Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

February 26, 2012

Where to Publish and Find Ontologies? A Survey of Ontology Libraries

Filed under: Interoperability,Ontology,Semantic Colonialism,Semantic Web — Patrick Durusau @ 8:27 pm

Where to Publish and Find Ontologies? A Survey of Ontology Libraries by Natasha F. Noy and Mathieu d’Aquin.

Abstract:

One of the key promises of the Semantic Web is its potential to enable and facilitate data interoperability. The ability of data providers and application developers to share and reuse ontologies is a critical component of this data interoperability: if different applications and data sources use the same set of well defined terms for describing their domain and data, it will be much easier for them to “talk” to one another. Ontology libraries are the systems that collect ontologies from different sources and facilitate the tasks of finding, exploring, and using these ontologies. Thus ontology libraries can serve as a link in enabling diverse users and applications to discover, evaluate, use, and publish ontologies. In this paper, we provide a survey of the growing—and surprisingly diverse—landscape of ontology libraries. We highlight how the varying scope and intended use of the libraries affects their features, content, and potential exploitation in applications. From reviewing eleven ontology libraries, we identify a core set of questions that ontology practitioners and users should consider in choosing an ontology library for finding ontologies or publishing their own. We also discuss the research challenges that emerge from this survey, for the developers of ontology libraries to address.

Speaking of semantic colonialism, this survey is an accounting of the continuing failure of that program. The examples cited as “ontology libraries” are for the most part not interoperable with each other.

Not that I disagree that having greater data interoperability would be a bad thing, it would be a very good thing, for some issues. The problem, as I see it, is the fixation of the Semantic Web community on a winner-takes-all model of semantics. Could well be, (warning, heresy ahead) that RDF and OWL aren’t the most effective ways to represent or “reason” about data. Just saying, no proof, formal or otherwise to be offered.

And certainly there is a lack of data written using RDF (or even linked data) or annotated using OWL. I don’t think there is a good estimate of all available data so it is difficult to give a good figure for exactly how little of the overall amount of data that is in all the Semantic Web formats.

Any new format will only be applied to the creation of new data so that will leave us with the ever increasing mountains of legacy data which lack the new format.

Rather than seeking to reduce semantic diversity, what appears to be a losing bet, we should explore mechanisms to manage semantic diversity.

February 25, 2012

Ontological Conjunctive Query Answering over large, semi-structured knowledge bases

Filed under: Conjunctive Query,Knowledge,Ontology,Semi-structured Knowledge Bases — Patrick Durusau @ 7:37 pm

Ontological Conjunctive Query Answering over large, semi-structured knowledge bases

From the description:

Ontological Conjunctive Query Answering knows today a renewed interest in knowledge systems that allow for expressive inferences. Most notably in the Semantic Web domain, this problem is known as Ontology-Based Data Access. The problem consists in, given a knowledge base with some factual knowledge (very often a relational database) and universal knowledge (ontology), to check if there is an answer to a conjunctive query in the knowledge base. This problem has been successfully studied in the past, however the emergence of large and semi-structured knowledge bases and the increasing interest on non-relational databases have slightly changed its nature.

This presentation will highlight the following aspects. First, we introduce the problem and the manner we have chosen to address it. We then discuss how the size of the knowledge base impacts our approach. In a second time, we introduce the ALASKA platform, a framework for performing knowledge representation & reasoning operations over heterogeneously stored data. Finally we present preliminary results obtained by comparing efficiency of existing storage systems when storing knowledge bases of different sizes on disk and future implications.

Slides help as always.

Introduces the ALASKA – Abstract Logic-based Architecture Storage systems & Knowledge base Analysis.

Its goal is to enable to perform OCQA in a logical, generic manner, over existing, heterogeneous storage systems.

“ALASKA” is the author’s first acronym.

The results for Oracle software (slide 25) makes me suspect the testing protocol. Not that Oracle wins every contest by any means but such poor performance indicates some issue other its native capabilities.

February 15, 2012

International Conference on Knowledge Engineering and Ontology Development

Filed under: Conferences,Knowledge Management,Ontology — Patrick Durusau @ 8:32 pm

International Conference on Knowledge Engineering and Ontology Development

Regular Paper Submission: April 17, 2012
Authors Notification (regular papers): June 12, 2012
Final Regular Paper Submission and Registration: July 4, 2012

From the call for papers:

Knowledge Engineering (KE) refers to all technical, scientific and social as-pects involved in building, maintaining and using knowledge-based systems. KE is a multidisciplinary field, bringing in concepts and methods from several computer science domains such as artificial intelligence, databases, expert systems, decision support systems and geographic information systems.

Ontology Development (OD) aims at building reusable semantic structures that can be informal vocabularies, catalogs, glossaries as well as more complex finite formal structures representing the entities within a domain and the relationships between those entities. Ontologies, have been gaining interest and acceptance in computational audiences: formal ontologies are a form of software, thus software development methodologies can be adapted to serve ontology development. A wide range of applications is emerging, especially given the current web emphasis, including library science, ontology-enhanced search, e-commerce and business process design.

Part of IC3K 2012 – International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management.

February 11, 2012

Ontology for Media Resources 1.0

Filed under: Media,Ontology — Patrick Durusau @ 7:51 pm

Ontology for Media Resources 1.0 W3C Recommendation 09 February 2012

From the abstract:

This document defines the Ontology for Media Resources 1.0. The term “Ontology” is used in its broadest possible definition: a core vocabulary. The intent of this vocabulary is to bridge the different descriptions of media resources, and provide a core set of descriptive properties. This document defines a core set of metadata properties for media resources, along with their mappings to elements from a set of existing metadata formats. Besides that, the document presents a Semantic Web compatible implementation of the abstract ontology using RDF/OWL. The document is mostly targeted towards media resources available on the Web, as opposed to media resources that are only accessible in local repositories.

