Posted:November 15, 2010

UMBEL Vocabulary and Reference Concept OntologySignificant Upgrades, Changes Based on Two Years of Use

Structured Dynamics and Ontotext are pleased to announce the latest release of UMBEL, version 0.80. It has been more than a year since the last update of UMBEL, and well past earlier announced targets for this upgrade. UMBEL was first publicly released as version 0.70 on July 16, 2008.

UMBEL (Upper Mapping and Binding Exchange Layer) has two roles. It is firstly a vocabulary for building reference ontologies to guide the interoperation of domain information. It is secondly a reference ontology in its own right that contains about 21,000 general reference concepts. With more than two years of practical experience with UMBEL, much has been learned.

This learning has now been reflected into five major changes for the system, embodying numerous minor changes. I summarize these major changes below. The formal release of UMBEL v. 0.80 is also being accompanied by a complete revamping and updating of the project’s Web site. I hope you will find these changes as compelling and exciting as we do.

In the broader context, it is probably best to view this release as but the interim first step of a two-step release sequence leading to UMBEL version 1.00. We are on track to release version 1.00 by the end of this year. This second step will include a complete mapping to the PROTON upper-level ontology and the re-organization and categorization of Wikipedia content into the UMBEL structure. We anticipate the pragmatic challenges in this massive effort will also inform some further refinements to UMBEL itself, which will also lead to further changes in its specification.

Nonetheless, UMBEL v. 0.80 does embody most of the language and structural changes anticipated over this evolution. It is fully ready for use and evaluation; it will, for example, be incorporated into a next version of FactForge. But, do be aware that the major revisions discussed herein are subject to further refinements as the efforts leading to version 1.00 are culminated over the next few weeks.

Let’s now overview these major changes in UMBEL v. 0.80.

Major Change #1: Clarification of Dual Role

The genesis of UMBEL more than three years ago was the recognition that data interoperability on the semantic Web depended on shared reference concepts to link related content. We spent much effort to construct such a reference structure with about 21,000 concepts. That purpose remains.

But, the way in which we created this structure — its vocabulary — has also proven to have value in its own right. The same basic way that we constructed the original UMBEL we have now applied to multiple, specific domain ontologies. With use, it has become clear that the vocabulary for creating reference ontologies is on an equal footing to the reference concepts themselves.

With this understanding has come clarity of role and description of UMBEL. With version 0.80, we now have explicitly split and defined these roles and files.

The UMBEL Vocabulary

Thus, UMBEL’s first purpose is to provide a general vocabulary (the UMBEL Vocabulary) of classes and predicates for describing domain ontologies, with the specific aim of promoting interoperability with external datasets and domains. It is usable exclusive of the UMBEL Reference Concept Ontology.

The UMBEL Vocabulary recognizes that different sources of information have different contexts and different structures. A meaningful vocabulary is necessary that can express potential relationships between two information sources with respect to their differences in structure and scope. By nature, these connections are not always exact. Means for expressing the “approximateness” of relationships are essential.

The vocabulary has been greatly simplified from earlier versions (see Major Change #2 below); it now defines two classes:

  • RefConcept
  • SuperType

These are explained further below. And, the vocabulary has 10 properties:

  • isAbout
  • isRelatedTo
  • isLike
  • hasMapping
  • hasCharacteristic
  • isCharacteristicOf
  • preflabel
  • altLabel
  • hiddenLabel
  • definition.

(Note, the latter four are also in SKOS; see [1].)

In addition, UMBEL re-uses certain properties from external vocabularies. These classes and properties are used to instantiate the UMBEL Reference Concept ontology (see next), and to link Reference Concepts to external ontology classes. For more detail on the vocabulary see Part I: Vocabulary Specification in the specifications.

The UMBEL Reference Concept Ontology

The second purpose of UMBEL is to provide a coherent framework of broad subjects and topics, the “reference concepts” or RefConcepts, expressed as the UMBEL Reference Concept Ontology. The RefConcepts act as binding nodes for mapping relevant Web-accessible content, also with the specific aim of promoting interoperability and to reason over a coherent reference structure and its linked resources. UMBEL presently has about 21,000 of these reference concepts drawn from the Cyc knowledge base, which are organized into more than 30 mostly disjoint SuperTypes (see Major Change #3).

The UMBEL Reference Concept Ontology is, in essence, a content graph of subject nodes related to one another via broader-than and narrower-than relations. In turn, these internal UMBEL RefConcepts may be related to external classes and individuals (instances and named entities) via a set of relational, equivalent, or alignment predicates (the UMBEL Vocabulary, see above).

