Shifting the Center of Gravity to the OWL API, Web Services

Previous installments in this series have listed existing ontology tools, overviewed development methodologies, and proposed a new approach to building lightweight, domain ontologies [1]. For the latter to be successful, a new generation in ontology development tools is needed. This post provides an explication of the landscape under which this new generation of tools is occurring.

Ontologies supply the structure for relating information to other information in the semantic Web or the linked data realm. Because of this structural role, ontologies are pivotal to the coherence and interoperability of interconnected data.

We are now concluding the first decade of ontology development tools, especially those geared to the semantic Web and its associated languages of RDFS and OWL. Last year we also saw the release of the major update to the OWL 2 language, with its shift to more expressiveness and a variety of profiles. The upcoming next generation of ontology tools now must also shift.

The current imperative is to shift away from ontology engineering by a priesthood to pragmatic daily use and maintenance by domain practitioners. Market growth demands simpler, task-focused tools with intuitive interfaces. For this change to occur, the general tools architecture needs to shift its center of gravity from IDEs and comprehensive toolkits to APIs and Web services. Not surprisingly, this same shift is what has been occurring across all areas of software.

Methodology Reprise: The Nature of the Landscape

In the previous installment of this series, we presented a new methodological approach to ontology development, geared to lightweight, domain ontologies. One aspect of that design was to separate the operational workflow into two pathways:

• Instances, and their descriptive characteristics, and
• Conceptual relationships, or ontologies.

The ontology build methodology concentrated on the upper half of this diagram (blue, with yellow lead-ins and outcomes) with the various steps overviewed in that installment [2]:

Figure 1. Flowchart of Ontology Development Methodology (click to expand)

The methodology captured in this diagram embraces many different emphases from current practice:  re-use of existing structure and information assets; conscious split between instance data (ABox) and the conceptual structure (TBox) [3]; incremental design; coherency and other integrity testing; and explicit feedback for scope extension and growth. The methodology also embraces some complementary utility ontologies that also reflect the design of ontology-driven apps [4].

These are notable changes in emphasis. But they are not the most important one. The most important change is the tools landscape to implement this methodology. This landscape needs to shift to pragmatic daily use and maintenance by domain practitioners. That requires simpler and more task-oriented tools. And that change in tooling needs a still more fundamental shift in tools architecture and design.

A Legacy of Excellent First Generation Tools

In many places throughout this series I use the term “inadequate” to describe the current state of ontology development tools. This characterization is not a criticism of first-generation tools per se. Rather, it is a reflection of their inadequacy to fulfill the realities of the new tooling landscape argued in this series. The fact remains, as initial generation tools, that many of the existing tools are quite remarkable and will play central roles (mostly for the professional ontologist or developer) moving forward.

At the risk of overlooking some important players, let’s trace the (partial) legacy of some of the more pivotal tools in today’s environment.

As early as a decade ago the ontology standards languages were still in flux and the tools basis was similarly immature. Frame logic, description logics, common logic and many others were competing at that time for primacy and visibility. Most ontology tools at that time such as Protégé [5], OntoEdit [6], or OilEd [7] were based on F-logic or the predecessor to OWL, DAML+Oil. But the OWL language was under development by the W3C and in anticipation of its formal release the tools environment was also evolving to meet it. Swoop [8], for example, was one of the first dedicated OWL browsers. A Protégé plug-in for OWL was also developed by Holger Knublauch [9]. In parallel, the OWL group at the University of Manchester also introduced the OWL API [10].

With the formal release of OWL 1.0 in 2004, ontology tools continued to migrate to the language. Protégé, up through the version 3x series, became a popular open source system with many visualization and OWL-related plug-ins. Knublauch joined TopQuadrant and brought his OWL experience to TopBraid Composer, which shifted to the Eclipse IDE platform and leveraged the Jena API [9,11]. In Europe, the NeON (Networked Ontologies) project started in 2006 and by 2008 had an Eclipse-based OWL platform using the OWL API with key language processing capabilities through GATE [12].

Most recently, Protégé and NeON in open source, and TopBraid Composer on the commercial side, have likely had the largest market share of the comprehensive ontology toolkits. So far, with the release of OWL 2 in late 2009, only Protégé in version 4 and the TwoUse Toolkit have yet fully embraced all aspects of the new specification, doing so by intimately linking with the new OWL API (version 3x has full OWL 2 support) [13]. However, most leading reasoners now support OWL 2 and products such as TopBraid Composer and Ontotext’s OWLIM support OWL 2 RL as well [14].

The evolution of Protégé to version 4 (OWL 2) was led by the University of Manchester via its CO-ODE project [15], now ended, which has also been a source for most existing Protégé 4 plug-ins. (Because of the switch to OWL 2 and the OWL API most earlier plug-ins are incompatible with Protégé 4.) Manchester has also been a leading force in the development of OWL 2 and the alternative Manchester syntax.

Though only recently stable because of the formalization of OWL 2, Protégé 4 and its linkage to the new OWL API provides for a very powerful combination. With Protégé, the system has a familiar ontology editing framework and a mechanism for plug-in migration and growth. With the OWL API, there is now a common API for leading reasoners (Pellet, HermiT, FaCT++, RacerPro, etc.), a solid ontology management and annotation framework, and validators for various OWL 2 profiles (RL, EL and QL). The system is widely embraced by the biology community, probably the most active scientific field in ontologies. However, plug-in support lags the diversity of prior versions of Protégé and there does not appear to be the energy and community standing behind it as in prior years.

A Normative Tools Landscape

These leading frameworks and toolkits have opted to be “ontology engineering” environments. Via plug-ins and complicated interfaces (tabs or Eclipse-style panes) the intent has apparently been to provide “all capabilities in one box.” The tools have been IDE-centric.

Unfortunately, one must be a combination of ontologist, developer, programmer and IDE expert in order use the tools effectively. And, as incremental capabilities get added to the systems, these also inherit the same complexity and style of the host environment. It is simply not possible to make complex environments and conventions simple.

Curiously, the existence or use of APIs have also not been adequately leveraged. The usefulness of an API means that subsets of information can be extracted and worked on in very clear and simple ways. This information can then be roundtripped without loss. An API allows a tailored subset abstraction of the underlying data model. In contrast, IDEs, such as Protégé or Eclipse, when they play a similar role, force all interfaces to share their built-in complexity.

With these thoughts in mind, then, we set out to architect a tools suite and work flow that could truly take advantage of a central API. We further wanted to isolate the pieces into distributable Web services in keeping with our standard structWSF Web services framework design.

This approach also allows us to split out simpler, focused tools that domain users and practitioners can use. And, we can do all of this while also enabling the existing professional toolsets and IDEs to also interoperate in the environment.

The resulting tools landscape is shown in the diagram below. This diagram takes the same methodology flow from Figure 1 (blue and yellow boxes) and stretches them out in a more linear fashion. Then, we embed the various tools (brown) and APIs (orange) in relation to that methodology:

Figure 2. The Normative Ontology Tools Landscape (click to expand)

This diagram is worth expanding to full size and studying in some detail. Aspects of this diagram that deserve more discussion are presented in the sections below.

OWL API as Center of Gravity

As noted in the preceding methodology installment, the working ontology is the central object being managed and extended for a given deployment. Because that ontology will evolve and grow over time, it is important the complete ontology specification itself be managed by some form of version control system (green) [16]. This is the one independent tool in the landscape.

Access to and from the working ontology is mediated by the OWL API [13]. The API allows all or portions of the ontology specification to be manipulated separately, with a variety of serializations. Changes made to the ontology can also be tested for validity. Most leading reasoners can interact directly with the API. Protégé 4 also interacts directly with the API, as can various rules engines [17]. Additionally, other existing APIs, notably the Alignment API with its own mapping tools and links to other tools such as S-Match can interact with the OWL API. It is reasonable to expect more APIs to emerge over time that also interoperate [18].

The OWL API is the best current choice because of its native capabilities and because Jena does not yet support OWL 2 [11]. However, because of the basic design with structWSF (see next), it is also possible to swap out with different APIs at a later time should developments warrant.

In short, having the API play the central management role in the system means that any and all tools can be designed to interact effectively with the working ontology(ies) without any loss in information due to roundtripping.

Web Services (structWSF) as Canonical Access Layer

The same rationale that governed our development of structWSF [19] applies here: to abstract basic services and functionality through a platform-independent Web services layer. This Web services layer has canonical (standard) ways to interact with other services and is generally RESTful in design to support distributed deployments. The design conforms to proper separation of view from logic and structure. Moreover, because of the design, changes can be made on either side of the layer in terms of user interface or functionality.