Credit where credit is due. It is nice to see that this ontology comes with a mapping to existing metadata formats.

I would not take the last line about “media resources available on the web,” too seriously. There are more media resources off the web than on. If you find this ontology useful, use it.

February 7, 2012

Ignorance & Semantic Uniformity

Filed under: GoodRelations,Ontology,RDF — Patrick Durusau @ 4:34 pm

I saw Volkswagen Vehicles Ontology by Martin Hepp, in a tweet by Bob DuCharme today.

Being a former owner of a 1972 Super Beetle, I checked under

vvo:AudioAndNavigation

Only to find that cassette player wasn’t one of the options:

The class of audio and navigation choices or components (CD/DVD/SatNav, a “MonoSelectGroup” in automotive terminology), VW ID: 1

I searched the ontology for “Beetle” and came up empty.

Is ignorance the path to semantic uniformity?

February 4, 2012

ADMS Public Review is launched

Filed under: ADMS,Ontology,RDF — Patrick Durusau @ 3:40 pm

ADMS Public Review is launched

Public Review ends: 6 February 2012

From the post:

The ISA programme of the European Commission launched the public review of the Asset Description Metadata Schema (ADMS) on 6 January 2012 this will end on 6 February 2012 (inclusive).

From mid 2012, the Joinup platform, of the ISA programme, will make available a large number of semantic interoperability assets, described using ADMS, through a federation of asset repositories of Member States, standardisation bodies and other relevant stakeholders.

Apologies for the late notice but this item just came to my attention.

This is version 0.8 so unless the EC uses Hadoop numbering practices (jumping from 0.22 to 1.0) and such, I suspect there will be additional opportunities to comment.

ADMS 0.8 (has the following files):

At least as of today, 4 February 2012, the following two files don’t require you to answer if you are willing to participate in a post-download survey. I know every marketing department thinks their in-house and amateurish surveys are meaningful. Not. Ask a professional survey group if you really want to do surveys. Expensive but at least they will be meaningful.

These five (5) files require you to register and accept the post-download survey or answer: “No, I prefer to remain anonymous – start the download immediately.” five (5) times.

The ADMS_Specification-v0.8.zip file contains ADMS_Specification-v0.8.pdf (which is listed above).

The specification document is thirty-five (35) pages long so it won’t take you long to read.

I was puzzled by the documentation note (dcterms:abstract) in the adms08.rdf file that reads:

ADMS is intended as a model that facilitates federation and co-operation. It is not the primary intention that repository owners redesign or convert their current systems and data to conform to ADMS, but rather that ADMS can act as a common layer among repositories that want to exchange data.

But the examples found in ADMS_Examples-v0.8.zip are dated variously, 2011 – ADMS_Examples_Digitaliser_v0.03.pdf, 2010 – ADMS_Examples_ADMS_v0.03.pdf, ADMS_Examples_DCMES_v0.03.pdf, 2009 – ADMS_Examples_SKOS_v0.04.pdf, with version numbers, v0.03 and v.0.04 that leave doubt about the examples being current with the specification draft.

Morever, the examples are contrary to the goal of ADMS in that they represent presentation of data in ADMS rather than using ADMS as a target vocabulary. In other words, if you are a target vocabulary, give target vocabulary examples.

Do you have a feeling of deja vu reading these documents? Been here, done that? Which projects would you name off the top of your head that cover some, all or more than the ground covered here? (Extra points if you look up citations/URLs.)

Shameless self-promotion follows if you want to stop reading here.

It doesn’t look like my editing schedule is full for this year. Ghost or public editing of documentation or standards available. ODF 1.2 is an example of what is possible with a dedicated technical team like Sun had at Hamburg backing me as an editor. It is undergoing revision but no standard or document is ever perfect. Anyone who says differently is mis-informed or lying.

Cry Me A River, But First Let’s Agree About What A River Is

Filed under: Ontology,Semantic Diversity,Semantic Web — Patrick Durusau @ 3:34 pm

Cry Me A River, But First Let’s Agree About What A River Is

The post starts off well enough:

How do you define a forest? How about deforestation? It sounds like it would be fairly easy to get agreement on those terms. But beyond the basics – that a definition for the first would reflect that a forest is a place with lots of trees and the second would reflect that it’s a place where there used to be lots of trees – it’s not so simple.

And that has consequences for everything from academic and scientific research to government programs. As explained by Krzysztof Janowicz, perfectly valid definitions for these and other geographic terms exist by the hundreds, in legal texts and government documents and elsewhere, and most of them don’t agree with each other. So, how can one draw good conclusions or make important decisions when the data informing those is all over the map, so to speak.

….

Having enough data isn’t the problem – there’s official data from the government, volunteer data, private organization data, and so on – but if you want to do a SPARQL query of it to discover all towns in the U.S., you’re going to wind up with results that include the places in Utah with populations of less than 5,000, and Los Angeles too – since California legally defines cities and towns as the same thing.

“So this clearly blows up your data, because your analysis is you thinking that you are looking at small rural places,” he says.

This Big Data challenge is not a new problem for the geographic-information sciences community. But it is one that’s getting even more complicated, given the tremendous influx of more and more data from more and more sources: Satellite data, rich data in the form of audio and video, smart sensor network data, volunteer location data from efforts like the Citizen Science Project and services like Facebook Places and Foursquare. “The heterogeneity of data is still increasing. Semantic web tools would help you if you had the ontologies but we don’t have them,” he says. People have been trying to build top-level global ontologies for a couple of decades, but that approach hasn’t yet paid off, he thinks. There needs to be more of a bottom-up take: “The biggest challenge from my perspective is coming up with the rules systems and ontologies from the data.”

