specification of such an application for future development.     (1A6A)

Hackathon Launch Slides (from 27 Feb) for reference     (1A6B)

Activities     (1A7)

  • Explore and identify ontologies for the different types of content that relate to risk (events, situations, statistics, incidents, goals etc.)     (1A7A)
  • Brainstorm semantic abstractions which would unify these concepts as they relate to risk, and of risk itself     (1A7B)
  • Identify ontology design patterns around these concepts     (1A7C)
  • Consider how to re-use such patterns, for example taking existing patterns for Situation and Event and specializing these for Risky Situation and Risky Event     (1A7D)
  • Stand up an integration ontology for these concepts     (1A7E)

Future work / scope out     (1A7F)

Focus will be on     (1A8)

  • Ontology design patterns versus high level abstractions     (1A8A)
  • Extending design patterns for new application contexts     (1A8B)
  • Use of ontology partitions in integration     (1A8C)
  • Use and interpretation of Linked data using ontologies     (1A8D)
  • Understanding what makes an ontology re-usable and how to assess the ontology for a given use case     (1A8E)

  • Need ideas on this��     (1A9A)
  • Default is to use Prot��g�� with GoToMeeting screen sharing     (1A9B)
  • Ontology visualization tools are available but won't be able to generate RDF/OWL for testing (only useful if we work only at the conceptual level)     (1A9C)
  • Perhaps we can use part of the hackathon to explore possible tools?     (1A9D)
  • Would like to see tooling for business-facing expression of semantic abstractions (or may use some prototype for this based on UML tooling)     (1A9E)


This page has been migrated from the OntologWiki - Click here for original page     (1A9F)