Use of the structWSF layer also means that tools and functionality can be distributed anywhere on the Web. Specialized server-side functions can be supported as well as dedicated specialty hardware. Text indexing or disambiguation services can fit within this design.

The ultimate value of piggybacking on the structWSF framework is that all other extant services also become available. Thus, a wealth of converters, data managers, and semantic components (or display widgets) can be invoked depending on the needs of the specific tool.

Simpler, Task-specific Tools

The objective, of course, of this design is to promote more and simpler tools useful to domain users. Some of these are shown under the Use & Maintain box in the diagram above; others are listed by category in the table below.

The RESTful interface and parameter calls of the structWSF layer further simplify the ontology management and annotation abstractions arising from the OWL API. The number of simple tools available to users under this design is virtually limitless. These tools are also fast to develop and test.

Combining These New Thrusts and Moving Forward

This landscape is not yet a full reality. It is a vision of adaptive and simpler tools, working with a common API, and accessible via platform-independent Web services. It also preserves many of the existing tools and IDEs familiar to present ontology engineers.

However, pieces of this landscape do presently exist and more are on the way. The next section briefly overviews some of the major application areas where these tools might contribute.

Individual Tools within the Landscape

If one inspects the earlier listing of 185 ontology tools it is clear that there is a diversity of tools both in terms of scope and function across the entire ontology development stack. It is also clear that nearly all of those 185 tools listed do not communicate with one another. That is a tremendous waste.

Via shared APIs and some degree of consistent design it should be possible to migrate these capabilities into a more-or-less interoperating whole. We have thus tried to categorize some important tool types and exemplar tools from that listing to show the potential that exists. (Please note that the Example Tools are links to the tools and categories from the earlier 185 tools listing.)

This correlation of types and example tools is not meant to be exhaustive nor a recommendation of specific tools. But, this tabulation is illustrative of the potential that exists to both simplify and extend tool support across the entire ontology development workflow:

The beauty of this approach is that most of the tools listed are open source and potentially amenable to the minor modifications necessary to conform with this proposed landscape.

Key Gaps in the Landscape

Contrasting the normative tools landscape above with the existing listing of ontology tools points out some key gaps or areas deserving more development attention. Some of these are:

• Vocabulary managers — easy inspection and editing environments for concepts and predicates are lacking. Though standard editors allow direct ontology language edits (OWL or RDFS), these are not presently navigable or editable by non-ontologists. Intuitive browsing structures with more “infobox”-like editing environments could be helpful here
• Graph API — it would be wonderful to have a graph API (including analysis options) that could communicate with the OWL API. Failing that, it would be helpful to have a graph API that communicated well with RDF and ontology structures; extant options are few
• Large-graph visualizer — while we have earlier reviewed large-scale graph visualization software, the alternatives are neither easy to set up nor use. Being able to readily select layout options with quick zooms and scaling options are important
• Graphical editor — some browsers or editors (e.g, FlexViz) provide nice graph-based displays of ontologies and their properties and annotations. However, there appear to be few environments where the ontology graph can be directly edited or visually used for design or expansion.

Finally, it does appear that the effort and focus behind Protégé seems to be slowing somewhat. The future has clearly shifted to OWL 2 with Protégé 4. Yet, besides the admirable CO-ODE project (now ended), tools and plug-in support seems to have slowed. Many of the admirable plug-ins for Protégé 3x do not appear to be under active development as upgrades to Protégé 4. While Protégé’s future (and similar IDEs) seems assured, its prominence possibly will (and should) be replaced by a simpler kit of tools useful to users and practitioners.

Funding and Pending Project Priorities

For the past few months we at Structured Dynamics have seen ontology design and management as the pending technical priorities within the semantic technology space. Now that the market no longer looks at “ontology” as a four-letter word, it is imperative to simplify the development and use of ontologies. The first generation of tools leading up to this point have been helpful to understand the semantic space; changes are now necessary to expand it.

In our first generation we have begun to understand the types and nature of needed tools. But our focus on IDEs and comprehensive toolsets belies a developer’s or technologist’s perspective. We need to now shift focus and look at tool needs from the standpoint of users and actual use of ontologies. Many players and many toolmakers and innovators will need to contribute to build this market for semantic technologies and approaches.

Fortunately, replacing an IDE focus with one based around APIs and Web services should be a fairly smooth and natural transition. If we truly desire to be market makers, we need to stand back and place ourselves into the shoes of the domain practitioners, the subject matter experts. We need to shield actual users from all of the silly technical details and complexity. And, then, let’s focus — task-by-task — on discrete items of management and use of ontologies. Growth of the semantic technology space depends on expanding our practitioner base.

For its part, Structured Dynamics is presently seeking new projects and sponsors with a commitment to these aims. Like our prior development of structWSF and semantic components, we will be looking to make simpler ontology tools a priority in the coming months. Please let me know if you want to partner with us toward this commitment.

Earlier Listing is Expanded by More than 30%

At the beginning of this year Structured Dynamics assembled a listing of ontology building tools at the request of a client. That listing was presented as The Sweet Compendium of Ontology Building Tools. Now, again because of some client and internal work, we have researched the space again and updated the listing [1].

All new tools are marked with <New> (new only means newly discovered; some had yet to be discovered in the prior listing). There are now a total of 185 tools in the listing, 31 of which are recently new, and 45 added at various times since the first release. <Newest> reflects updates — most from the developers themselves — since the original publication of this post.

Comprehensive Ontology Tools

• Altova SemanticWorks is a visual RDF and OWL editor that auto-generates RDF/XML or nTriples based on visual ontology design. No open source version available
• Amine is a rather comprehensive, open source platform for the development of intelligent and multi-agent systems written in Java. As one of its components, it has an ontology GUI with text- and tree-based editing modes, with some graph visualization
• The Apelon DTS (Distributed Terminology System) is an integrated set of open source components that provides comprehensive terminology services in distributed application environments. DTS supports national and international data standards, which are a necessary foundation for comparable and interoperable health information, as well as local vocabularies. Typical applications for DTS include clinical data entry, administrative review, problem-list and code-set management, guideline creation, decision support and information retrieval.. Though not strictly an ontology management system, Apelon DTS has plug-ins that provide visualization of concept graphs and related functionality that make it close to a complete solution
• DOME is a programmable XML editor which is being used in a knowledge extraction role to transform Web pages into RDF, and available as Eclipse plug-ins. DOME stands for DERI Ontology Management Environment
• FlexViz is a Flex-based, Protégé-like client-side ontology creation, management and viewing tool; very impressive. The code is distributed from Sourceforge; there is a nice online demo available; there is a nice explanatory paper on the system, and the developer, Chris Callendar, has a useful blog with Flex development tips
• <Newest> ITM supports the management of complex knowledge structures (metadata repositories, terminologies, thesauri, taxonomies, ontologies, and knowledge bases) throughout their lifecycle, from authoring to delivery. ITM can also manage alignments between multiple knowledge structures, such as thesauri or ontologies, via the integration of INRIA’s Alignment API. Commercial; from Mondeca
• Knoodl facilitates community-oriented development of OWL based ontologies and RDF knowledge bases. It also serves as a semantic technology platform, offering a Java service-based interface or a SPARQL-based interface so that communities can build their own semantic applications using their ontologies and knowledgebases. It is hosted in the Amazon EC2 cloud and is available for free; private versions may also be obtained. See especially the screencast for a quick introduction
• The NeOn toolkit is a state-of-the-art, open source multi-platform ontology engineering environment, which provides comprehensive support for the ontology engineering life-cycle. The v2.3.0 toolkit is based on the Eclipse platform, a leading development environment, and provides an extensive set of plug-ins covering a variety of ontology engineering activities. You can add these plug-ins or get a current listing from the built-in updating mechanism
• ontopia is a relative complete suite of tools for building, maintaining, and deploying Topic Maps-based applications; open source, and written in Java. Could not find online demos, but there are screenshots and there is visualization of topic relationships
• Protégé is a free, open source visual ontology editor and knowledge-base framework. The Protégé platform supports two main ways of modeling ontologies via the Protégé-Frames and Protégé-OWL editors. Protégé ontologies can be exported into a variety of formats including RDF(S), OWL, and XML Schema. There are a large number of third-party plugins that extends the platform’s functionality
  • Protégé Plugin Library – frequently consult this page to review new additions to the Protégé editor; presently there are dozens of specific plugins, most related to the semantic Web and most open source
  • Collaborative Protégé is a plug-in extension of the existing Protégé system that supports collaborative ontology editing as well as annotation of both ontology components and ontology changes. In addition to the common ontology editing operations, it enables annotation of both ontology components and ontology changes. It supports the searching and filtering of user annotations, also known as notes, based on different criteria. There is also an online demo
  • <New>Web Protégé is an online version of Protégé attempting to capture all of the native functionality; still under development
• <New>Sigma is open source knowledge engineering environment that includes ontology mapping, theorem proving, language generation in multiple languages, browsing, OWL read/write, and analysis. It includes the Suggested Upper Merged Ontology (SUMO), a comprehensive formal ontology. It’s under active development and use
• TopBraid Composer is an enterprise-class modeling environment for developing Semantic Web ontologies and building semantic applications. Fully compliant with W3C standards, Composer offers comprehensive support for developing, managing and testing configurations of knowledge models and their instance knowledge bases. It is based on the Eclipse IDE. There is a free version (after registration) for small ontologies
• <New>TwoUse Toolkit is an implementation of current OMG and W3C standards for developing ontology-based software models and model-based OWL2 ontologies, largely based around UML. There are a variety of tools, including graphics editors, with more to come
• <New>Wandora is a topic maps engine written in Java with support for both in-memory topic maps and persisting topic maps in MySQL and SQL Server. It also contains an editor and a publishing system, and has support for automatic classification. It can read OBO, RDF(S), and many other formats, and can export topic maps to various graph formats. There is also a web-based topic maps browser, and graphical visualization.