The actual RefConcepts used are the least changed part in UMBEL from previous versions, and still have the same identifiers as prior versions. The Reference Concept Ontology now uses a recently updated release of the OpenCyc KB v3. Cycorp also added some additional mapping predicates in this release that allows items such as fields of study to be added to the structure. (Thanks, Cycorp!)

Here is a large-graph view of the 21,000 reference concepts in the ontology (click to expand; large file):

UMBEL Reference Concept Ontology

More detail on the RefConcepts is provided in Part II: Reference Concepts Specification of the full specifications.

Major Change #2: Reference Concepts and Predicate Simplification

Another set of major changes was the simplification and streamlining of the predicates and construction of the UMBEL Vocabulary [2]. Again, the specifications detail these changes, but the significant ones include:

Natural World Natural Phenomena
Natural Substances
Earthscape
Extraterrestrial
Living Things Prokaryotes
Protists & Fungus
Plants
Animals
Diseases
Person Types
Human Activities Organizations
Finance & Economy
Society
Activities
Time-related Events
Time
Human Works Products
Food or Drink
Drugs
Facilities
Human Places Geopolitical
Workplaces, etc.
Information Chemistry (n.o.c)
Audio Info
Visual Info
Written Info
Structured Info
Notations & References
Numbers
Descriptive Attributes
Classificatory Abstract-level
Topics/Categories
Markets & Industries
Dimensions and SuperTypes
  • Changed the name of ‘Subject Concepts’ (SubjectConcept, or SC) to ‘Reference Concepts’ (RefConcept, or RC). The umbel:SubjectConcept class got deprecated, and the umbel:RefConcept class got added. As noted by many practitioners, the rather tortured use of the earlier “subject concepts” was questioned. The change in this new version reflects the actual reference use of the concepts and ontologies that employ them
  • Dropped the “SemSet” class, and replaced the same idea of providing multiple tagging options via the best practice of the use of umbel:preLabel and multiple umbel:altLabels and umbel:hiddenLabels. This simplifies the language and brings usage into conformance with standard practice and reasoners
  • With the addition of SuperTypes (see next Major Change), dropped the distinction for “abstract concepts” and rolled their earlier use into the standard RefConcepts
  • The simplification due to OWL 2 metamodeling (see Major Change #4) enabled the removal of many earlier predicates and their inverse properties,
  • With experience gained through linking datasets and their attributes to ontologies [3], added predicates (hasCharacteristic and isCharacteristicOf) for relating external properties, and
  • Many other streamlining changes and improvements to property specifications.

See further the Part II in the full specifications.

Major Change #3: SuperTypes

Shortly after the first public release of UMBEL, it was apparent that the 21,000 reference concepts tended to “cluster” into some natural groupings. Further, upon closer investigation, it was also apparent that most of these concepts were disjoint with one another. As subsequent analysis showed, more fully detailed in the Annex G document, fully 75% of the reference concepts in the UMBEL ontology are disjoint with one another.

Natural clusters provide a tractable way to access and manage some 21,000 items. And, large degrees of disjointedness between concepts also can lead to reasoning benefits and faster processing and selection of those items.

For these reasons a dedicated analysis to analyze and assign all UMBEL reference concepts to a new class of SuperTypes was undertaken. SuperTypes are now a major enhancement to UMBEL v. 0.80. The assignment results and the SuperType specification are discussed in Part II, with full analysis results in Annex G.

In addition, all of these SuperTypes are clustered into nine “dimensions”, which are useful for aggregation and organizational purposes, but which have no direct bearing on logic assertions or disjointedness testing. These nine dimensions, with their associated SuperTypes, are shown in the table to the right. Note the last two dimensions (and four SuperTypes), shown in italics, are by definition non-disjoint.

The construct of the SuperType may be applied to any domain ontology constructed with the UMBEL Vocabulary. The UMBEL Reference Concept Ontology includes all disjoint assertions for all of its RefConcepts.

Major Change #4: OWL 2 Compliance

One of the most challenging improvements in the new UMBEL version 0.80 was to make its vocabulary and ontology compliant with the new OWL 2 Web Ontology Language. We wanted to convert to OWL 2 in order to:

  • Use OWL reasoners
  • Load the full UMBEL into the Protégé 4 ontology editor
  • Use the OWL API, consistent with many other ontology tools we are pursuing, and
  • Take advantage of a neat trick in OWL 2 called “punning“.