All true, many of which objectors to the current Semantic Web approach have been saying for a very long time.

I am not sure about the line: “The heterogeneity of data is still increasing.”

In part because I don’t know of any reliable measure of heterogeneity by which a comparison could be made. True there is more data now than at some X point in the past, but that isn’t necessarily an indication of increased heterogeneity. But that is a minor point.

More serious is the a miracle occurs statement that follows:

How to do it, he thinks, is to make very small and really local ontologies directly mined with the help of data mining or machine learning techniques, and then interlink them and use new kinds of reasoning to see how to reason in the presence of inconsistencies. “That approach is local ontologies that arrive from real application needs,” he says. “So we need ontologies and semantic web reasoning to have neater data that is human and also machine readable. And more effective querying based on analogy or similarity reasoning to find data sets that are relevant to our work and exclude data that may use the same terms but has different ontological assumptions underlying it.”

Doesn’t that have the same feel as the original Semantic Web proposals that were going to eliminate semantic ambiguity from the top down? The very approach that is panned in this article?

And “new kinds of reasoning,” ones I assume have not been invented yet, are going “to reason in the presence of inconsistencies.” And excluding data that “…has different ontological assumptions underlying it.”

Since we are the source of ontological assumptions that underlie the use of terms, I am real curious about how those assumptions are going to become available to these to be invented reasoning techniques?

Oh, that’s right, we are all going to specify our ontological assumptions at the bottom to percolate up. Except that to be useful for machine reasoning, they will have to be as crude as the ones that were going to be imposed from the top down.

I wonder why the indeterminate nature of semantics continues to elude Semantic Web researchers. A snapshot of semantics today may be slightly incorrect tomorrow, probably incorrect in some respect in a month and almost surely incorrect in a year or more.

Take Saddam Hussein for example. One time friend and confidant of Donald Rumsfeld (there are pictures). But over time those semantics changed, largely because Hussein slipped the lease and was no longer a proper vassal to the US. Suddenly, the weapons of mass destruction, in part nerve gas we caused to be sold to him, became a concern. And so Hussein became an enemy of the US. Same person, same facts. Different semantics.

There are less dramatic examples but you get the idea.

We can capture even changing semantics but we need to decide what semantics we want to capture and at what cost? Perhaps that is a better way to frame my objection to most Semantic Web activities, they are not properly scoped. Yes?

January 31, 2012

Multiple Recognitions

Filed under: Logic,Ontology,Semantics — Patrick Durusau @ 4:38 pm

Yesterday in The “L&O” Shortage I asked the question:

“…can something be recognized more than once?”

That may not be an artful way to frame the question. Perhaps better:

When an author uses some means for identification, whatever that may be, can it be recognized differently by different users?

One case that comes to mind in the interpretation of Egyptian Hieroglyphics over time. In addition to the attempts in the 16th and 17th centuries, which are now thought to be completely fantastic, there are the modern “accepted” translations as well as ancient Egyptian texts where it appears the scribe did not understand what was being copied.

If we are going to faithfully record the history of interpretation of such literature, we cannot flatten the “translated” texts to have the meanings we would assign to them today. The references of the then current literature would make no sense if we did.

Google Books is a valuable service but it is also a dangerous one for research purposes. In part because semantic drift occurs in any living language (or the interpretation of dead ones) and the results are reported without any warnings about such shifts.

Did you know, for example, that “cab” at one time was a slang reference to a house of prostitution? Would give new meaning to the statement: “I will call you a cab.” doesn’t it?

Before we can assign semantics to any word, we need to know what is being identified by that word. But knowing that any one word may represent multiple identifications.

Requirement: A system of identification must support the same identifiers resolving to different identifications.

The consequences of deciding otherwise on such a requirement, I will try to take up tomorrow.

January 30, 2012

The “L&O” Shortage

Filed under: Logic,Ontology — Patrick Durusau @ 8:03 pm

Last week I mentioned that we are facing a critical shortage of both logicians and ontologists: Alarum – World Wide Shortage of Logicians and Ontologists.

This is the first of a number of posts on what we can do, facing this tidal wave of data with nary a logician or ontologist in sight.

I have a question that I think we need to answer before we get to the question of semantics.

Is it fair to say that identification comes before semantics? That is we have to recognize something (whatever that may be) before we can talk about its semantics?

I ask because I think it is important to take the requirements for data and its semantics one step at a time. And in particular to not jump ahead of ourselves with half-remembered bits of doggerel from grade school to propose syntactic solutions.

Or to put it differently, let’s make sure of what order steps need to be taken before we trip over our own feet.

That would be the requirements phase, as is well known to the successful programmers and startup folks among the audience.

So, is requirement #1 that something be recognized? Whether that is a file, format, subject of any sort or description. I don’t know but suspect we can’t even use logic on things we have yet to recognize.

Just to give you a hint about tomorrow or perhaps the next day, I have meetings tomorrow, can something be recognized more than once?

This may seem like a slow start but the time will pass more quickly than you think it will. There are a number of “perennial” issues that I will argue can be side-lined, in part because they have no answer other than personal preference.

January 27, 2012

Alarum – World Wide Shortage of Logicians and Ontologists

Filed under: BigData,Linked Data,Logic,Ontology — Patrick Durusau @ 4:32 pm

Did you know there is an alarming shortage of logicians and ontologists around the world? Apparently everywhere, in all countries.