Not Apparently in Active Use

• Adaptiva is a user-centred ontology building environment, based on using multiple strategies to construct an ontology, minimising user input by using adaptive information extraction
• Exteca is an ontology-based technology written in Java for high-quality knowledge management and document categorisation, including entity extraction. Though code is still available, no updates have been provided since 2006. It can be used in conjunction with search engines
• IODT is IBM’s toolkit for ontology-driven development. The toolkit includes EMF Ontolgy Definition Metamodel (EODM), EODM workbench, and an OWL Ontology Repository (named Minerva)
• KAON is an open-source ontology management infrastructure targeted for business applications. It includes a comprehensive tool suite allowing easy ontology creation and management and provides a framework for building ontology-based applications. An important focus of KAON is scalable and efficient reasoning with ontologies
• Ontolingua provides a distributed collaborative environment to browse, create, edit, modify, and use ontologies. The server supports over 150 active users, some of whom have provided us with descriptions of their projects. Provided as an online service; software availability not known.

Vocabulary Prompting Tools

• AlchemyAPI from Orchestr8 provides an API based application that uses statistical and natural language processing methods. Applicable to webpages, text files and any input text in several languages
• BooWa is a set expander for any language (formerly known as SEALS); developed by RC Wang of Carnegie Mellon
• Google Keywords allows you to enter a few descriptive words or phrases or a site URL to generate keyword ideas
• Google Sets for automatically creating sets of items from a few examples
• Open Calais is free limited API web service to automatically attach semantic metadata to content, based on either entities (people, places, organizations, etc.), facts (person ‘x’ works for company ‘y’), or events (person ‘z’ was appointed chairman of company ‘y’ on date ‘x’). The metadata results are stored centrally and returned to you as industry-standard RDF constructs accompanied by a Globally Unique Identifier (GUID)
• Query-by-document from BlogScope has a nice phrase extraction service, with a choice of ranking methods. Can also be used in a Firefox plug-in (not texted with 3.5+)
• SemanticHacker (from Textwise) is an API that does a number of different things, including categorization, search, etc. By using ‘concept tags’, the API can be leveraged to generate metadata or tags for content
• TagFinder is a Web service that automatically extracts tags from a piece of text. The tags are chosen based on both statistical and linguistic analysis of the original text
• Tagthe.net has a demo and an API for automatic tagging of web documents and texts. Tags can be single words only. The tool also recognizes named entities such as people names and locations
• TermExtractor extracts terminology consensually referred in a specific application domain. The software takes as input a corpus of domain documents, parses the documents, and extracts a list of “syntactically plausible” terms (e.g. compounds, adjective-nouns, etc.)
• TermFinder uses Poisson statistics, the Maximum Likelihood Estimation and Inverse Document Frequency between the frequency of words in a given document and a generic corpus of 100 million words per language; available for English, French and Italian
• TerMine is an online and batch term extractor that emphasizes part of speech (POS) and n-gram (phrase extraction). TerMine is the terminological management system with the C-Value term extraction and AcroMine acronym recognition integrated
• Topia term extractor is a part-of-speech and frequency based term extraction tool implemented in python. Here is a term extraction demo based on this tool
• Topicalizer is a service which automatically analyses a document specified by a URL or a plain text regarding its word, phrase and text structure. It provides a variety of useful information on a given text including the following: Word, sentence and paragraph count, collocations, syllable structure, lexical density, keywords, readability and a short abstract on what the given text is about

• TrMExtractor does glossary extraction on pure text files for either English or Hungarian

• Wikify! is a system to automatically “wikify” a text by adding Wikipedia-like tags throughout the document. The system extracts keywords and then disambiguates and matches them to their corresponding Wikipedia definition
• Yahoo! Placemaker is a freely available geoparsing Web service. It helps developers make their applications location-aware by identifying places in unstructured and atomic content – feeds, web pages, news, status updates – and returning geographic metadata for geographic indexing and markup
• Yahoo! Term Extraction Service is an API to Yahoo’s term extraction service, as well as many other APIs and services in a variety of languages and for a variety of tasks; good general resource. The service has been reported to be shut down numerous times, but apparently is kept alive due to popular demand.

Initial Ontology Development

• COE COE (CmapTools Ontology Editor) is a specialized version of the CmapTools from IMHC. COE — and its CmapTools parent — is based on the idea of concept maps. A concept map is a graph diagram that shows the relationships among concepts. Concepts are connected with labeled arrows, with the relations manifesting in a downward-branching hierarchical structure. COE is an integrated suite of software tools for constructing, sharing and viewing OWL encoded ontologies based on these constructs
• Conzilla2 is a second generation concept browser and knowledge management tool with many purposes. It can be used as a visual designer and manager of RDF classes and ontologies, since its native storage is in RDF. It also has an online collaboration server [apparently last updated in 2008]
• http://diagramic.com/ has an online Flex network graph demo, which also has a neat facility for quick entry and visualization of relationships; mostly small scale; pretty cool. Does not appear to be code available anywhere
• <New>DL-Learner is a tool for learning OWL class expressions from examples and background knowledge. It extends Inductive Logic Programming (ILP) to Description Logics and the Semantic Web. DL-Learner now has a flexible component based design, which allows to extend it easily with new learning algorithms, learning problems, reasoners, and supported background knowledge sources. A new type of supported knowledge sources are SPARQL endpoints, where DL-Learner can extract knowledge fragments, which enables learning classes even on large knowledge sources like DBpedia, and includes an OWL API reasoner interface and Web service interface.
• DogmaModeler is a free and open source, ontology modeling tool based on ORM. The philosophy of DogmaModeler is to enable non-IT experts to model ontologies with a little or no involvement of an ontology engineer; project is quite old, but the software is still available and it may provide some insight into naive ontology development
• Erca is a framework that eases the use of Formal and Relational Concept Analysis, a neat clustering technique. Though not strictly an ontology tool, Erca could be implemented in a work flow that allows easy import of formal contexts from CSV files, then algorithms that computes the concept lattice of the formal contexts that can be exported as dot graphs (or in JPG, PNG, EPS and SVG formats). Erca is provided as an Eclipse plug-in
• GraphMind is a mindmap editor for Drupal. It has the basic mindmap features and some Drupal specific enhancements. There is a quick screencast about how GraphMind looks like and what is does. The Flex source is also available from Github
• <New>H-Maps is a commercial suite of tools for building topic maps applications, consisting of a topic maps engine and server, a mapping framework for converting from legacy data, and a navigator for visualizing data. It is typically used in bioinformatics (drug discovery and research, toxicological studies, etc), engineering (support and expert systems), and for integration of hetereogeneous data. It supports the XTM 1.0 and TMAPI 1.0 specifications
• irON using spreadsheets, via its notation and specification. Spreadsheets can be used for initial authoring, esp if the irON guidelines are followed. See further this case study of Sweet Tools in a spreadsheet using irON (commON)
• <New>JXML2OWL API is a library for mapping XML schemas to OWL Ontologies on the JAVA platform. It creates an XSLT which transforms instances of the XML schema into instances of the OWL ontology. JXML2OWL Mapper is GUI application using the JXML2OWL API
• MindRaider is Semantic Web outliner. It aims to connect the tradition of outline editors with emerging technologies. MindRaider mission is to organize not only the content of your hard drive but also your cognitive base and social relationships in a way that enables quick navigation, concise representation and inferencing
• <New>Neologism is a simple web-based RDF Schema vocabulary editor and publishing system. Use it to create RDF classes and properties, which are needed to publish data on the Semantic Web. Its main goal is to dramatically reduce the time required to create, publish and modify vocabularies for the Semantic Web. It is written in PHP and built on the Drupal platform. Neologism is currently in alpha
• <New>OCS – Ontology Creation System is software to develop ontologies in cooperative way with a graphical interface
• RDF123 is an application and web service for converting data in simple spreadsheets to an RDF graph. Users control how the spreadsheet’s data is converted to RDF by constructing a graphical RDF123 template that specifies how each row in the spreadsheet is converted as well as metadata for the spreadsheet and its RDF translation
• <New>ROC (Rapid Ontology Construction) is a tool that allows domain experts to quickly build a basic vocabulary for their domain, re-using existing terminology whenever possible. How this works is that the ROC tool asks the domain expert for a set of keywords that are ‘core’ terms of the domain, and then queries remote sources for concepts matching those terms. These are then presented to the user, who can select terms from the list, find relations to other terms, and expand the set of terms and relations, iteratively. The resulting vocabulary (or ‘proto-ontology’, basically a SKOS-like thesaurus) can be used as is, or can be used as input for a knowledge engineer to base a more comprehensive domain ontology on. Interface “triples-oriented,” not graphical.
• Topincs is a Topic Map authoring software that allows groups to share their knowledge over the web. It makes use of a variety of modern technologies. The most important are Topic Maps, REST and Ajax. It consists of three components: the Wiki, the Editor, and the Server. The servier requires AMP; the Editor and Wiki are based on browser plug-ins.