The latter reason is the most important given the reference role of UMBEL and ontologies based on the UMBEL Vocabulary. It is not unusual to want to treat things either as a class or an instance in an ontology. Among other aspects, this is known as metamodeling and it can be accomplished in a number of ways. “Punning” is one metamodeling technique that importantly allows us to use concepts in ontologies as either classes or instances, depending on context.

To better understand why we should metamodel, let’s look at a couple of examples, both of which combine organizing categories of things and then describing or characterizing those things. This dual need is common to most domains [4].

As one example, let’s take a categorization of apes as a kind of mammal, which is then a kind of animal. In these cases, ape is a class, which relates to other classes, and apes may also have members, be they particular kinds of apes or individual apes. Yet, at the same time, we want to assert some characteristics of apes, such as being hairy, two legs and two arms, no tails, capable of walking bipedally, with grasping hands, and with some being endangered species. These characteristics apply to the notion of apes as an instance.

As another example we may have the category of trucks, which may further be split into truck types, brands of trucks, type of engine, and so forth. Yet, again, we may want to characterize that a truck is designed primarily for the transport of cargo (as opposed to automobiles for people transport), or that trucks may have different drivers license requirements or different license fees than autos. These descriptive properties refer to trucks as an instance.

These mixed cases combine both the organization of concepts in relation to one another and with respect to their set members, with the description and characterization of these concepts as things unto themselves. This is a natural and common way to express most any domain of interest. It is also a general requirement for a reference ontology, as we use in the sense of UMBEL.

When we combine this “punning” aspect of OWL 2 with our standard way of relating concepts in a hierarchical manner, this general view of the predicates within UMBEL emerges (click to expand):

UMBEL Predicates - click to expand

On the left-hand side (quadrants A and C) is the “class” view of the structure; the right-hand side is the “individual” (or instance) view of the structure (quadrants B and D). These two views represent alternative perspectives for looking at the UMBEL reference concepts based on metamodeling.

The top side of the diagram (quadrants A and B) is an internal view of UMBEL reference concepts (RefConcept) and their predicates (properties). This internal view applies to the UMBEL Reference Concept Ontology or to domain ontologies based on the UMBEL Vocabulary. These relationships show how RefConcepts are clustered into SuperTypes or how hierarchical relationships are established between Reference Concepts (via the skos:narrowerTransitive and skos:broaderTransitive relations). The concept relationships and their structure is a “class” view (quadrant A); treating these concepts as instances in their own right and relating them to SKOS is provided by the right-hand “individual” (instance) view (quadrant B).

The bottom of the diagram (quadrants C and D) shows either classes or individuals in external ontologies. The key mapping predicates cross this boundary (the broad dotted line) between UMBEL-based ontologies and external ontologies. See further Part I in the full specification for more detailed discussed of this figure and its relation to metamodelling.

Major Change #5: Documentation and Packaging

These changes also warranted better documentation and a better project Web site. From a documentation standpoint, the organization was simplified between the actual specifications and related annexes. Also, because of a more collaborative basis resulting from the new partnership with Ontotext, we also established an internal wiki following TechWiki designs. Initial authoring occurs there, with final results re-purposed and published on the project Web site.

The UMBEL Web site also underwent a major upgrade. It is now based on Drupal, and therefore will be able to embrace our conStruct advances in visualization and access over time. We also posted the full Reference Concept Ontology as an OWLDoc portal.

We feel these changes have now resulted in a clean and easy-to-maintain framework for the next phase in UMBEL’s growth and maturation.

Next Steps and Version

As noted in the intro, this version is but an interim step to the pending next release of UMBEL v. 1.00. This next version will provide mappings to leading ontologies and knowledge bases, as well as the upgrade of existing Web services and other language support features. Intended production or commercial uses would best await this next version.

However, the current version 0.80 is fully consistent and OWL 2-compliant. It loads and can be reasoned over with OWL 2 reasoners (see those available with Protégé 4.1, for example). We encourage you to download, test and comment upon this version. Specifics are:

As co-editors, Frédérick Giasson and I are extremely enthused about the changes and cleanliness of version 0.80. It is already helping our client work. We think these improvements are a good harbinger for UMBEL version 1.00 to come by the end of the year. We hope you agree.


