Marquette, Michigan, United States
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Publications

  • Deystifying OWL for the Enterprise

    Springer

    A large and growing number of organizations are using the Web Ontology Language (OWL) as as part of the Semantic Web technology stack. The need for ontologists is increasing faster than the number and variety of available resources for learning OWL. This is especially true for the primary target audience for this book: modelers who want to build OWL ontologies for practical use in enterprise and government settings. The purpose of this book is to speed up the process of learning and mastering...

    A large and growing number of organizations are using the Web Ontology Language (OWL) as as part of the Semantic Web technology stack. The need for ontologists is increasing faster than the number and variety of available resources for learning OWL. This is especially true for the primary target audience for this book: modelers who want to build OWL ontologies for practical use in enterprise and government settings. The purpose of this book is to speed up the process of learning and mastering OWL. To that end, the focus is on the 30% of OWL that gets used 90% of the time. Others who may benefit from this book include technically oriented managers, semantic technology developers, undergraduate and post-graduate students, and finally, instructors looking for new ways to explain OWL. The book unfolds in a spiral manner, starting with the core ideas. Each subsequent cycle reinforces and expands on what has been learned in prior cycles and introduces new related ideas. Part 1 is a cook's tour of ontology and OWL, giving an informal overview of what things need to be said to build an ontology, followed by a detailed look at how to say them in OWL. This is illustrated using a healthcare example. Part 1 concludes with an explanation of some foundational ideas about meaning and semantics to prepare the reader for subsequent chapters. Part 2 goes into depth on properties and classes, which are the core of OWL. There are detailed descriptions of the main constructs that you are likely to need in every day modeling, including what inferences are sanctioned. Each is illustrated with real-world examples. Part 3 explains and illustrates how to put OWL into practice, using examples in healthcare, collateral, and financial transactions. A small ontology is described for each, along with some key inferences. Key limitations of OWL are identified, along with possible workarounds. The final chapter gives a variety of practical tips and guidelines to send the reader on their way.

    See publication

Projects

  • Global Healthcare Company: advice and training

    - Present

    Provide advice on how to set up an IT research function, Conduct two day semantic technology training.

  • Top tier global investment bank: Intercompany Agreements

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    Played key role on team that delivered a working prototype application to allow subject matter experts to enter service level agreements into a database. Interviewed SMEs to learn about service agreements between different parts of the company. Used agile method to build and refine an ontology to represent the agreements, in conjunction with building an ontology driven application to create service level agreements and put them in a triple store. This is in response to regulators requiring...

    Played key role on team that delivered a working prototype application to allow subject matter experts to enter service level agreements into a database. Interviewed SMEs to learn about service agreements between different parts of the company. Used agile method to build and refine an ontology to represent the agreements, in conjunction with building an ontology driven application to create service level agreements and put them in a triple store. This is in response to regulators requiring banks that are ‘too big to fail’ to have resolution plans in place, in the event of a repeat of what happened to Lehmann Brothers. A traditional document-based approach requires fully manual exploration of a huge tangle of unstructured agreements. By having the agreements in a triple store, the ability to analyse and understand the complex relationships is dramatically improved.

  • National Agricultural Library: Training, Mentoring, Educational Materials Ontology

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    Gave a tailored version of our standard 6-day class on designing and building business ontologies. Gave advice on how to use semantic technology in house. Mentored 3 employees by leading them first hand through our process of ontology design to solve a data integration problem they had with a number of heterogeneous educational materials databases. Led them through an interview with a subject matter expert and followed that with a review of our class materials, some design sessions and then...

    Gave a tailored version of our standard 6-day class on designing and building business ontologies. Gave advice on how to use semantic technology in house. Mentored 3 employees by leading them first hand through our process of ontology design to solve a data integration problem they had with a number of heterogeneous educational materials databases. Led them through an interview with a subject matter expert and followed that with a review of our class materials, some design sessions and then creating the ontology itself.

  • Major player in financial services industry, Ontology for Data Integration

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    Played key role on team that delivered a working prototype application to allow subject matter experts to enter service level agreements into a database. Interviewed SMEs to learn about service agreements between different parts of the company. Used agile method to build and refine an ontology to represent the agreements, in conjunction with building an ontology driven application to create service level agreements and put them in a triple store. This is in response to regulators requiring...