Ontology Editing

• First, see all of the Comprehensive Tools and Ontology Development listings above
• Anzo for Excel includes an (RDFS and OWL-based) ontology editor that can be used directly within Excel. In addition to that, Anzo for Excel includes the capability to automatically generate an ontology from existing spreadsheet data, which is very useful for quick bootstrapping of an ontology
• <New>ATop is a topic map browser and editor written in Java and supports the XTM 1.0 specification; project has not been updated since 2008
• Hozo is an ontology visualization and development tool that brings version control constructs to group ontology development; limited to a prototype, with no online demo
• Lexaurus Editor is for off-line creation and editing of vocabularies, taxonomies and thesauri. It supports import and export in Zthes and SKOS XML formats, and allows hierarchical / poly-hierarchical structures to be loaded for editing, or even multiple vocabularies to be loaded simultaneously, so that terms from one taxonomy can be re-used in another, using drag and drop. Not available in open source
• Model Futures OWL Editor combines simple OWL tools, featuring UML (XMI), ErWin, thesaurus and imports. The editor is tree-based and has a “navigator” tool for traversing property and class-instance relationships. It can import XMI (the interchange format for UML) and Thesaurus Descriptor (BT-NT XML), and EXPRESS XML files. It can export to MS Word.
• <New>OBO-Edit is an open source ontology editor written in Java. OBO-Edit is optimized for the OBO biological ontology file format. It features an easy to use editing interface, a simple but fast reasoner, and powerful search capabilities
• <New>Onotoa is an Eclipse-based ontology editor for topic maps. It has a graphical UML-like interface, an export function for the current TMCL-draft and a XTM export
• OntoTrack is a browsing and editing ontology authoring tool for OWL Lite. It combines a sophisticated graphical layout with mouse enabled editing features optimized for efficient navigation and manipulation of large ontologies
• OWLViz is an attractive visual editor for OWL and is available as a Protégé plug-in
• PoolParty is a triple store-based thesaurus management environment which uses SKOS and text extraction for tag recommendations. See further this manual, which describes more fully the system’s functionality. Also, there is a PoolParty Web service that enables a Zthes thesaurus in XML format to be uploaded and converted to SKOS (via skos:Concepts)
• SKOSEd is a plugin for Protege 4 that allows you to create and edit thesauri (or similar artefacts) represented in the Simple Knowledge Organisation System (SKOS).
• TemaTres is a Web application to manage controlled vocabularies, taxonomies and thesaurus. The vocabularies may be exported in Zthes, Skos, TopicMap, etc.
• ThManager is a tool for creating and visualizing SKOS RDF vocabularies. ThManager facilitates the management of thesauri and other types of controlled vocabularies, such as taxonomies or classification schemes
• Vitro is a general-purpose web-based ontology and instance editor with customizable public browsing. Vitro is a Java web application that runs in a Tomcat servlet container. With Vitro, you can: 1) create or load ontologies in OWL format; 2) edit instances and relationships; 3) build a public web site to display your data; and 4) search your data with Lucene. Still in somewhat early phases, with no online demos and with minimal interfaces.
• <New>Vocab Editor is an RDF/OWL/SKOS vocabulary-diagram editor. It has both client- (Javascript) and server-side (Python) implmentations. It is open source with a demo. There is a blog (Spanish) and online sample vocabulary app editor.

Not Apparently in Active Use

• Omnigator The Omnigator is a form-based manipulaton tool centered on Topic Maps, though it enables the loading and navigation of any conforming topic map in XTM, HyTM, LTM or RDF formats. There is a free evaluation version.
• OntoGen is a semi-automatic and data-driven ontology editor focusing on editing of topic ontologies (a set of topics connected with different types of relations). The system combines text-mining techniques with an efficient user interface. It requires .Net.
• OntoLight is a set of software modules for: transforming raw ontology data for several ontologies from their specific formats into a unifying light-weight ontology format, grounding the ontology and storing it into grounded ontology format, populating grounded ontologies with new instance data, and creating mappings between grounded ontologies; includes Cyc. Download no longer available. See http://analytics.ijs.si/~blazf/papers/Context_SiKDD07.pdf and http://www.neon-project.org/web-content/index.php?option=com_weblinks&task=view&catid=17&id=52 or http://www.neon-project.org/web-content/index.php?option=com_weblinks&catid=21&Itemid=73
• OWL-S-editor is an editor for the development of services in OWL-S, with graphical, WSDL and import/export support
• ReTAX+ is an aide to help a taxonomist create a consistent taxonomy and in particular provides suggestions as to where a new entity could be placed in the taxonomy whilst retaining the integrity of the revised taxonomy (c.f., problems in ontology modelling)
• SWOOP is a lightweight ontology editor. (Swoop is no longer under active development at mindswap. Continuing development can be found on SWOOP’s Google Code homepage at http://code.google.com/p/swoop/)
• WebOnto supports the browsing, creation and editing of ontologies through coarse grained and fine grained visualizations and direct manipulation.

