2016 and continuing posts on ontologies

Well, 2015 seems to have gotten away from me. Over the last year, I have been working to design and implement several ontologies for policy-based management. The work is based on Complexible's Stardog graph database, with services accessed through a RESTful API, and with a front-end, single-page web application created with Bootstrap and Backbone. It has been a blast working with and learning all these technologies, and my new year's resolution is to get back into writing my blog and share some of my learnings.

Another thing that I am doing is related to the International Association for Ontology and Its Applications (IAOA). More specifically, I am a part of the Semantic Web Applied Ontologies Special Interest Group (SWAO SIG). The SIG is continuing the work of the 2014 Ontology Summit and facilitating discussions of ontologies and their development and application. I will be contributing to those discussions in 2016, and started with a short post on the various definitions of the term, ontology. Check out the SWAO link above for the discussion!

That's it for now. Happy 2016!

Andrea

Ontology Summit 2014 and the communique

Ontology Summit 2014 officially concluded with the symposium on April 28-29. There were some great keynotes, summary presentations and discussions. You can see most of the slides on the Day 1 and Day 2 links, and can also check out the online, unedited Day 1 chat and Day 2 chat.

The main "output" of each Ontology Summit is a communique. This year's communique is titled Semantic Web and Big Data Meets Applied Ontology, consistent with the Summit theme. Follow the previous link to get the full document, and consider endorsing it (if you are so inclined). To endorse the communique, send an email to with the subject line: "I hereby confirm my endorsement of the OntologySummit2014 Communique" and include (at least) your name in the body of the email. Other remarks or feedback can also be included. And, I would encourage you to add your thoughts.

I want to provide a quick list of the high points of the communique (for me):

• In the world of big data, ontologies can help with semantic integration and mapping, reduction of semantic mismatches, normalization of terms, and inference and insertion of metadata and other annotations.
• Development approaches that involve a heavy-weight, complete analysis of "the world" are evolving to lighter weight approaches. This can be seen in the development of ontology design patterns, the use of ontologies in Watson, and the bottom-up annotation and interlinking approaches of web/RESTful services (as "Linked Services").
• There are some best practices that can be applied for sharing and reuse to succeed (and since I drafted most of these best practices, I am just copying them directly below :-)):
  • Wise reuse possibilities follow from knowing your project requirements. Competency questions should be used to formulate and structure the ontology requirements, as part of an agile approach. The questions help contextualize and frame areas of potential content reuse.
  • Be tactical in your formalization. Reuse content based on your needs, represent it in a way that meets your objectives, and then consider how it might be improved and reused. Clearly document your objectives so that others understand why you made the choices that you did.
  • Small ontology design patterns provide more possibilities for reuse because they have low barriers for creation and potential applicability, and offer greater focus and cohesiveness. They are likely less dependent on the original context in which they were developed.
  • Use "integrating" modules to merge the semantics of reused, individual content and design patterns.
  • Separately consider the reuse of classes/concepts, from properties, from individuals and from axioms. By separating these semantics (whether for linked data or ontologies) and allowing their specific reuse, it is easier to target specific content and reduce the amount of transformation and cleaning that is necessary.
  • RDF provides a basis for semantic extension (for example, by OWL and RIF). But, RDF triples without these extensions may be underspecified bits of knowledge. They can help with the vocabulary aspects of work, but formalization with languages like OWL can more formally define and constrain meaning. This allows intended queries to be answerable and supports reasoning.
  • Provide metadata (providing definitions, history and any available mapping documentation) for your ontologies and schemas. Also, it is valuable to distinguish constraints or concepts that are definitive (mandatory to capture the semantics of the content) versus ones that are specific to a domain. Domain-specific usage, and "how-to" details for use in reasoning applications or data analytics are also valuable. Some work in this area, such as Linked Open Vocabularies and several efforts in the Summit's Hackathon, is underway and should be supported.
  • Use a governance process for your ontologies (and it would be even better if enforced by your tooling). The process should include open consideration, comment, revision and acceptance of revisions by a community.
• Lastly, what are some of the interesting areas of investigation? One area, certainly, is the need for tooling to better support modular ontology development, integration, and reuse. Another is support for hybrid reasoning capabilities - supporting both description logic and first-order logic reasoning, and both logical and probabilistic reasoning. Third, tooling that combines data analytic and ontological processing would be valuable to make sense of "big data", and aid in the dissemination of the resulting knowledge to users and for decision support. To truly address this last area, it may be necessary to create specialized hardware and processing algorithms to combine and process data using the graph-structured representations of ontologies.

