Open Semantic Framework 3.1 Released

Structured Dynamics is happy to announce the immediate availability of the Open Semantic Framework version 3.1. This new version includes a set of fixes to different components of the framework in the last few months. The biggest change is deployment of OSF using Virtuoso Open Source version 7.1.0. triple_120

We also created a new API for Clojure developers called: clj-osf. Finally we created a new Open Semantic Framework web portal that better describes the project and is hopefully easier to use and more modern.

Quick Introduction to the Open Semantic Framework

What is the Open Semantic Framework?

The Open Semantic Framework (OSF) is an integrated software stack using semantic technologies for knowledge management. It has a layered architecture that combines existing open source software with additional open source components. OSF is designed as an integrated content platform accessible via the Web, which provides needed knowledge management capabilities to enterprises. OSF is made available under the Apache 2 license.

OSF can integrate and manage all types of content – unstructured documents, semi-structured files, spreadsheets, and structured databases – using a variety of best-of-breed data indexing and management engines. All external content is converted to the canonical RDF data model, enabling common tools and methods for tagging and managing all content. Ontologies provide the schema and common vocabularies for integrating across diverse datasets. These capabilities can be layered over existing information assets for unprecedented levels of integration and connectivity. All information within OSF may be powerfully searched and faceted, with results datasets available for export in a variety of formats and as linked data.

A new Open Semantic Framework website

The OSF 3.1 release also triggered the creation of a new website for the project. We wanted something leaner and more modern and that is what I think we delivered. We also reworked the content, we wrote about a series of usecases 1 2 3 4 5 6 and we better aggregated and presented information for each web service endpoint.

A new OSF sandbox

We also created an OSF sandbox where people can test each web service endpoint and test how each functionality works. All of the web services are open to users. The sandbox is not meant to be stable considering that everybody have access to all endpoints. However, the sandbox server will be recreated on a periodic basis. If the sandbox is totally broken and users experiment issues, they can always request a re-creation of the server directly on the OSF mailing list.

Each of the web service pages on the new OSF portal has a Sandbox section where you see some code examples of how to use the endpoint and how to send requests to the sandbox. Here are the instructions to use the sandbox server.

A new OSF API for Clojure: clj-osf

The OSF release 3.1 also includes a new API for Clojure developers: clj-osf.

clj-osf is a Domain Specific Language (DSL) that should lower the threshold to use the Open Semantic Framework.

To use the DSL, you only have to configure your application to use a specific OSF endpoint. Here is an example of how to do this for the Sandbox server:

;; Define the OSF Sandbox credentials (or your own):
(require '[clj-osf.core :as osf])

(osf/defosf osf-test-endpoint {:protocol :http
                               :domain ""
                               :api-key "EDC33DA4D977CFDF7B90545565E07324"
                               :app-id "administer"})

(osf/defuser osf-test-user {:uri ""})

Then you can send simple OSF web service queries. Here is an example that sends a search query to return records of type foaf:Person that also match the keyword “bob”:

(require '[ :as search])

 (search/query "bob")
 (search/type-filters [""]))

A complete set of clj-osf examples is available on the OSF wiki.

Finally the complete clj-osf DSL documentation is available here.

A community effort

This new release of the OSF Installer is another effort of the growing Open Semantic Framework community. The upgrade of the installer to deploy the OSF stack using Virtuoso Open Source version 7.1.0 has been created by William (Bill) Anderson.

Deploying a new OSF 3.1 Server

Using the OSF Installer

OSF 3.1 can easily be deployed on a Ubuntu 14.04 LTS server using the osf-installer application. It can easily be done by executing the following commands in your terminal:

mkdir -p /usr/share/osf-installer/

cd /usr/share/osf-installer/


chmod 755


./osf-installer --install-osf -v

Using a Amazon AMI

If you are an Amazon AWS user, you also have access to a free AMI that you can use to create your own OSF instance. The full documentation for using the OSF AMI is available here.

Upgrading Existing Installations

Existing OSF installations can be upgraded using the OSF Installer. However, note that the upgrade won’t deploy Virtuoso Open Source 7.1.0 for you. All the code will be upgraded, but Virtuoso will remain the version you were last using on your instance. All the code of OSF 3.1 is compatible with previous versions of Virtuoso, but you won’t benefit the latest improvements to Virtuoso (in terms of performances) and its latest SPARQL 1.1 implementations. If you want to upgrade Virtuoso to version 7.1.0 on an existing OSF instance you will have to do this by hands.