[1] Some relevant SKOS properties are now shown in the UMBEL namespace. This is a technical issue with regard to SKOS needing to have a separate namespace for its DL version, which has been brought up with the relevant Work Group individuals at the W3C. As soon as this oversight is rectified, the SKOS predicates now in UMBEL will be deprecated in favor of the appropriate ones in SKOS.
[2] We’d especially like to thank Jack Park for a series of critical email exchanges in November 2008 regarding terminology and purpose. We are, of course, solely responsible for the changes we did invoke.
[3] See, for example, the MyPeg.ca site, with its richness of indicator and demographic data. UMBEL co-editors Bergman and Giasson have each blogged about this site.
[4] Much of this material is drawn from M.K. Bergman, “Metamodeling in Domain Ontologies,” AI3:::Adaptive Information blog, Sept 20, 2010; see https://www.mkbergman.com/913/metamodeling-in-domain-ontologies/. In the reference ontologies that are the focus here, we often want to treat our concepts as both classes and instances of a class. This is known as “metamodeling” or “metaclassing” and is enabled by “punning” in OWL 2. For example, here a case cited on the OWL 2 wiki entry on “punning“:
People sometimes want to have metaclasses. Imagine you want to model information about the animal kingdom. Hence, you introduce a class a:Eagle, and then you introduce instances of a:Eagle such as a:Harry.
(1) a:Eagle rdf:type owl:Class
(2) a:Harry rdf:type a:Eagle
Assume now that you want to say that “eagles are an endangered species”. You could do this by treating a:Eagle as an instance of a metaconcept a:Species, and then stating additionally that a:Eagle is an instance of a:EndangeredSpecies. Hence, you would like to say this:
(3) a:Eagle rdf:type a:Species
(4) a:Eagle rdf:type a:EndangeredSpecies.
This example comes from Boris Motik, 2005. “On the Properties of Metamodeling in OWL,” paper presented at ISWC 2005, Galway, Ireland, 2005. For some other examples, see Bernd Neumayr and Michael Schrefl, 2009. “Multi-Level Conceptual Modeling and OWL (Draft, 2 May – Including Full Example)”; see http://www.dke.jku.at/m-owl/most09_22_full.pdf.

Posted by AI3's author, Mike Bergman Posted on November 15, 2010 at 1:54 am in Ontologies, Semantic Web, Structured Dynamics, UMBEL | Comments (3)
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Posted:November 8, 2010

Innovative Winnipeg Project Powered by SD TechnologyPeg Project

This past Friday the Peg project was unveiled for the first time to an enthusiastic welcome at the Winnipeg Poverty Reduction Partnership Forum. A beta version of its website (www.mypeg.ca) was also launched. Peg is an innovative Web portal for community indicators of well-being for the city of Winnipeg, Manitoba. First conceived in 2002, with much subsequent refinement, its strong consortium of members from the local community and recent backing have now allowed it to be shared with the public.

Since early this year, Structured Dynamics has been the lead technical contractor on the project. But Peg is about people and involvement, not technology. Peg is an effort of community and perspectives and information and stories, all designed to coalesce how to make Winnipeg a better community moving forward. So, while the technology underlying the site is innovative (yes, we’re proud 😉 ), more so is the effort and vision of the community making it happen. Though just a beta release, the current site and the commitment behind it points to some exciting future developments.

Here is the main screen for Peg (clicking on any of the screen captures below will take you directly to the relevant part of the site):

Peg Main Page

A Community Perspective Backed by Dynamic Functionality

Winnipeg’s community indicator system (CIS) is organized around themes, cross-cutting issues that bridge across themes, and indicators and supporting data to track and measure the city’s well-being. Peg’s major themes, agreed upon after extensive community consultation, are: basic needs; health; education & learning; social vitality; governance; built environment; economy; and natural environment. In this first beta release, the emphasis has been on the cross-cutting issue of poverty and some of the indicators to track it.

The perspective being brought to bear on these questions of well-being is comprehensive and embracing. Data and demographics and quantitative indicators of well-being are matched with stories and narratives from affected parties, videos, and a variety of display and visualization options. Much of the supporting data is organized by the 236 neighborhoods in Winnipeg, or broader community areas, with comparative baselines to city, province and nation. The information is both hard and soft, and presented in engaging, exciting and dynamic ways. Using the best of current social media, Peg is meant to be a virtual meeting place and town hall for the public to share and engage one another.