That's it for me, but please take a look at the communique, draw your own conclusions, and determine your own highlights.

Andrea

Ontology Reuse and Ontology Summit 2014

I've been doing a lot of thinking about ontology and vocabulary reuse (given my role as co-champion of Track A in Ontology Summit 2014). We are finally in our "synthesis" phase of the Summit, and I just updated our track's synthesis draft yesterday.

So, while this is all fresh in my mind, I want to highlight a few key take-aways ... For an ontology to be reused, it must provide something "that is commonly needed"; and then, the ontology must be found by someone looking to reuse it, understood by that person, and trusted as regards its quality. (Sam Adams made all these points in 1993 in a panel discussion on software reuse.) To be understood and trusted, it must be documented far more completely than is (usually) currently done.

Here are some of the suggestions for documentation:

• Fully describe and define each of the concepts, relationships, axioms and rules that make up the ontology (or fragment)
• Explain why the ontology was developed
• Explain how the ontology is to be used (and perhaps how the uses may vary with different triple stores or tools)
• Explain how the ontology was/is being used (history) and how it was tested in those environment(s)
• Explain differences, if it is possible to use the ontology in different ways in different domains and/or for different purposes
• Provide valid encoding(s) of the ontology
• These encodings should discuss how each has evolved over time
• "Valid" means that there are no consistency errors when a reasoner is run against the ontology
• It is also valuable to create a few individuals, run a reasoner, and make sure that the individual's subsumption hierarchy is correct (e.g., an individual that is supposed to only be of type "ABC", is not also of type "DEF" and "XYZ")
• Multiple encodings may exist due to the use of different syntaxes (Turtle and OWL Functional Syntax, for example, to provide better readability, and better version control, respectively) and to specifically separate the content to provide:
• A "basic" version of the ontology with only the definitive concepts, axioms and properties
• Other ontologies that add properties and axioms, perhaps to address particular domains
• Rules that apply to the ontology, in general or for particular domains

Defining much of this information is a goal of the VOCREF (Vocabulary and Ontology Characteristics Related to Evaluation of Fitness) Ontology, which was a Hackathon event in this year's Ontology Summit. I participated in that event on March 29th and learned a lot. A summary of our experiences and learnings is posted on the Summit wiki.

VOCREF is a good start at specifying characteristics for an ontology. I will certainly continue to contribute to it. But, I also feel that too much content is contained in the vocref-top ontology (I did create an issue to address this). That makes it too top-heavy and not as reusable as I would like. Some of the content needs to be split into separate ontologies that can be reused independently of characterizing an ontology. Also, the VOCREF ontology needs to "dog-food" its own concepts, relationships, ... VOCREF itself needs to be more fully documented.

To try to help with ontology development and reuse, I decided to start a small catalog of content (I won't go so far as to call it a "repository"). The content in the catalog will vary from annotation properties that can provide basic documentation, to general concepts applicable to many domains (for example, a small event ontology), to content specific to a domain. The catalog may directly reference, document and (possibly) extend ontologies like VOCREF (with correct attribution), or may include content that is newly developed. For example, right now, I am working on some general patterns and a high level network management ontology. I will post my current work, and then drill-down to specific semantics.

All of the content will be posted on the Nine Points github page. The content will be fully documented, and licensed under the MIT License (unless prohibited by the author and the licensing of the original content). In addition, for much of the content, I will also try to discuss the ontology here, on my blog.

Let me know if you have feedback on this approach and if there is some specific content that you would like to see!

Andrea

Ontology Summit 2014 Hackathon, Mar 29 - Ontological Catalog Project

Ontology Summit 2014 Hackathon is tomorrow (Saturday, Mar 29). There are six proposals, all of which look really interesting! You can see a summary of each of them on the Hackathon wiki page.

As for me, I will be participating in the one that is listed last :-), with Amanda Vizedom. But, I have to warn you that the name is a bit overwhelming ... "An ontological catalogue of ontology and metadata vocabulary characteristics relevant to suitability for semantic web and big data applications". Whew!