Came as a complete shock/surprise to me.

I was reading ‘Digital Universe’ to Add 1.8 Zettabytes in 2011 by Rich Miller which says:

More than 1.8 zettabytes of information will be created and stored in 2011, according to the latest IDC Digital Universe Study sponsored by EMC. That’s a mind-boggling figure, equivalent to 1.8 trillion gigabytes -enough information to fill 57.5 billion 32GB Apple iPads. It also illustrates the challenge in storing and managing all that data.

But then I remembered the “state of the Semantic Web” report of 31,634,213,770 triples.

I know it is apples and oranges to some degree but compare the figures for data and linked data:

Data 1,800,000,000,000,000,000,000
Triples 31,634,213,770

Not to mention that the semantics of data is constantly evolving. If not business and scientific data, recall that “texting” was unknown little more than a decade ago.

It is clear that we don’t have enough logicians and ontologists (who have yet to agree on a common upper ontology) to keep up with the increasing flow of data. For that matter, the truth is they have been constantly falling behind for centuries. Systems are proposed, cover some data, only to become data that has to be covered by subsequent systems.

Some options to deal with this crisis:

  • Universal Logician/Ontologist Conscription Act – All 18 year olds world wide have to spend 6 years in the LogoOnto Corps. First four years learning the local flavor of linked data and the last two years coding data.
  • Excess data to /dev/null – Pipe all non-Linked data to /dev/null until logicians/ontologists can catch up. Projected to be sometime after 5500, perhaps late 5500’s. (According to Zager and Evans.)
  • ???

There are other options. Propose yours and/or wait for some suggestions here next week!

January 22, 2012

A Description Logic Primer

Filed under: Description Logic,Logic,Ontology — Patrick Durusau @ 7:37 pm

A Description Logic Primer by Markus Krötzsch, Frantisek Simancik and Ian Horrocks.

Abstract:

This paper provides a self-contained first introduction to description logics (DLs). The main concepts and features are explained with examples before syntax and semantics of the DL SROIQ are defined in detail. Additional sections review light-weight DL languages, discuss the relationship to the Web Ontology Language OWL and give pointers to further reading.

It’s an introduction to description logics but it is also a readable introduction to description logics (DLs). And it will give you a good overview of the area.

As the paper points out, DLs are older than their use with web ontology languages but that is the use that you are most likely to encounter.

You won’t find anything new information here but it may be a good refresher.

January 17, 2012

Topic Maps as Jigsaw Puzzles?

Filed under: Cyc,Ontology,SUMO,Topic Maps — Patrick Durusau @ 8:20 pm

I ran across:

How could a data governance framework possibly predict how you will assemble the puzzle pieces? Or how the puzzle pieces will fit together within your unique corporate culture? Or which of the many aspects of data governance will turn out to be the last (or even the first) piece of the puzzle to fall into place in your organization? And, of course, there is truly no last piece of the puzzle, since data governance is an ongoing program because the business world constantly gets jumbled up by change.

So, data governance frameworks are useful, but only if you realize that data governance frameworks are like jigsaw puzzles. (emphasis added)

in A Data Governance Framework Jigsaw Puzzle by Jim Harris.

I rather liked the comparison to a jigsaw puzzle and the argument that the last piece seems magical only because it is the last piece. You could jumble them up and some other piece would be the last piece.

The other part that I liked was the conclusion that “…the business world constantly gets jumbled up by change.”

Might want to read that again: “…the business world constantly gets jumbled up by change.”

I will boldly generalize that to: the world constantly gets jumbled by change.

Well, perhaps not such a bold statement as I think anyone old enough to be reading this blog realizes the world of today isn’t the world it was ten years ago. Or five years ago. Or in many cases one year ago.

I think that may explain some of my unease with ontologies that claim to have captured something fundamental rather than something fit for a particular use.

At one time an ontology based on earth, wind, fire and water would have been sufficient for most purposes. It isn’t necessary to claim more than fitness for use and in so doing, it leaves us the ready option to change should a new use come along. One that isn’t served by the old ontology.

Interchange is one use case and if you want to claim that Cyc or SUMO are appropriate for a particular case of interchange, that is a factual claim that can be evaluated. Or to claim that either one is sufficient for “reasoning” about a particular domain. Again, a factual question subject to evaluation.

But the world that produced both Cyc and SUMO isn’t the world of today. Both remain useful but the times they are a changing. Enough change and both ontologies and topic maps will need to change to suit your present needs.

Ontologies and topic maps are jigsaw puzzles with no final piece.

January 16, 2012

structr – update

Filed under: Graphs,Neo4j,Ontology,structr,Topic Map Software,Topic Maps — Patrick Durusau @ 2:29 pm

structr

One of the real pleasures of going over my older posts is checking up on projects I have mentioned in the past. Particularly when they show significant progress since the last time I looked.

Structr is one of those projects.

A lot of progress and I saw today that the homepage advertises:

With structr, you can build web sites or portals, but also interactive web applications.

And if you like, you can add topic maps or ontologies to the content graph. (emphasis added)

Guess I need to throw a copy on my “big box” and see what happens!

January 3, 2012

Ontologies as Semantically Discrete Data

Filed under: Ontology,Rough Sets,Semantics — Patrick Durusau @ 5:09 pm

The contest associated with the Topical Classification of Biomedical Research Papers conference involves the use of of the domain ontology MeSH. The contest involves the classification of materials using that ontology and clustering the results. (You should read the contest description for the full details. I am only pulling out facts needed for this post, which aren’t many.)

It occurred to me that an ontology consists of a set of values that are semantically discrete. That is any value in an ontology is distinct from all other values in the ontology and there is no “almost X,” or “nearly Y,” in an ontology.