Ontology Mapping

• <New>The Alignment API is an API and implementation for expressing and sharing ontology alignments. The correspondences between entities (e.g., classes, objects, properties) in ontologies is called an alignment. The API provides a format for expressing alignments in a uniform way. The goal of this format is to be able to share on the web the available alignments. The format is expressed in RDF, so it is freely extensible. The Alignment API itself is a Java description of tools for accessing the common format. It defines four main interfaces (Alignment, Cell, Relation and Evaluator).
• COMA++ is a schema and ontology matching tool with a comprehensive infrastructure. Its graphical interface supports a variety of interaction
• ConcepTool is a system to model, analyse, verify, validate, share, combine, and reuse domain knowledge bases and ontologies, reasoning about their implication
• <New>MapOnto is a research project aiming at discovering semantic mappings between different data models, e.g, database schemas, conceptual schemas, and ontologies. So far, it has developed tools for discovering semantic mappings between database schemas and ontologies as well as between different database schemas. The Protege plug-in is still available, but appears to be for older versions
• MatchIT automates and facilitates schema matching and semantic mapping between different Web vocabularies. MatchIT runs as a stand-alone or plug-in Eclipse application and can be integrated with popular third party applications. MatchIT’s uses Adaptive Lexicon™ as an ontology-driven dictionary and thesaurus of English language terminology to quantify and ank the semantic similarity of concepts. It apparently is not available in open source
• myOntology is used to produce the theoretical foundations, and deployable technology for the Wiki-based, collaborative and community-driven development and maintenance of ontologies instance data and mappings
• OLA/OLA2 (OWL-Lite Alignment) matches ontologies written in OWL. It relies on a similarity combining all the knowledge used in entity descriptions. It also deal with one-to-many relationships and circularity in entity descriptions through a fixpoint algorithm
• Potluck is a Web-based user interface that lets casual users—those without programming skills and data modeling expertise—mash up data themselves. Potluck is novel in its use of drag and drop for merging fields, its integration and extension of the faceted browsing paradigm for focusing on subsets of data to align, and its application of simultaneous editing for cleaning up data syntactically. Potluck also lets the user construct rich visualizations of data in-place as the user aligns and cleans up the data.
• PRIOR+ is a generic and automatic ontology mapping tool, based on propagation theory, information retrieval technique and artificial intelligence model. The approach utilizes both linguistic and structural information of ontologies, and measures the profile similarity and structure similarity of different elements of ontologies in a vector space model (VSM).
• <New>S-Match takes any two tree like structures (such as database schemas, classifications, lightweight ontologies) and returns a set of correspondences between those tree nodes which semantically correspond to one another.
• Vine is a tool that allows users to perform fast mappings of terms across ontologies. It performs smart searches, can search using regular expressions, requires a minimum number of clicks to perform mappings, can be plugged into arbitrary mapping framework, is non-intrusive with mappings stored in an external file, has export to text files, and adds metadata to any mapping. See also http://sourceforge.net/projects/vine/.

Not Apparently in Active Use

• ASMOV (Automated Semantic Mapping of Ontologies with Validation) is an automatic ontology matching tool which has been designed in order to facilitate the integration of heterogeneous systems, using their data source ontologies
• Chimaera is a software system that supports users in creating and maintaining distributed ontologies on the web. Two major functions it supports are merging multiple ontologies together and diagnosing individual or multiple ontologies
• CMS (CROSI Mapping System) is a structure matching system that capitalizes on the rich semantics of the OWL constructs found in source ontologies and on its modular architecture that allows the system to consult external linguistic resources
• ConRef is a service discovery system which uses ontology mapping techniques to support different user vocabularies
• DRAGO reasons across multiple distributed ontologies interrelated by pairwise semantic mappings, with a vision of peer-to-peer mapping of many distributed ontologies on the Web. It is implemented as an extension to an open source Pellet OWL Reasoner
• Falcon-AO (Finding, aligning and learning ontologies) is an automatic ontology matching tool that includes the three elementary matchers of String, V-Doc and GMO. In addition, it integrates a partitioner PBM to cope with large-scale ontologies
• FOAM is the Framework for ontology alignment and mapping. It is based on heuristics (similarity) of the individual entities (concepts, relations, and instances)
• hMAFRA (Harmonize Mapping Framework) is a set of tools supporting semantic mapping definition and data reconciliation between ontologies. The targeted formats are XSD, RDFS and KAON
• IF-Map is an Information Flow based ontology mapping method. It is based on the theoretical grounds of logic of distributed systems and provides an automated streamlined process for generating mappings between ontologies of the same domain
• LILY is a system matching heterogeneous ontologies. LILY extracts a semantic subgraph for each entity, then it uses both linguistic and structural information in semantic subgraphs to generate initial alignments. The system is presently in a demo version only
• MAFRA Toolkit – the Ontology MApping FRAmework Toolkit allows users to create semantic relations between two (source and target) ontologies, and apply such relations in translating source ontology instances into target ontology instances
• OntoEngine is a step toward allowing agents to communicate even though they use different formal languages (i.e., different ontologies). It translates data from a “source” ontology to a “target”
• OWLS-MX is a hybrid semantic Web service matchmaker. OWLS-MX 1.0 utilizes both description logic reasoning, and token based IR similarity measures. It applies different filters to retrieve OWL-S services that are most relevant to a given query
• RiMOM (Risk Minimization based Ontology Mapping) integrates different alignment strategies: edit-distance based strategy, vector-similarity based strategy, path-similarity based strategy, background-knowledge based strategy, and three similarity-propagation based strategies
• semMF is a flexible framework for calculating semantic similarity between objects that are represented as arbitrary RDF graphs. The framework allows taxonomic and non-taxonomic concept matching techniques to be applied to selected object properties
• Snoggle is a graphical, SWRL-based ontology mapper. Snoggle attempts to solve the ontology mapping problem by providing a graphical user interface (similar to which of the Microsoft Visio) to guide the process of ontology vocabulary alignment. In Snoggle, user-defined mappings can be serialized into rules, which is expressed using SWRL
• Terminator is a tool for creating term to ontology resource mappings (documentation in Finnish).

Ontology Visualization/Analysis

Though all are not relevant, see my post from a couple of years back on large-scale RDF graph software.

• Social network graphing tools (many covered elsewhere)
• Cytoscape is a bioinformatics software platform for visualizing molecular interaction networks and integrating these interactions with gene expression profiles and other state data; I have also written specifically about Cytoscape’s use in UMBEL
  • RDFScape is a project that brings Semantic Web “features” to the popular Systems Biology software Cytoscape
  • NetworkAnalyzer performs analysis of biological networks and calculates network topology parameters including the diameter of a network, the average number of neighbors, and the number of connected pairs of nodes. It also computes the distributions of more complex network parameters such as node degrees, average clustering coefficients, topological coefficients, and shortest path lengths. It displays the results in diagrams, which can be saved as images or text files; used by SD
• Graphl is a tool for collaborative editing and visualisation of graphs, representing relationships between resources or concepts of the real world. Graphl may be thought of as a visual wiki, a place where everybody can contribute to a shared repository of knowledge
• <New>Graphviz is open source graph visualization software. It has several main graph layout programs. It also has web and interactive graphical interfaces, and auxiliary tools, libraries, and language bindings.
• <New>GrOWL is an ontology visualizer and editor. The layout of the GrOWL graph can be defined automatically or loaded from a separate style sheet. GrOWL implements configurable filters that can transform the display by simplifying it, hiding concepts and relationships that have no descriptions associated, or perform more complex translations. Concepts can be stored in ontologies with extensive annotations to provide documentation. GrOWL shows these annotation as tooltips, and supports complex HTML and links within them. The GrOWL browser can be used inside a web browser or as a stand-alone application. When used inside a browser, it supports Javascript interaction so that it can be used as a concept chooser with implementation-defined operations.
• igraph is a free software package for creating and manipulating undirected and directed graphs
• Network Workbench is a very complex, comprehensive; Swiss Army Knife
• NetworkX – Python; very clean
• <New>OntoGraf, a Protege 4 plug-in, gives support for interactively navigating the relationships of your OWL ontologies. Various layouts are supported for automatically organizing the structure of your ontology. Different relationships are supported: subclass, individual, domain/range object properties, and equivalence. Relationships and node types can be filtered.
• <New>OWL2Prefuse is a Java package which creats Prefuse graphs and trees from OWL files (and Jena OntModels). It takes care of converting the OWL data structure to the Prefuse datastructure. This makes it is easy for developers, to use the Prefuse graphs and trees into their Semantic Web applications.
• <New>RDF Gravity is a tool for visualising RDF/OWL Graphs/ ontologies. RDF Gravity is implemented by using the JUNG Graph API and Jena semantic web toolkit. Its main features are:
  • Graph Visualization
  • Global and Local Filters (enabling specific views on a graph)
  • Full text Search
  • Generating views from RDQL Queries
  • Visualising multiple RDF files
• <Newest> SKOS Reader is a SKOS browser and an HTML renderer of SKOS thesauri and terminologies that can display a SKOS file hierarchically, alphabetically, or permuted. Commercial; from Mondeca
• Stanford Network Analysis Package (SNAP) is a general purpose network analysis and graph mining library. It is written in C++ and easily scales to massive networks with hundreds of millions of nodes
• Social Networks Visualizer (SocNetV) is a flexible and user-friendly tool for the analysis and visualization of Social Networks. It lets you construct networks (mathematical graphs) with a few clicks on a virtual canvas or load networks of various formats (GraphViz, GraphML, Adjacency, Pajek, UCINET, etc) and modify them to suit your needs. SocNetV also offers a built-in web crawler, allowing you to automatically create networks from all links found in a given initial URL
• Tulip may be incredibly strong
  • quite active (but not much online stuff): http://sourceforge.net/projects/auber/files/
• Springgraph component for Flex
• VizierFX is a Flex library for drawing network graphs. The graphs are laid out using GraphViz on the server side, then passed to VizierFX to perform the rendering. The library also provides the ability to run ActionScript code in response to events on the graph, such as mousing over a node or clicking on it.
• <New>VUE (Visual Understanding Environment) is an open source project focused on creating flexible tools for managing and integrating digital resources in support of teaching, learning and research. VUE provides a flexible visual environment for structuring, presenting, and sharing digital information.
• <New>yEd is a diagram editor that can be used to quickly and effectively generate high-quality drawings of diagrams. It can support OWL imports.
• <New>ZGRViewer is a graph visualizer implemented in Java and based upon the Zoomable Visual Transformation Machine. It is specifically aimed at displaying graphs expressed using the DOT language from AT&T GraphViz and processed by programs dot, neato or others such as twopi. ZGRViewer is designed to handle large graphs, and offers a zoomable user interface (ZUI), which enables smooth zooming and easy navigation in the visualized structure.