    Played key role on team that delivered a working prototype application to allow subject matter experts to enter service level agreements into a database. Interviewed SMEs to learn about service agreements between different parts of the company. Used agile method to build and refine an ontology to represent the agreements, in conjunction with building an ontology driven application to create service level agreements and put them in a triple store. This is in response to regulators requiring banks that are ‘too big to fail’ to have resolution plans in place, in the event of a repeat of what happened to Lehmann Brothers. A traditional document-based approach requires fully manual exploration of a huge tangle of unstructured agreements. By having the agreements in a triple store, the ability to analyse and understand the complex relationships is dramatically improved.

  • Office of the Secretary of State, the state of Washington

    -

    Created an ontology to support the design of a new online system for registration and filing of documents for corporations and charities. One of the three options offered was a semantic approach. The discovery process involved a combination of interviews with SMEs and analyzing thousands of specific regulations from the statutes related to registration and filing. We explained the ontology in non-technical terms, with the help of a summary diagram containing all the essential elements on a...

    Created an ontology to support the design of a new online system for registration and filing of documents for corporations and charities. One of the three options offered was a semantic approach. The discovery process involved a combination of interviews with SMEs and analyzing thousands of specific regulations from the statutes related to registration and filing. We explained the ontology in non-technical terms, with the help of a summary diagram containing all the essential elements on a single 11x17 sheet. Our designs and recommendations were used to issue the subsequent call for proposals to implement the system. We were not allowed to propose for that work, to avoid conflict of interest.

  • Top tier global investment bank: Faceted taxonomy of risk controls

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    We built a faceted taxonomy to represent approximately 8000 specific control measures that are put into place to mitigate risk. We conducted numerous sessions with subject matter experts all around the globe to understand the essential nature of the controls, that were being managed in a spreadsheet. Because they were mostly expressed as unformatted text, there was no practical way to systematically compare and analyze the controls as a whole. Through an interactive process, we identified and...

    We built a faceted taxonomy to represent approximately 8000 specific control measures that are put into place to mitigate risk. We conducted numerous sessions with subject matter experts all around the globe to understand the essential nature of the controls, that were being managed in a spreadsheet. Because they were mostly expressed as unformatted text, there was no practical way to systematically compare and analyze the controls as a whole. Through an interactive process, we identified and evaluated numerous candidate facets, and possible values for each and settled on a final result. To test whether they were adequate, we conducted a pilot whereby a half a dozen SMEs each re-expressed several dozen of the controls that they managed, using the faceted taxonomy. This resulted in a few relatively minor changes to the taxonomy, confirming the adequacy of the facets and values for the task. In all, a few hundred controls were so-encoded. The idea is that instead of having 8000 controls that are hard to compare and manage, there are now just a few several dozen things to learn: a handful of facets, and for each a handful of possible values. This has the potential to dramatically simplify the process of managing and evolving the controls.

    As an extra, we also delivered to the client, a formal mapping from the informal terms used in the facets and values, to a formal ontology that we had built in a prior engagement. As far as we know, this is a novel technique for unifying taxonomies and ontologies has never been done before. One of the intangible impacts of this work is the new way of thinking about knowledge assets as faceted taxonomies. They are applying this to good advantage in their ongoing work. The client is now poised to unify a broader set of knowledge assets.

  • Sentara Healthcare Enterprise Ontology (SHEO)

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    April 2011 – March 2012; and again July-August, 2013.
    Created the world’s first comprehensive ontology covering the business of healthcare. Sentara Healthcare owns and operates several hospitals and a wide variety of other care facilities, and has their own health insurance subsidiary. Identified a range of topics to cover, and conducted twelve 3-hour sessions interviewing a total of over 100 of their best and brightest employees to learn about their business. The scope of the ontology...

    April 2011 – March 2012; and again July-August, 2013.
    Created the world’s first comprehensive ontology covering the business of healthcare. Sentara Healthcare owns and operates several hospitals and a wide variety of other care facilities, and has their own health insurance subsidiary. Identified a range of topics to cover, and conducted twelve 3-hour sessions interviewing a total of over 100 of their best and brightest employees to learn about their business. The scope of the ontology includes: scientific body of knowledge, care delivery and coordination, registration and billing, health insurance, regulations, accreditations, human resources, business strategy, marketing, finance, and supply chain. To communicate the ontology to a non-technical audience, created a summary diagram showing the essential elements of the ontology and their relationships. It all fits onto a convenient 11 x 17 sheet of paper.