I mention this because we apply ontologies to semantically continuous domains. Such as journal articles that were written without regard to any particular ontology.

Which would also explain why given a common ontology, such as MeSH, we may disagree as to which terms to apply to a particular document. We “see” different aspects in the semantically continuous document that influence our view of what term from the semantically discrete ontology to use. And in many cases we may be in agreement.

But the fact remains that we have applied a semantically discrete instrument to a semantically continuous data set.

I suppose one question is whether rough sets can capture and preserve some semantic continuity for use in information retrieval.

December 21, 2011

Opaque Attribute Alignment

Filed under: Mapping,Ontology — Patrick Durusau @ 7:22 pm

Opaque Attribute Alignment by Jennifer Sleeman, Rafael Alonso, Hua Li, Art Pope, and Antonio Badia.

Abstract:

Ontology alignment describes a process of mapping ontological concepts, classes and attributes between different ontologies providing a way to achieve interoperability. While there has been considerable research in this area, most approaches that rely upon the alignment of attributes use label based string comparisons of property names. The ability to process opaque or non-interpreted attribute names is a necessary component of attribute alignment. We describe a new attribute alignment approach to support ontology alignment that uses the density estimation as a means for determining alignment among objects. Using the combination of similarity hashing, Kernel Density Estimation (KDE) and Cross entropy, we are able to show promising F-Measure scores using the standard Ontology Alignment Evaluation Initiative (OAEI) 2011 benchmark.

Just in case you run across different ontologies covering the same area, however unlikely that seems 10+ years after the appearance of the Semantic Web.

December 13, 2011

Ontology Matching 2011

Filed under: Identification,Identity,Ontology — Patrick Durusau @ 9:54 pm

Ontology Matching 2011

Proceedings of the 6th International Workshop on Ontology Matching (OM-2011)

From the conference website:

Ontology matching is a key interoperability enabler for the Semantic Web, as well as a useful tactic in some classical data integration tasks dealing with the semantic heterogeneity problem. It takes the ontologies as input and determines as output an alignment, that is, a set of correspondences between the semantically related entities of those ontologies. These correspondences can be used for various tasks, such as ontology merging, data translation, query answering or navigation on the web of data. Thus, matching ontologies enables the knowledge and data expressed in the matched ontologies to interoperate.


The workshop has three goals:

  • To bring together leaders from academia, industry and user institutions to assess how academic advances are addressing real-world requirements. The workshop will strive to improve academic awareness of industrial and final user needs, and therefore direct research towards those needs. Simultaneously, the workshop will serve to inform industry and user representatives about existing research efforts that may meet their requirements. The workshop will also investigate how the ontology matching technology is going to evolve.
  • To conduct an extensive and rigorous evaluation of ontology matching approaches through the OAEI (Ontology Alignment Evaluation Initiative) 2011 campaign. The particular focus of this year’s OAEI campaign is on real-world specific matching tasks involving, e.g., open linked data and biomedical ontologies. Therefore, the ontology matching evaluation initiative itself will provide a solid ground for discussion of how well the current approaches are meeting business needs.
  • To examine similarities and differences from database schema matching, which has received decades of attention but is just beginning to transition to mainstream tools.

An excellent set of papers and posters.

While I was writing this post, I realized that had the papers been described as matching subject identifications by similarity measures, I would have felt completely different about the papers.

Isn’t that odd?

Question: Do you agree/disagree that mapping ontologies is different from mapping subject identifications? Why/why not?

UMBEL Services, Part 1: Overview

Filed under: Ontology,Open Semantic Framework,SPARQL — Patrick Durusau @ 9:52 pm

UMBEL Services, Part 1: Overview

From the post:

UMBEL, the Upper Mapping and Binding Exchange Layer, is an upper ontology of about 28,000 reference concepts and a vocabulary designed for domain ontologies and ontology mapping [1]. When we first released UMBEL in mid-2008 it was accompanied by a number of Web services and a SPARQL endpoint, and general APIs. In fact, these were the first Web services developed for release by Structured Dynamics. They were the prototypes for what later became the structWSF Web services framework, which incorporated many lessons learned and better practices.

By the time that the structWSF framework had evolved with many additions to comprise the Open Semantic Framework (OSF), those original UMBEL Web services had become quite dated. Thus, upon the last major update to UMBEL to version 1.0 back in February of this year, we removed these dated services.

Like what I earlier mentioned about the cobbler’s children being the last to get new shoes, it has taken us a bit to upgrade the UMBEL services. However, I am pleased to announce we have now completed the transition of UMBEL’s earlier services to use the OSF framework, and specifically the structWSF platform-independent services. As a result, there are both upgraded existing services and some exciting new ones. We will now be using UMBEL as one of our showcases for these expanding OSF features. We will be elaborating upon these features throughout this series, some parts of which will appear on Fred Giasson’s blog.

In this first part, we provide a broad overview of the new UMBEL OSF implementation. We also begin to foretell some of the parts to come that will describe some of these features in more detail.

There are three more parts that follow this one.

If you have the time, I am interested in your take on this resource.

A lot of time and effort has gone into making this a useful site, so what parts do you like best/least? What would you change?

More to follow on this one.

December 5, 2011

Sharing and Integrating Ontologies

Filed under: Logic,Ontology — Patrick Durusau @ 7:44 pm

Sharing and Integrating Ontologies

Peter Yim, organizer and promoter of all things ontological, reminded me of this effort quite recently.

If you were constrained by:

The semantics defined by ISO/IEC 24707 for Common Logic should be the basis for the logics used to define ontologies.

could you still write a topic map?