Really, it is about creating simple sets of concepts (i.e., a "catalog") to characterize vocabularies, models and ontologies. The catalog will be created in GitHub as a publicly available, open-source ontology (collaboratively developed and extensible over time). This Hackathon project is all about the problem of reuse ... You can't reuse something unless you understand not only what its contents are, but the intent behind creating the thing, how it was designed to be used, etc. This is summarized in the following quote from the Summit's Track A synthesis:

Documentation must include the basic details of the semantics, but also the range of conditions, contexts and intended purposes for which the content was developed. It was recommended that standard metadata for reuse be defined and complete exemplars provided.

If you are interested in participating, the kickoff is 10am EDT tomorrow using Google Hangout. Working materials are available at https://github.com/ajvizedom/vocref. If you are interested, have a look at the GitHub site, "watch" the repository, and become a contributor by adding yourself to the team roster on the project's wiki page.

Looking forward to working with you tomorrow!

Andrea

Reuse of ontology and model concepts

Reuse is a big topic in this year's Ontology Summit.  In a Summit session last week, I discussed some experiences related to my recent work on a network management ontology.  The complete presentation is available from the Summit wiki.  And, I would encourage you to look at all the talks given that day since they were all very interesting! (The agenda, slides, chat transcript, etc. are accessible from the conference call page.)

But ... I know that you are busy.  So, here are some take-aways from my talk:

• What were the candidates for reuse?  There were actually several ontologies and models that were looked at (and I will talk about them in later posts), but this talk was about two specific standards:  ISO 15926 for the process industry, and FIBO for the financial industry.
• Why did we reuse since there was not perfect overlap of the chosen domain models/ontologies and network management?  Because there was good thought and insight put into the standards, and there also was tooling developed that we want to reuse.  Besides that, we have limited time and money - so jump starting the development was "a good thing". 
• Did we find valuable concepts to reuse?  Definitely.  Details are in the talk but two examples are:
• Defining individuals as possible versus actual.  For anyone that worries about network and capacity planning, inventory management, or staging of new equipment, the distinction between what you have now, what you will have, and what you might have is really important.
• Ontology annotation properties.  Documentation of definitions, sources of information, keywords, notes, etc. are extremely valuable to understand semantics.  I have rarely seen good documentation in an ontology itself (it might be done in a specification that goes with the ontology).  The properties defined and used in FIBO were impressive.
• Was reuse easy?  Not really.  It was difficult to pull apart sets of distinct concepts in ISO 15926, although we should have (and will do) more with templates in the future.  Also, use of OWL was a mapping from the original definition, which made it far less "natural"/native.  FIBO was much more modular and defined in OWL.  But due to ontology imports, we pretty much ended up loading and working through the complete foundational ontology.  

Given all this, what are some suggestions for getting more reuse?

1. Create and publish more discrete, easily understood "modules" that:
• Define a maximum of 12-15 core entities with their relationships (12-15 items is about the limit of what people can visually retain)
• Document the assumptions made in the development (where perhaps short cuts were made, or could be made)
• Capture the axioms (rules) that apply separately from the core entities (this could allow adjustments to the axioms or assumptions for different domains or problem spaces, without invalidating the core concepts and their semantics)
• Encourage evolution and different renderings of the entities and relationships (for example, with and without short cuts)
2. Focus on "necessary and sufficient" semantics when defining the core entities in a module and leave some things under-specified  
• Don't completely define everything just because it touches your semantics (admittedly, you have to bring all the necessary semantics together to create a complete model or ontology, but more on that in the next post)
• A contrived example is that physical hardware is located somewhere in time and space, but it is unlikely that everyone's requirements for spatial and temporal information will be consistent.  So, relate your Hardware entity to a Location and leave it at that.  Let another module (or set of modules) handle the idiosyncrasies of Location.

In my next post, I promise to talk more about how to combine discrete "modules" with under-specified concepts to create a complete solution.

Andrea

Semantic Technologies and Ontologies Overview Presentation

Last year, I did a short talk on semantic technologies and ontologies, and thought that I would share it. The audience was mostly people who were new to the technologies, and needed to understand their basics and how/where they are used.