This beta is but a first expression of Peg’s longer-term vision, yet already has the backbone to take on these labors. A concept explorer allows the public to explore and navigate through the entire information space; much information is mapped and presented in locational relevance; narratives and stories and videos are linked contextually to topics and issues; and many, many dashboards can be created and displayed for showing trends and comparing neighborhoods, and letting the data speak visually:

Peg Explorer Peg Map Tab
Peg Stories Tab Peg Dashboard Tab

The current beta is but a start. The Peg project, in continued consultation with stakeholders, will be developing further indicators for each of its eight major themes, providing information about past and current trends, and expanding into additional cross-cutting issues. Daily, the site will see an increase in richness and relevance.

Project Participants

Peg has been spearheaded by the United Way of Winnipeg and the International Institute for Sustainable Development (IISD), also based in Winnipeg, with the partnership of the Province of Manitoba, the City of Winnipeg, Health in Common, and a cross section of community interests and members across the city. Peg is a non-profit effort, and is embarking on a new three-year work plan to oversee further funding and expansion.

Peg is governed by a Steering Committee with budgetary and strategic responsibilities. Peg also works with an Engagement Group — a broad-based group of Winnipeggers — that serves as a testing ground for ideas, direction and policy. The site provides credits for the various entities involved and responsible for the effort.

IISD has provided overall project management for the current effort. As personal thanks, we’d especially like to recognize Connie Walker, Laszlo Pinter, Christa Rust and Charles Thrift. Tactica, also of Winnipeg, has been the lead graphics and site designer for Peg. SD has worked closely with them to ensure a smooth launch, and they’ve done a great job. Thanks to all!

Now, This is Semantics Done Right

Of course, for more on the project, go directly to the Peg site or those of its other major participants and contributors. But, in our role as implementers of the behind-the-scenes wizardry powering the site, we would be remiss if we did not mention a couple of technical items.

As lead technical developer, SD was responsible for all data access, management, development and visualization software for the site. The site was developed in Drupal, with Virtuoso as the RDF data store and Solr for faceted site search. As part of its Open Semantic Framework, based on the Citizen Dan local government appliance, SD contributed and extended major open source software for Peg. These contributions included the structWSF Web services framework, conStruct modules for linking the system into Drupal, and the Flex-based semantic Components including the explorer, map, story viewer, browse/search, dashboard, workbench and back office widgets. We also developed the adaptive ontology driving the entire site, based on the Peg framework vocabulary already hashed out by the community participants.

During the course of the project we developed an entirely new workbench capability for creating new, persistent dashboards. We extended the sRelationBrowser semantic component with complete and flexible theming and styling; virtually all aspects of nodes, edges and behavior have now been exposed for tailoring, including fonts, colors and use of images. We enhanced the irON format to make it easier for project participants to submit spreadsheet datasets to the site for new indicator data. We will be migrating these advances to our existing open source software over the coming weeks. Check Fred Giasson’s blog for release details; he has also begun a series on the technology details.

But, in my opinion, what is most remarkable about all of this is that these bloody details are completely hidden from the user. Though real geeks can get RDF and linked data via export options, for the standard user they simple interact and experience the site. No triples are shoved in their face, no technology screams out for attention, and ne’er any URIs are to be found. The thing simply works, all the while being flexible, contextual, attractive and fun.

And that, folks, I submit, is semantics done right!

Posted:November 1, 2010

SemanticWeb.com

Jennifer Zaino of SemanticWeb.com has just published an interview with me regarding our recently announced partnership with Ontotext and its relation to linked data. Thanks, Jenny, for a fair and accurate representation of our conversation!

Some of the questions related to reference vocabularies and linking predicates are somewhat hard to convey. Jenny did a very nice job capturing some nuanced concepts. I invite you to read the article yourself and judge.

Posted:October 25, 2010

Objective is to Tackle the ‘Semantics’ Gap in the Semantic Web

OntotextStructured Dynamics I’m pleased to announce that our company, Structured Dynamics, has formed a strategic partnership with Ontotext, a leading semantic technology company for the past 10 years.

Ontotext is the developer of OWLIM, a highly scalable semantic database engine, and KIM, a popular semantic annotation and search platform. Its FactForge and LinkedLifeData services provide the largest curated and interoperable linked data platforms over which inferencing and reasoning may be applied. Some of Ontotext’s major clients include AstraZeneca, BBC and Korea Telecom. Major professional services include its own technologies, plus text mining and semantic annotation. Ontotext has notable and longstanding technical partnerships, such as with the GATE team and many of the other leading technologies and companies in the semantic Web space. We are very pleased to join forces with them.