Miscellaneous Ontology Tools

• Apolda (Automated Processing of Ontologies with Lexical Denotations for Annotation) is a plugin (processing resource) for GATE (http://gate.ac.uk/). The Apolda processing resource (PR) annotates a document like a gazetteer, but takes the terms from an (OWL) ontology rather than from a list
• <Newest>CA Manager supports customized workflows for semantic annotation of content. Commercial; from Mondeca
• <New>Gloze is a XML to RDF, RDF to XML, and XSD to OWL mapping tool based on Jena; see also http://jena.hpl.hp.com/juc2006/proceedings/battle/paper.pdf . See also http://jena.sourceforge.net/contrib/contributions.html
• <New>Hoolet is an implementation of an OWL-DL reasoner that uses a first order prover. The ontology is translated to collection of axioms (in an obvious way based on the OWL semantics) and this collection of axioms is then given to a first order prover for consistency checking.
• LexiLink is a tool for building, curating and managing multiple lexicons and ontologies in one enterprise-wide Web-based application. The core of the technology is based on RDF and OWL
• mopy is the Music Ontology Python library, designed to provide easy to use python bindings for ontology terms for the creation and manipulation of music ontology data. mopy can handle information from several ontologies, including the Music Ontology, full FOAF vocab, and the timeline and chord ontologies
• OBDA (Ontology Based Data Access) is a plugin for Protégé aimed to be a full-fledged OBDA ontology and component editor. It provides data source and mapping editors, as well as querying facilities that, in sum, allow you to design and test every aspect of an OBDA system. It supports relational data sources (RDBMS) and GLAV-like mappings. In its current beta form, it requires Protege 3.3.1, a reasoner implementing the OBDA extensions to DIG 1.1 (e.g., the DIG server for QuOnto) and Jena 2.5.5
• <New>oBrowse is a web based ontology browser developed in java. oBrowse parses OWL files of an ontology and displays ontology in a tree view. Protege-API, JSF are used in development
• OntoComP is a Protégé 4 plugin for completing OWL ontologies. It enables the user to check whether an OWL ontology contains “all relevant information” about the application domain, and extend the ontology appropriately if this is not the case
• Ontology Browser is a browser created as part of the CO-ODE (http://www.co-ode.org/) project; rather simple interface and use
• Ontology Metrics is a web-based tool that displays statistics about a given ontology, including the expressivity of the language it is written in
• <New>OntoLT aims at a more direct connection between ontology engineering and linguistic analysis. OntoLT is a Protégé plug-in, with which concepts (Protégé classes) and relations (Protégé slots) can be extracted automatically from linguistically annotated text collections. It provides mapping rules, defined by use of a precondition language that allow for a mapping between linguistic entities in text and class/slot candidates in Protégé. Only available for older Protégé versions
• OntoSpec is a SWI-Prolog module, aiming at automatically generating XHTML specification from RDF-Schema or OWL ontologies
• OWL API is a Java interface and implementation for the W3C Web Ontology Language (OWL), used to represent Semantic Web ontologies. The API is focused towards OWL Lite and OWL DL and offers an interface to inference engines and validation functionality
• OWL Module Extractor is a Web service that extracts a module for a given set of terms from an ontology. It is based on an implementation of locality-based modules that is part of the OWL API.
• OWL Syntax Converter is an online tool for converting ontologies between different formats, including several OWL syntaxes, RDF/XML, KRSS
• OWL Verbalizer is an on-line tool that verbalizes OWL ontologies in (controlled) English
• OwlSight is an OWL ontology browser that runs in any modern web browser; it’s developed with Google Web Toolkit and uses Gwt-Ext, as well as OWL-API. OwlSight is the client component and uses Pellet as its OWL reasoner
• Pellint is an open source lint tool for Pellet which flags and (optionally) repairs modeling constructs that are known to cause performance problems. Pellint recognizes several patterns at both the axiom and ontology level.
• PROMPT is a tab plug-in for Protégé is for managing multiple ontologies by comparing versions of the same ontology, moving frames between included and including project, merging two ontologies into one, or extracting a part of an ontology
• <New>ReDeFer is a compendium of RDF-aware utilities organised in a set of packages: RDF2HTML+RDFa: render a piece of RDF/XML as HTML+RDFa; XSD2OWL: transform an XML Schema into an OWL Ontology; CS2OWL: transform a MPEG-7 Classification Scheme into an OWL Ontology; XML2RDF: transform a piece of XML into RDF; and RDF2SVG: render a piece of RDF/XML as a SVG showing the corresponding graph
• SegmentationApp is a Java application that segments a given ontology according to the approach described in “Web Ontology Segmentation: Analysis, Classification and Use” (http://www.co-ode.org/resources/papers/seidenberg-www2006.pdf)
• SETH is a software effort to deeply integrate Python with Web Ontology Language (OWL-DL dialect). The idea is to import ontologies directly into the programming context so that its classes are usable alongside standard Python classes
• SKOS2GenTax is an online tool that converts hierarchical classifications available in the W3C SKOS (Simple Knowledge Organization Systems) format into RDF-S or OWL ontologies
• SpecGen (v5) is an ontology specification generator tool. It’s written in Python using Redland RDF library and licensed under the MIT license
• Text2Onto is a framework for ontology learning from textual resources that extends and re-engineers an earlier framework developed by the same group (TextToOnto). Text2Onto offers three main features: it represents the learned knowledge at a metalevel by instantiating the modelling primitives of a Probabilistic Ontology Model (POM), thus remaining independent from a specific target language while allowing the translation of the instantiated primitives
• Thea is a Prolog library for generating and manipulating OWL (Web Ontology Language) content. Thea OWL parser uses SWI-Prolog’s Semantic Web library for parsing RDF/XML serialisations of OWL documents into RDF triples and then it builds a representation of the OWL ontology
• TONES Ontology Repository is primarily designed to be a central location for ontologies that might be of use to tools developers for testing purposes; it is part of the TONES project
• Visual Ontology Manager (VOM) is a family of tools enables UML-based visual construction of component-based ontologies for use in collaborative applications and interoperability solutions.
• Web Ontology Manager is a lightweight, Web-based tool using J2EE for managing ontologies expressed in Web Ontology Language (OWL). It enables developers to browse or search the ontologies registered with the system by class or property names. In addition, they can submit a new ontology file
• RDF evoc (external vocabulary importer) is an RDF external vocabulary importer module (evoc) for Drupal caches any external RDF vocabulary and provides properties to be mapped to CCK fields, node title and body. This module requires the RDF and the SPARQL modules.

Not Apparently in Active Use

• ActiveOntology is a library, written in Ruby, for easy manipulation of RDF and RDF-Schema models, thru a dynamic DSL based on Ruby idiom
• Almo is an ontology-based workflow engine in Java supporting the ARTEMIS project; part of the OntoWare initiative
• ClassAKT is a text classification web service for classifying documents according to the ACM Computing Classification System
• Elmo provides a simple API to access ontology oriented data inside a Sesame RDF repository. The domain model is simplified into independent concerns that are composed together for multi-dimensional, inter-operating, or integrated applications
• ExtrAKT is a tool for extracting ontologies from Prolog knowledge bases.
• F-Life is a tool for analysing and maintaining life-cycle patterns in ontology development.
• Foxtrot is a recommender system which represents user profiles in ontological terms, allowing inference, bootstrapping and profile visualization.
• HyperDAML creates an HTML representation of OWL content to enable hyperlinking to specific objects, properties, etc.
• LinKFactory is an ontology management tool, it provides an effective and user-friendly way to create, maintain and extend extensive multilingual terminology systems and ontologies (English, Spanish, French, etc.). It is designed to build, manage and maintain large, complex, language independent ontologies.
• LSW – the Lisp semantic Web toolkit enables OWL ontologies to be visualized. It was written by Alan Ruttenberg
• OntoClassify is a system for scalable classification of text into large topic ontologies currently including DMoz and Inspec. The system is available as Web service. The software runs under Windows platform.