My suggestion would be yes, since a topic map is “without form and void” prior to being filled in by an author.

True, prior to doing that “filling in,” you will have selected a form to fill in, that is a data model (we call them legends) so your topic map already has some rules and topics in place before you start.

But, the fact remains you could write a topic map using the semantics of ISO/IEC 24707 and identify those semantics so that ontologies could be mapped to them.

December 3, 2011

AO: Annotation Ontology

Filed under: Annotation,Ontology — Patrick Durusau @ 8:22 pm

AO: Annotation Ontology

From the description:

The Annotation Ontology is a vocabulary for performing several types of annotation – comment, entities annotation (or semantic tags), textual annotation (classic tags), notes, examples, erratum… – on any kind of electronic document (text, images, audio, tables…) and document parts. AO is not providing any domain ontology but it is fostering the reuse of the existing ones for not breaking the principle of scalability of the Semantic Web.

Anita de Waard mentioned this in her How to Execute the Research Paper.

Interesting work but you have to realize that all ontologies evolve (except for those that aren’t used) and that not everyone uses the same one.

Still, it is the sort of thing you will encounter in topic maps work so you need to be aware of it.

November 23, 2011

SUMMER SCHOOL ON ONTOLOGY ENGINEERING AND THE SEMANTIC WEB

Filed under: Ontology,Semantic Web — Patrick Durusau @ 5:39 pm

9TH SUMMER SCHOOL ON ONTOLOGY ENGINEERING AND THE SEMANTIC WEB (SSSW 2012), 8-14 July, 2012, Cercedilla, near Madrid, Spain.

Applications open: 30 January 2012, close: 31 March 2012

from the webpage:

The groundbreaking SSSW series of summer schools started in 2003. It is now a well-establish event within the research community and a role model for several other initiatives. Presented by leading researchers in the field, it represents an opportunity for both students and practitioners to equip themselves with the range of theoretical, practical, and collaboration skills necessary for full engagement with the challenges involved in developing Ontologies and Semantic Web applications. To ensure a high ratio between tutors and students the school will be limited to 50 participants. Applications for the summer school will open on the 30th January 2012 and will close by the 31st March 2012.

From the very beginning the school pioneered an innovative pedagogical approach, combining the practical with the theoretical, and adding teamwork and a competitive element to the mix. Specifically, tutorial/lecture material is augmented with hands-on practical workshops and we ensure that the sessions complement each other by linking them to a group project. Work on developing and presenting a project in cooperation with other participants serves as a means of consolidating the knowledge and skills gained from lectures and practical sessions. It also introduces an element of competition among teams, as prizes are awarded to the best projects at the end of the week. Participants will be provided with electronic versions of all course lectures and all necessary tools and environments for the hands-on sessions. PC access with all tools pre-installed will be available on site as well. SSSW 2011 will provide a stimulating and enjoyable environment in which participants will benefit not only from the formal and practical sessions but also from informal and social interactions with established researchers and the other participants to the school. To further facilitate communication and feedback all attendees will present a poster on their research.

It may just be me but I never cared for conferences/meetings that were “near” major locations. Academic and professional meetings should be held at or near large international airports. People who want vacation junkets should become politicians.

November 17, 2011

Modular Unified Tagging Ontology (MUTO)

Filed under: Ontology,Tagging,Taxonomy — Patrick Durusau @ 8:38 pm

Modular Unified Tagging Ontology (MUTO)

From the webpage:

The Modular Unified Tagging Ontology (MUTO) is an ontology for tagging and folksonomies. It is based on a thorough review of earlier tagging ontologies and unifies core concepts in one consistent schema. It supports different forms of tagging, such as common, semantic, group, private, and automatic tagging, and is easily extensible.

I though the tagging axioms were worth repeating:

  • A tag has always exactly one label – otherwise it is not a tag.

    (Additional labels can be separately defined, e.g. via skos:Concept.)
  • Tags with the same label are not necessarily semantically identical.

    (Each tag has its own identity and property values.)
  • A tag can itself be a resource of tagging (tagging of tags).

From the properties defined, however, it isn’t clear how to determine when tags do have the same meaning and/or how to communicate that understanding to others?

Ah, or would that be a tagging of a tagging?

That sounds like it leaves a lot of semantic detail on the cutting room floor but it may be that viable semantic systems, oh, say natural languages, do exactly that. Something to think about isn’t it?

October 28, 2011

Context and Semantics for Knowledge Management – … Personal Productivity [and Job Security]

Filed under: Context,Knowledge Management,Ontology,Semantic Web,Semantics — Patrick Durusau @ 3:13 pm

Context and Semantics for Knowledge Management – Technologies for Personal Productivity by Warren, Paul; Davies, John; Simperl, Elena (Eds.). 1st Edition., 2011, X, 392 p. 120 illus., 4 in color. Hardcover, ISBN 978-3-642-19509-9

I quite agree with the statement: “the fact that much corporate knowledge only resides in employees’ heads seriously hampers reuse.” True but it is also a source of job security. In organizations both large and small, in the U.S. and in other countries as well.

I don’t think any serious person believes the Pentagon (US) needs to have more than 6,000 HR systems. But, job security presents different requirements from say productivity, accomplishment of mission (aside from the mission of remaining employed), in this case, national defense, etc.

How one overcomes job security is going to vary from system to system. Be aware it is a non-technical issue and technology is not the answer to it. It is a management issue that management would like to treat as a technology problem. Treating personnel issues as problems that can be solved with technology nearly universally fails.