Semantic ‘Gap’ is Basis of Partnership

Our partnership was formed to address some of the key semantic ‘gaps’ in the semantic Web. The partnership will focus on development of the next generation of the UMBEL and PROTON ontologies, as well as tools and applications based on them.

Volumes of linked data on the Web are growing. This growth is exposing three key weaknesses:

  1. inadequate semantics for how to link disparate information together that recognizes inherently different contexts and viewpoints and (often) approximate mappings
  2. misapplication of many linking predicates, such as owl:sameAs, and
  3. a lack of coherent reference concepts by which to aggregate and organize this linkable content.

Thanks to the efforts of the W3C (World Wide Web Consortium), we now have the techniques, languages and standards to deliver the “web” portion of the semantic Web. But, the practical “semantics” for actually effecting the semantic Web have heretofore been lacking. Early experience with linked data has exposed many poor practices. The lack of approximate linking predicates and reference concepts undercuts our ability to achieve meaningful semantic interoperability.

In forming our partnership, Ontotext and SD will shine attention on this semantics “gap”. We will also be aggressively seeking additional partners and players to join with us on this challenge. My recent outreach to DCMI (the Dublin Core Metadata Initiative) is one example of this commitment; we will be talking with others in the coming weeks.

Linked data and the prospects of the semantic Web are at a critical juncture. While we have seen much growth in the release of linked data, we are still not seeing much uptake (other than some curated pockets). Linkages between datasets are still disappointingly low, and quality of linkages is an issue. The time has come to stop simply shoveling more triples over the fence.

Building Blocks

The combination of UMBEL and PROTON offers a powerful blend to address these weaknesses. Our partnership will first provide a logical mapping and consolidated framework based on the two core ontologies. These will be made available as standard ontologies and via open source semantic annotation tools.

UMBEL PROTONUMBEL (Upper Mapping and Binding Exchange Layer) is both a vocabulary for building domain ontologies and a framework of more than 20,000 reference concepts. The UMBEL reference ontology is used to tag information and map existing schema in order to help link content and promote interoperability. UMBEL’s reference concepts and structure are a direct subset extraction of the Cyc knowledge base.

The PROTON ontology (PROTo ONtology) is a basic upper-level ontology that contains about 300 classes and 100 properties, providing coverage of the general concepts necessary for a wide range of tasks, including semantic annotation, indexing, and retrieval of documents. It is domain independent with coverage suitable to encompass any domain or named entity.

This consolidated framework will then be applied to organize and provide a coherent categorization of the Wikipedia online encyclopedia. One expression of this result will be a new version of Ontotext’s FactForge, already the largest and best performing reasoning engine leveraging linked data. This new version will allow easy access to the most central Linking Open Data (LOD) datasets such as DBpedia, Freebase, and Geonames, through the vocabularies of UMBEL and PROTON. Additional applications in linked data mining and general tagging of standard Web content are also contemplated by the partnership.

Ontotext’s proven reasoning technologies and ability to host extremely large knowledge bases with great performance are tremendous boons to the next iteration of UMBEL. We have been seeking large-scale coherency testing of UMBEL for some time and Ontotext is the perfect answer.

Ontotext’s CEO, Atanas Kiryakov, indicated their interest in UMBEL stemmed from what they saw as some stumbling blocks with linked data while developing FactForge. “The growth and maturation of linked data will require credible ways to orient and annotate the data,” said Kiryakov. “UMBEL is the right scope of comprehensiveness and size to use as one foundation for this,” he said. Ontotext is also the original developer and current maintainer of PROTON, which will also contribute in this role.

What is to Come?

The efforts of the partnership will first be seen with release of UMBEL v. 0.80 in the next couple of weeks. This update revises many aspects of the ontology based on two years of applied experience and updates it to OWL 2. Then, this basis will be used for broader mappings and linkages to Wikipedia. Those next mappings are earmarked for UMBEL version 1.00, slated for release by the end of the year. All of these planned efforts will be released as open source.

Among other intended uses, PROTON, UMBEL and FactForge form a layered reference data structure that will be used for data integration within the European Union research project RENDER. The large-scale RENDER project aims to integrate diverse methods in the ways Web information is selected, ranked, aggregated, presented and used.

Beyond that, further relationships and partnerships are being actively sought with players serious about interoperable, high-quality data on the semantic Web. We welcome inquiries or outreach.