[Disclaimer] The presentation is pretty basic ...

But it seemed to work. It overviews key terms (like the "o-word", ontology :-) and standards (based on the ever popular, semantic "layer cake" image). In looking over the deck, I see that I should have talked about RIF (Rule Interchange Format). But, I was using SWRL at the time, and so gravitated to that. (My apologies for not being complete.)

Since the talk was meant to show that semantic technologies are not just an academic exercise, I spent most of the time highlighting how and where the technologies are used. IMHO, I think that the major uses are:

• Semantic search and query expansion
• Mapping and merging of data
• Knowledge management

The last bullet might be a bit ambiguous. For me, it means organizing knowledge (my blog's namesake) and inferring new knowledge (via reasoning and logic).

There are also quite a few examples of real companies using ontologies and semantic technologies. It is kind of amazing when you look at what is being done.

So, take a look and let me know what you think.

And, as a teaser, I want to highlight that I will be presenting at the next Ontology Summit 2014 session on Thursday, January 23rd, on "Reuse of Content from ISO 15926 and FIBO". If you want to listen in, the details for the conference call are here.  Hopefully, you can join in.

Andrea

Ontology Summit 2014 Kicks Off Tomorrow, Jan 16

The topic for this year's Summit is "Big Data and Semantic Web Meet Applied Ontology". The Summit kicks off with a conference call on Thursday, January 16th, at 9:30am PST/12:30pm EST/5:30pm GMT (call details). Here is a short excerpt from the Summit's "Goals and Objectives":

Since the beginnings of the Semantic Web, ontologies have played key roles in the design and deployment of new semantic technologies. Yet over the years, the level of collaboration between the Semantic Web and Applied Ontology communities has been much less than expected. Within Big Data applications, ontologies appear to have had little impact. This year's Ontology Summit is an opportunity for building bridges between the Semantic Web, Linked Data, Big Data, and Applied Ontology communities.

For those of you not familiar with the Summit, it was started in 2006, and there is a different theme each year. It is sponsored by a set of organizations including NIST, Ontolog, NCOR, NCBO, IAOA & NITRD. The way that the Summit works is by a series of conference calls (every Thursday) and lots of email discussion. It is culminated by a face-to-face meeting in late April.

I highly recommend participating, or even just lurking. It is not necessary (or even possible :-) to attend the call every week and to read every email on the ontolog-forum. (Also, it is not mandatory to come to the face-to-face.) If you have to miss something, slides and transcripts of the conference chats, as well as an email archive, are available online. In addition, at the end of the Summit, a "communique" is prepared that summarizes the discussions and work.

I have lurked on the edges of the Summit since the late 2000s, but finally have the time to actively participate. This year, I am co-championing Track A on "Common, Reusable Semantic Content". This topic is near and dear to my heart since I am a strong proponent of reuse. IMHO, it is always valuable (when it is possible) to build on someone else's good work, and benefit from their learnings, rather than starting from scratch. So, when modeling or designing, I look to find something similar and then extrapolate from, or build on it.

Needless to say, I usually don't take other ontologies "en masse", but pick and choose the semantics, patterns or ideas that make sense. How to do this is one aspect of Track A, and there is more. Here are some excerpts from our "Mission" statement:

Semantic technologies such as ontologies and reasoning play a major role in the Semantic Web and are increasingly being applied to help process and understand information expressed in digital formats. Indeed, the derivation of assured knowledge from the connection of diverse (and linked) data is one of the main themes of Big Data ... One challenge in these efforts is to build and leverage common semantic content thus reducing the burden of new ontology creation while avoiding silos of different ontologies. Examples of such content are whole or partial ontologies, ontology modules, ontological patterns and archetypes, and common theories related to ontologies and their fit to the real world ... Achieving commonality and reuse in a timely manner and with manageable resources remain key ingredients for practical development of quality and interoperable ontologies ... This track will discuss the reuse problem and explore possible solutions. Among these are practical issues like the use of ontology repositories and tools, and the possibility of using basic and common semantic content in smaller, more accessible pieces. The goal is to identify exemplary content and also define the related information to enable use/reuse in semantic applications and services. A secondary goal is to highlight where more work is needed and enable the applied ontology community to further develop semantic content and its related information.

I hope that you can join me!

Andrea