From the announcement:

Knowledge and information are among the biggest assets of enterprises and organizations. However, efficiently managing, maintaining, accessing, and reusing this intangible treasure is difficult. Information overload makes it difficult to focus on the information that really matters; the fact that much corporate knowledge only resides in employees’ heads seriously hampers reuse.

The work described in this book is motivated by the need to increase the productivity of knowledge work. Based on results from the EU-funded ACTIVE project and complemented by recent related results from other researchers, the application of three approaches is presented: the synergy of Web 2.0 and semantic technology; context-based information delivery; and the use of technology to support informal user processes. The contributions are organized in five parts. Part I comprises a general introduction and a description of the opportunities and challenges faced by organizations in exploiting Web 2.0 capabilities. Part II looks at the technologies, and also some methodologies, developed in ACTIVE. Part III describes how these technologies have been evaluated in three case studies within the project. Part IV starts with a chapter describing the principal market trends for knowledge management solutions, and then includes a number of chapters describing work complementary to ACTIVE. Finally, Part V draws conclusions and indicates further areas for research.

Overall, this book mainly aims at researchers in academia and industry looking for a state-of-the-art overview of the use of semantic and Web 2.0 technologies for knowledge management and personal productivity. Practitioners in industry will also benefit, in particular from the case studies which highlight cutting-edge applications in these fields.

October 24, 2011

ONKI

Filed under: Ontology — Patrick Durusau @ 6:45 pm

ONKI (Finnish Ontology Library Service)

From the website:

The ONKI service contains Finnish and international ontologies, vocabularies and thesauri needed for publishing your content cost-efficiently on the Semantic Web. Ontologies are conceptual models identifying the concepts of a domain. They contain machine “understandable” descriptions of the relations between the concepts.

ONKI is published and maintained by Semantic Computing Research Group SeCo. It is part of the on-going project to build a national semantic web infrastructure to Finland (FinnONTO).

Collection of ontologies/vocabularies, some of which will be familiar, others, perhaps less so.

Searchable ontologies/vocabularies and in many cases, downloadable.

The Finnish Collaborative Holistic Ontology (KOKO)

Filed under: Ontology — Patrick Durusau @ 6:44 pm

The Finnish Collaborative Holistic Ontology (KOKO)

From the website:

The Finnish Collaborative Holistic Ontology is the general, aggregated ontology of the National ontology service ONKI. KOKO ontology has the General Finnish Ontology YSO as its top ontology and a variety of other domain specific ontologies extending its concepts into more detailed subconcept hierarchies. KOKO’s domain specific ontologies include initially MAO (cultural heritage), AFO (agriforestry), TAO (applied arts), VALO (photography), and other ontologies are being added to KOKO by ontology matching.

The idea of KOKO and the National Finnish ontology infrastructure is described in English and in Finnish in the articles and reports below.

The KOKO ontology is created as a part of the FinnONTO project.

If you are looking for upper ontologies, this is one.

I ran across this while looking up references in: MUTU: An Analysis Tool….

MUTU: An Analysis Tool…

Filed under: Mapping,Ontology — Patrick Durusau @ 6:44 pm

MUTU: An Analysis Tool for Maintaining a System of Hierarchically Linked Ontologies (pdf)

Abstract

We consider ontology evolution in a system of light-weight Linked Data ontologies, aligned with each other to form a larger ontology system. When one ontology changes, the human editor must keep track of the actual changes and of the modifications needed in the related ontologies in order to keep the system consistent. This paper presents an analysis tool MUTU, by which such changes and their potential effects on other ontologies can be found. Such an analysis is useful for the ontology editors for understanding the differences between ontology versions, and for updating linked ontologies when changes occurred in other components of an ontology system.

Not available on the web, yet, but sounds interesting.

October 22, 2011

Edelweiss

Filed under: Interface Research/Design,Ontology,Semantic Web — Patrick Durusau @ 3:17 pm

Edelweiss

From the website:

The research team Edelweiss aims at offering models, methods and techniques for supporting knowledge management and collaboration in virtual communities interacting with information resources through the Web. This research will result in an ergonomic graph-based and ontology-based platform.

This research will result in an ergonomic graph-based and ontology-based platform. Activity Report 2010
Located at INRIA Sophia Antipolis-Méditerranée, Edelweiss was previously known as Acacia.
Edelweiss stands for…

  • Exchanges : communication, diffusion, knowledge capitalization, reuse, learning.
  • Documents : texts, multimedia, XML.
  • Extraction : semi-automated information extraction from documents.
  • Languages : graphs, semantic web languages, logics.
  • Webs : architectures, diffusion, implementation.
  • Ergonomics : user interfaces, scenarios.
  • Interactions : interaction design, protocols, collaboration.
  • Semantics : ontologies, semantic annotations, formalisms, reasoning.
  • Servers : distributed services, distributed data, applications.

Good lists of projects, software, literature, etc.

Anyone care to share any longer acronyms in actual use at projects?

October 17, 2011

Networked Knowledge Organization Systems/Services NKOS

Filed under: Knowledge Organization,Library,Ontology,Terminology,Thesaurus,Vocabularies — Patrick Durusau @ 6:40 pm

Networked Knowledge Organization Systems/Services NKOS

From the website:

NKOS is devoted to the discussion of the functional and data model for enabling knowledge organization systems/services (KOS), such as classification systems, thesauri, gazetteers, and ontologies, as networked interactive information services to support the description and retrieval of diverse information resources through the Internet.

Knowledge Organization Systems/Services (KOS) model the underlying semantic structure of a domain. Embodied as Web-based services, they can facilitate resource discovery and retrieval. They act as semantic road maps and make possible a common orientation by indexers and future users (whether human or machine). — Douglas Tudhope, Traugott Koch, New Applications of Knowledge Organization Systems

A wide variety of resources that will interest anyone working with knowledge systems. I would expect any number of these to appear in future posts with comments or observations.