• Ontodella is a Prolog HTTP server for category projection and semantic linking
• OntoWeaver is an ontology-based approach to Web sites, which provides high level support for web site design and development
• OWLLib is a PHP library for accessing OWL files. OWL is w3.org standard for storing semantic information
• pOWL is a Semantic Web development platform for ontologies in PHP. pOWL consists of a number of components, including RAP
• ROWL is the Rule Extension of OWL; it is from the Mobile Commerce Lab in the School of Computer Science at Carnegie Mellon University
• Semantic Net Generator is a utlity for generating Topic Maps automatically from different data sources by using rules definitions specified with Jelly XML syntax. This Java library provides Jelly tags to access and modify data sources (also RDF) to create a semantic network
• SMORE is OWL markup for HTML pages. SMORE integrates the SWOOP ontology browser, providing a clear and consistent way to find and view Classes and Properties, complete with search functionality
• SOBOLEO is a system for Web-based collaboration to create SKOS taxonomies and ontologies and to annotate various Web resources using them
• SOFA is a Java API for modeling ontologies and Knowledge Bases in ontology and Semantic Web applications. It provides a simple, abstract and language neutral ontology object model, inferencing mechanism and representation of the model with OWL, DAML+OIL and RDFS languages; from java.dev
• WebScripter is a tool that enables ordinary users to easily and quickly assemble reports extracting and fusing information from multiple, heterogeneous DAMLized Web sources.

Release of Semantic Components Adds Final Layer, Leads to Streamlined Sites

Yesterday Fred Giasson announced the release of code associated with Structured Dynamics‘ open source semantics components (also called sComponents).  A semantic component is an ontology-driven component, or widget, based on Flex. Such a component takes record descriptions, ontologies and target attributes/types as inputs and then outputs some (possibly interactive) visualizations of the records.

Though not all layers are by any means complete, from an architectural standpoint the release of these semantic components provides the last and missing layer to complete our open semantic framework. Completing this layer now also enables Structured Dynamics to rationalize its open source Web sites and various groups and mailing lists associated with them.

The OSF “Semantic Muffin”

We first announced the open semantic framework — or OSF — a couple of weeks back. Refer to that original post for more description of the general design [1]. However, we can show this framework with the semantic components layer as illustrated by what some have called the “semantic muffin”:

(click for full size)

The OSF stack consists of these layers, moving from existing assets upward through increasing semantics and usability:

• Existing assets — any and all existing information and data assets, ranging from unstructured to structured. Preserving and leveraging those assets is a key premise
• scones / irON — this layer is for general conversion of non-RDF data and data schema to RDF (via irON or RDFizers) or for information extraction of subject concepts or named entities (scones)
• structWSF — is the pivotal Web services framework layer, and provides the standard, common interface by which existing information assets get represented and presented to the outside world and to other layers in the OSF stack
• Semantic components — the highlighted layer in the “semantic muffin”; in essence, this is the visualization and data interaction layer in the OSF stack; see more below
• Ontologies — are the layer containing the structured assets “driving” the system; this includes the concepts and relationships of the domain at hand, and administrative ontologies that guide how the user interfaces or widgets in the system should behave, and
• conStruct — is the content management system (CMS) layer based on Drupal and the thinnest layer with respect to OSF; this optional layer provides the theming, user rights and permissions, or other functionality drawn from Drupal’s 6500 third-party modules.

Not all of these layers are required in a given deployment and their adoption need not be sequential or absolutely depend on prior layers. Nonetheless, they do layer and interact with one another in the general manner shown.

The Semantics Components Layer

Current semantic components, or widgets, include: filter; tabular templates (similar to infoboxes); maps; bar, pie or linear charts; relationship (concept) browser; story and text annotator and viewer; workbench for creating structured views; and dashboard for presenting pre-defined views and component arrangements. These are generic tools that respond to the structures and data fed to them, adaptable to any domain without modification.

Though Fred’s post goes into more detail — with subsequent posts to get into the technical nuances of the semantic components — the main idea of these components is shown by the diagram below.

These various semantic components get embedded in a layout canvas for the Web page. By interacting with the various components, new queries are generated (most often as SPARQL queries) to the various structWSF Web services endpoints. The result of these requests is to generate a structured results set, which includes various types and attributes.

An internal ontology that embodies the desired behavior and display options (SCO, the Semantic Component Ontology) is matched with these types and attributes to generate the formal instructions to the semantic components. These instructions are presented via the sControl component, that determines which widgets (individual components, with multiples possible depending on the inputs) need to be invoked and displayed on the layout canvas. Here is a picture of the general workflow:

(click for full size)

New interactions with the resulting displays and components cause the iteration path to be generated anew, again starting a new cycle of queries and results sets. As these pathways and associated display components get created, they can be named and made persistent for later re-use or within dashboard invocations.

Consolidating and Rationalizing Web Sites and Mailing Lists

As the release of the semantic components drew near, it was apparent that releases of previous layers had led to some fragmentation of Web sites and mailing lists. The umbrella nature of the open semantic framework enabled us to consolidate and rationalize these resources.

Our first change was to consolidate all OSF-related material under the existing OpenStructs.org Web site. It already contained the links and background material to structWSF and irON. To that, we added the conStruct and OSF material as well. This consolidation also allowed us to retire the previous conStruct Web site as well, which now re-directs to OpenStructs.

We also had fragmentation in user groups and mailing lists. Besides shared materials, these had many shared members. The Google groups for irON, structWSF and conStruct were thus archived and re-directed to the new Open Semantic Framework Google group and mailing list. Personal notices of the change and invites have been issued to all members of the earlier groups. For those interested in development work and interchange with other developers on any of these OSF layers, please now direct your membership and attention to the OSF group.

There has also been a revigoration of the developers’ community Web site at http://community.openstructs.org/. It remains the location for all central developer resources, including bug and issue tracking and links to SVNs.

Actual code SVN repositories are unchanged. These code repositories may be found at:

• structWSF
• conStruct
• Semantic Components
• irON Parsers.

We hope you find these consolidations helpful. And, of course, we welcome new participants and contributors!

We’re Speaking on Rich Interfaces and MIKE2.0

As I reported about a year ago after my first attendance, I think the Semantic Technology Conference is the best venue going for pragmatic discussion of semantic approaches in the enterprise. I’m really pleased that I will be attending again this year. The conference (#SemTech) will be held at the Hilton Union Square in downtown San Francisco on June 21-25, 2010. Now in its sixth year and the largest of its kind, it is again projected to attract 1500 attendees or so.

I will be presenting two papers this year, covering rather dramatically different topics. Such is the business of a young company like Structured Dynamics that wears many hats!

Rich User Interfaces for Semantic Technologies

A really exciting presentation for us is, Sizzle for the Steak: Rich, Visual Interfaces for Ontology-driven Apps, on Wed, June 23 in the 2:00 PM – 3:00 PM session.

A nagging gap in the semantic technology stack is acceptable — better still, compelling — user experiences. After our exile for a couple of years doing essential infrastructure work, we have been unshackled over the past year or so to innovate on user interfaces for semantic technologies.

Our unique approach uses adaptive ontologies to drive rich Internet applications (RIAs) through what we call “semantic components.” This framework is unbelievably flexible and powerful and can seamlessly interact with our structWSF Web services framework and its conStruct Drupal implementations.

We will be showing these rich user interfaces for the first time in this session. We will show concept explorers, “slicer-and-dicers”, dashboards, information extraction and annotation, mapping, data visualization and ontology management. Get your visualization anyway you’d like, and for any slice you’d like!

While we will focus on the sizzle and demos, we will also explain a bit of the technology that is working behind Oz’s curtain.

Methods for Becoming a Semantic Enterprise

A more informal, interactive F2F discussion will be, MIKE2.0 for the Semantic Enterprise, on Thurs, June 24 in the 4:45 PM – 5:45 PM slot.