    The ontology was used afterwards as the basis for a linked data application for asthma patients, combining and correlating things like pollen counts and patient visits to reduce doctor and hospital visits. Worked with their team to leverage the ontology for search over their corporate web.

  • Top tier global investment bank (part 1/2): "Fix" an Activity Taxonomy

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    Addressed and corrected a number of problems with an existing taxonomy of activities that was difficult to evolve, maintain and reuse. A root problem was the fact that the taxonomy consisted of unstructured entries in a spreadsheet. Conducted a series of interactive sessions, eliciting and evaluating candidate facets for classifying activities, and possible values for those facets. The original taxonomy was thus decomposed into this set of facets and values. Re-composed the original...

    Addressed and corrected a number of problems with an existing taxonomy of activities that was difficult to evolve, maintain and reuse. A root problem was the fact that the taxonomy consisted of unstructured entries in a spreadsheet. Conducted a series of interactive sessions, eliciting and evaluating candidate facets for classifying activities, and possible values for those facets. The original taxonomy was thus decomposed into this set of facets and values. Re-composed the original taxonomy using the facets into a more useful form which is much easier to evolve and maintain, Furthermore, the facets and values are able to be leveraged by other groups who were struggling to make use the taxonomy in its original form.

  • Top tier global investment bank (part 2/2): Build division wide ontology

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    Created a division-wide ontology that covered the full scope of back office operations at a major investment bank. This was a significant undertaking, involving the following major topics: risk, controls, process, assigning work, financial instruments and markets, parties, business relationships, trades, transactions, and computing platforms. Went through many iterations of the interview, model, review cycle before reaching consensus in all the areas. In the end, the model was not very...

    Created a division-wide ontology that covered the full scope of back office operations at a major investment bank. This was a significant undertaking, involving the following major topics: risk, controls, process, assigning work, financial instruments and markets, parties, business relationships, trades, transactions, and computing platforms. Went through many iterations of the interview, model, review cycle before reaching consensus in all the areas. In the end, the model was not very large, consisting of a few hundred classes and a few hundred properties. Continued to hone our techniques for visualizing, presenting and explaining the ontology to non-technical audiences.

  • Global consumer products manufacturing firm: built materials ontology

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    Created a materials ontology for a major organization within a global manufacturing company. The core concepts revolved around materials, intermediate and finished products, and technical specifications. The scope also included safety regulations, toxic exposure risk simulation and analysis, hazard profiles, product registration, batches, lots and the supply chain. Technical specifications are highly complex, including allowable ranges in performance specifications, manufacturing recipes...

    Created a materials ontology for a major organization within a global manufacturing company. The core concepts revolved around materials, intermediate and finished products, and technical specifications. The scope also included safety regulations, toxic exposure risk simulation and analysis, hazard profiles, product registration, batches, lots and the supply chain. Technical specifications are highly complex, including allowable ranges in performance specifications, manufacturing recipes along with test procedures to measure against performance specifications. A particularly challenging aspect was how to represent product models and allowable ranges for specifications, which would be most easily handled in a second order logic notation. In both cases, special techniques and great care were required to express these central concepts into OWL. Went through many iterations of the interview, model, review cycle before reaching consensus in all the topic areas. Tested the adequacy of the ontology through a series of sessions where we elicited use case scenarios for how to leverage the ontology. This also fed into the discussion for the next phase of work.

  • Global legal research company: improved content data model, semantic technology training

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    Analyzed and gave feedback on an in-house Entity-Relationship (ER) data model for all of their legal content. There were many different components, including persons and their roles (e.g. lawyer, judge, client), addresses, jurisdictions, organizations, statutes, case law, geospatial, among others. Developed and delivered ‘train the trainer’ materials showing them how to use Protégé and some specialized software to see all their Entity Relationship models at once. This allowed them to more...

    Analyzed and gave feedback on an in-house Entity-Relationship (ER) data model for all of their legal content. There were many different components, including persons and their roles (e.g. lawyer, judge, client), addresses, jurisdictions, organizations, statutes, case law, geospatial, among others. Developed and delivered ‘train the trainer’ materials showing them how to use Protégé and some specialized software to see all their Entity Relationship models at once. This allowed them to more easily ensure that the model was correct. They implemented this new approach which is now integrated into their process for ongoing evolution of their models. After two engagements, they were converted from being ‘curious’ about semantic technology, to ‘definite believers’ in its usefulness for their purposes.

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