TaxoBank

Filed under: Ontology,Taxonomy,Thesaurus,Vocabularies — Patrick Durusau @ 6:39 pm

TaxoBank: Access, deposit, save, share, and discuss taxonomy resources

From the webpage:

Welcome to the TaxoBank Terminology Registry

The TaxoBank contains information about controlled vocabularies of all types and complexities. We invite you to both browse and contribute. Enjoy term lists for special purpose use, get ideas for building your own vocabulary, perhaps find one that can give you a quicker start.

The information collected about each vocabulary follows a study (TRSS) conducted by JISC, the Joint Information Systems Committee of the Higher and Further Education Funding Councils. All of the recommended fields included in the study’s final report are included; some of those the study identified as Optional are not. See more about the Terminology Registry Scoping Study (TRSS) at their site. In addition, input from other information experts was elicited in planning the site.

This is an interactive web site. To add information about a vocabulary, click on Create Content in the left navigation pane (you’ll need to register as a user first; we just need your name and email). There are only eight required fields, but your listing will be more useful if you complete all the applicable fields about your vocabulary.

Add a comment to almost any page – how you’ve used the vocabulary, what you’d add to it, how you’d use it if expanded to an ontology, etc. Comments are welcome on Event and Blog pages as well. Click on Add Comment, and enter your thoughts. Even anonymous visitors (not signed in) can add comments, but they’ll be reviewed by a site admin before they’re made visible.

You may also update the Events section of the site. Taxonomy, Knowledge Systems, Information Architecture or Management, Metadata are all appropriate event themes. Click on Create Content and then on Events to add a new one (you’ll need to be a registered user).

Contact us through the Contact page, with suggestions, corrections, or to discuss displaying your vocabulary on this site (particularly important if it was created on a college server and faces erasure at the end of the academic year), or if you have questions.

Thank you for visiting (and participating)!

The “Vocabulary spotlight” suggested “Thesaurus of BellyDancing” on my first visit.

To be honest, I had never thought about belly dancing having a thesaurus or even a standard vocabulary for its description.

For class: Browse the listing and pick out an entry for a subject area unfamiliar to you. Prepare a short, say less than 5 minute oral review of the entry. What did you like/dislike, find useful, less than useful, etc. Did any thing about the entry interest you in finding out more about the subject matter or its treatment?

October 15, 2011

Making Sense of Unstructured Data in Medicine Using Ontologies – October 19th

Filed under: Bioinformatics,Biomedical,Ontology — Patrick Durusau @ 4:30 pm

From the email announcement:

The next NCBO Webinar will be presented by Dr. Nigam Shah from Stanford University on “Making Sense of Unstructured Data in Medicine Using Ontologies” at 10:00am PT, Wednesday, October 19. Below is information on how to join the online meeting via WebEx and accompanying teleconference. For the full schedule of the NCBO Webinar presentations see: http://www.bioontology.org/webinar-series.

ABSTRACT:

Changes in biomedical science, public policy, information technology, and electronic heath record (EHR) adoption have converged recently to enable a transformation in the delivery, efficiency, and effectiveness of health care. While analyzing structured electronic records have proven useful in many different contexts, the true richness and complexity of health records—roughly 80 percent—lies within the clinical notes, which are free-text reports written by doctors and nurses in their daily practice. We have developed a scalable annotation and analysis workflow that uses public biomedical ontologies and is based on the term recognition tools developed by the National Center for Biomedical Ontology (NCBO). This talk will discuss the applications of this workflow to 9.5 million clinical documents—from the electronic health records of approximately one million adult patients from the STRIDE Clinical Data Warehouse—to identify statistically significant patterns of drug use and to conduct drug safety surveillance. For the patterns of drug use, we validate the usage patterns learned from the data against FDA-approved indications as well as external sources of known off-label use such as Medi-Span. For drug safety surveillance, we show that drug–disease co-occurrences and the temporal ordering of drugs and disease mentions in clinical notes can be examined for statistical enrichment and used to detect potential adverse events.

WEBEX DETAILS:
——————————————————-
To join the online meeting (Now from mobile devices!)
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1. Go to https://stanford.webex.com/stanford/j.php?ED=108527772&UID=0&PW=NZDdmNWNjOGMw&RT=MiM0
2. If requested, enter your name and email address.
3. If a password is required, enter the meeting password: ncbo
4. Click “Join”.

——————————————————-
To join the audio conference only
——————————————————-
To receive a call back, provide your phone number when you join the meeting, or call the number below and enter the access code.
Call-in toll number (US/Canada): 1-650-429-3300
Global call-in numbers: https://stanford.webex.com/stanford/globalcallin.php?serviceType=MC&ED=108527772&tollFree=0

Access code:929 613 752

October 5, 2011

Catalog QUDT

Filed under: Measurement,Ontology,Semantic Web — Patrick Durusau @ 6:54 pm

Catalog QUDT

From the website:

The QUDT, or ‘Quantity, Unit, Dimension and Type’ collection of ontologies define base classes, properties, and instances for modeling physical quantities, units of measure, and their dimensions in various measurement systems. The goal of the QUDT collection of models is to provide a machine-processable approach for specifying measurable quantities, units for measuring different kinds of quantities, the numerical values of quantities in different units of measure and the data structures and data types used to store and manipulate these objects in software. A simple treatment of units is separated from a full dimensional treatment of units. Vocabulary graphs will be used to organize units for different disciplines.

Useful in a number of domains. Comparison to other measurement ontology efforts should prove to be interesting.

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