MIKE2.0 (Method for an Integrated Knowledge Environment) is an open source methodology for enterprise information management that is coupled with a collaborative framework for information development. It is oriented around a variety of solution “offerings”, ranging from the comprehensive and the composite to specific practices and technologies. A couple of months back, I gave an overview of MIKE2.0 that was pretty popular.

We have been instrumental in adding a semantic enterprise component to MIKE2.0, with our specific version of it called Open SEAS. In this Face-to-Face session, experts and desirous practitioners will join together to discuss how to effectively leverage this framework. While I will intro and facilitate, expect many other MIKE2.0 aficionados to participate.

This is perhaps a new concept to many, but what is exciting about MIKE2.0 is that it provides a methodology and documentation complement to technology alone. When combined with that technology, all pieces comprise what might be called a total open solution. I personally think it is the next logical step beyond open source.

Hope to See You There!

So, if you have not already made plans, consider adjusting your schedule today. And, contact me in advance (mike at structureddynamics dot com) if you’ll be there. We’d love to chat!

In earlier posts, I described the significant progress in climbing the data federation pyramid, today’s evolution in emphasis to the semantic Web, and the 40 or so sources of semantic heterogeneity. We now transition to an overview of how one goes about providing these semantics and resolving these heterogeneities.

Why the Need for Tools and Automation?

In an excellent recent overview of semantic Web progress, Paul Warren points out:[1]

Although knowledge workers no doubt believe in the value of annotating their documents, the pressure to create metadata isn’t present. In fact, the pressure of time will work in a counter direction. Annotation’s benefits accrue to other workers; the knowledge creator only benefits if a community of knowledge workers abides by the same rules. . . . Developing semiautomatic tools for learning ontologies and extracting metadata is a key research area . . . .Having to move out of a user’s typical working environment to ‘do knowledge management’ will act as a disincentive, whether the user is creating or retrieving knowledge.

Of course, even assuming that ontologies are created and semantics and metadata are added to content, there still remains the nasty problems of resolving heterogeneities (semantic mediation) and efficiently storing and retrieving the metadata and semantic relationships.

Putting all of this process in place requires the infrastructure in the form of tools and automation and proper incentives and rewards for users and suppliers to conform to it.

Areas Requiring Tools and Automation

In his paper, Warren repeatedly points to the need for “semi-automatic” methods to make the semantic Web a reality. He makes fully a dozen such references, in addition to multiple references to the need for “reasoning algorithms.” In any case, here are some of the areas noted by Warren needing “semi-automatic” methods:

• Assign authoritativeness
• Learn ontologies
• Infer better search requests
• Mediate ontologies (semantic resolution)
• Support visualization
• Assign collaborations
• Infer relationships
• Extract entities
• Create ontologies
• Maintain and evolve ontologies
• Create taxonomies
• Infer trust
• Analyze links
• etc.

In a different vein, SemWebCentral lists these clusters of semantic Web-related tasks, each of which also requires tools:[2]

• Create an ontology — use a text or graphical ontology editor to create the ontology, which is then validated. The resulting ontology can then be viewed with a browser before being published
• Disambiguate data – generate a mapping between multiple ontologies to identify where classes and properties are the same
• Expose a relational database as OWL — an editor is first used to create the ontologies that represent the database schema, then the ontologies are validated, translated to OWL and then the generated OWL is validated
• Intelligently query distributed data – repository and again able to be queried
• Manually create data from an ontology — a user would use an editor to create new OWL data based on existing ontologies, which is then validated and browsable
• Programmatically interact with OWL content — custom programs can view, create, and modify OWL content with an API
• Query non-OWL data — via an annotation tool, create OWL metadata from non-OWL content
• Visualize semantic data — view semantic data in a custom visualizer.

With some ontologies approaching tens to hundreds of thousands to millions of triples, viewing, annotating and reconciling at scale can be daunting tasks, the efforts behind which would never be taken without useful tools and automation.

A Workflow Perspective Helps Frame the Challenge

A 2005 paper by Izza, Vincent and Burlat (among many other excellent ones) at the first International Conference on Interoperability of Enterprise Software and Applications (INTEROP-ESA) provides a very readable overview on the role of semantics and ontologies in enterprise integration.[3] Besides proposing a fairly compelling unified framework, the authors also present a useful workflow perspective emphasizing Web services (WS), also applicable to semantics in general, that helps frame this challenge:

Generic Semantic Integration Workflow (adapted from [3])

For existing data and documents, the workflow begins with information extraction or annotation of semantics and metadata (#1) in accordance with a reference ontology. Newly found information via harvesting must also be integrated; however, external information or services may come bearing their own ontologies, in which case some form of semantic mediation is required.

Of course, this is a generic workflow, and depending on the interoperation task, different flows and steps may be required. Indeed, the overall workflow can vary by perspective and researcher, with semantic resolution workflow modeling a prime area of current investigations. (As one alternative among scores, see for example Cardoso and Sheth.[4])

Matching and Mapping Semantic Heterogeneities

Semantic mediation is a process of matching schemas and mapping attributes and values, often with intermediate transformations (such as unit or language conversions) also required. The general problem of schema integration is not new, with one prior reference going back as early as 1986. [5] According to Alon Halevy:[6]

As would be expected, people have tried building semi-automated schema-matching systems by employing a variety of heuristics. The process of reconciling semantic heterogeneity typically involves two steps. In the first, called schema matching, we find correspondences between pairs (or larger sets) of elements of the two schemas that refer to the same concepts or objects in the real world. In the second step, we build on these correspondences to create the actual schema mapping expressions.

The issues of matching and mapping have been addressed in many tools, notably commercial ones from MetaMatrix,[7] and open source and academic projects such as Piazza, [8] SIMILE, [9] and the WSMX (Web service modeling execution environment) protocol from DERI. [10] [11] A superb description of the challenges in reconciling the vocabularies of different data sources is also found in the thesis by Dr. AnHai Doan, which won the 2003 ACM’s Prestigious Doctoral Dissertation Award.[12]

What all of these efforts has found is the inability to completely automate the mediation process. The current state-of-the-art is to reconcile what is largely unambiguous automatically, and then prompt analysts or subject matter experts to decide the questionable matches. These are known as “semi-automated” systems and the user interface and data presentation and workflow become as important as the underlying matching and mapping algorithms. According to the WSMX project, there is always a trade-off between how accurate these mappings are and the degree of automation that can be offered.

Also a Need for Efficient Semantic Data Stores

Once all of these reconciliations take place there is the (often undiscussed) need to index, store and retrieve these semantics and their relationships at scale, particularly for enterprise deployments. This is a topic I have addressed many times from the standpoint of scalability, more scalability, and comparisons of database and relational technologies, but it is also not a new topic in the general community.

As Stonebraker and Hellerstein note in their retrospective covering 35 years of development in databases,[13] some of the first post-relational data models were typically called semantic data models, including those of Smith and Smith in 1977[14] and Hammer and McLeod in 1981.[15] Perhaps what is different now is our ability to address some of the fundamental issues.

At any rate, this subsection is included here because of the hidden importance of database foundations. It is therefore a topic often addressed in this series.

A Partial Listing of Semantic Web Tools

In all of these areas, there is a growing, but still spotty, set of tools for conducting these semantic tasks. SemWebCentral, the open source tools resource center, for example, lists many tools and whether they interact or not with one another (the general answer is often No).[16] Protégé also has a fairly long list of plugins, but not unfortunately well organized. [17]

In the table below, I begin to compile a partial listing of semantic Web tools, with more than 50 listed. Though a few are commercial, most are open source. Also, for the open source tools, only the most prominent ones are listed (Sourceforge, for example, has about 200 projects listed with some relation to the semantic Web though most of minor or not yet in alpha release).

Tools Still Crude, Integration Not Compelling

Individually, there are some impressive and capable tools on this list. Generally, however, the interfaces are not intuitive, integration between tools is lacking, and why and how standard analysts should embrace them is lacking. In the semantic Web, we have yet to see an application of the magnitude of the first Mosaic browser that made HTML and the World Wide Web compelling.

It is perhaps likely that a similar “killer app” may not be forthcoming for the semantic Web. But it is important to remember just how entwined tools are to accelerating acceptance and growth of new standards and protocols.

This Friday brown bag leftover was first placed into the AI3 refrigerator about four years ago on June 12, 2006. It was the follow-on to last week’s Brown Bag Lunch posting. It is also the first attempt I made at assembling semantic Web- and -related tools, which has now grown into the 800+ Sweet Tools listing. No changes have been made to the original posting.