To upgrade the OSF codebase, the first thing is to upgrade the installer itself:

# Upgrade the OSF Installer

Then you can upgrade the components using the following commands:

# Upgrade the OSF Web Services
./usr/share/osf-installer/osf --upgrade-osf-web-services="3.1.0"

# Upgrade the OSF WS PHP API
./usr/share/osf-installer/osf --upgrade-osf-ws-php-api="3.1.0"

# Upgrade the OSF Tests Suites
./usr/share/osf-installer/osf --upgrade-osf-tests-suites="3.1.0"

# Upgrade the Datasets Management Tool
./usr/share/osf-installer/osf --upgrade-osf-datasets-management-tool="3.1.0"

# Upgrade the Data Validator Tool
./usr/share/osf-installer/osf --upgrade-osf-data-validator-tool="3.1.0"

clj-turtle: A Clojure Domain Specific Language (DSL) for RDF/Turtle

Some of my recent work leaded me to heavily use Clojure to develop all kind of new capabilities for Structured Dynamics. The ones that knows us, knows that every we do is related to RDF and OWL ontologies. All this work with Clojure is no exception.

Recently, while developing a Domain Specific Language (DSL) for using the Open Semantic Framework (OSF) web service endpoints, I did some research to try to find some kind of simple Clojure DSL that I could use to generate RDF data (in any well-known serialization). After some time, I figured out that no such a thing was currently existing in the Clojure ecosystem, so I choose to create my simple DSL for creating RDF data.

The primary goal of this new project was to have a DSL that users could use to created RDF data that could be feed to the OSF web services endpoints such as the CRUD: Create or CRUD: Update endpoints.

What I choose to do is to create a new project called clj-turtle that generates RDF/Turtle code from Clojure code. The Turtle code that is produced by this DSL is currently quite verbose. This means that all the URIs are extended, that the triple quotes are used and that the triples are fully described.

This new DSL is mean to be a really simple and easy way to create RDF data. It could even be used by non-Clojure coder to create RDF/Turtle compatible data using the DSL. New services could easily be created that takes the DSL code as input and output the RDF/Turtle code. That way, no Clojure environment would be required to use the DSL for generating RDF data.


For people used to Clojure and Leinengen, you can easily install clj-turtle using Linengen. The only thing you have to do is to add Add [clj-turtle "0.1.3"] as a dependency to your project.clj.

Then make sure that you downloaded this dependency by running the lein deps command.


The whole DSL is composed of simply six operators:

  • rdf/turtle
    • Used to generate RDF/Turtle serialized data from a set of triples defined by clj-turtle.
  • defns
    • Used to create/instantiate a new namespace that can be used to create the clj-turtle triples
  • rei
    • Used to reify a clj-turtle triple
  • iri
    • Used to refer to a URI where you provide the full URI as an input string
  • literal
    • Used to refer to a literal value
  • a
    • Used to specify the rdf:type of an entity being described


Working with namespaces

The core of this DSL is the defns operator. What this operator does is to give you the possibility to create the namespaces you want to use to describe your data. Every time you use a namespace, it will generate a URI reference in the triple(s) that will be serialized in Turtle.

However, it is not necessary to create a new namespace every time you want to serialize Turtle data. In some cases, you may not even know what the namespace is since you have the full URI in hands already. It is why there is the iri function that let you serialize a full URI without having to use a namespace.

Namespaces are just shorthand versions of full URIs that mean to make your code cleaner an easier to read and maintain.

Syntactic rules

Here are the general syntactic rules that you have to follow when creating triples in a (rdf) or (turtle) statement:

  1. Wrap all the code using the (rdf) or the (turtle) operator
  2. Every triple need to be explicit. This means that every time you want to create a new triple, you have to mention the subject, predicate and the object of the triple
  3. A fourth “reification” element can be added using the rei operator
  4. The first parameter of any function can be any kind of value: keywords, strings, integer, double, etc. They will be properly serialized as strings in Turtle.

Strings and keywords

As specified in the syntactic rules, at any time, you can use a string, a integer, a double a keyword or any other kind of value as input of the defined namespaces or the other API calls. You only have to use the way that is more convenient for you or that is the cleanest for your taste.

More about reification

Note: RDF reification is quite a different concept than Clojure’s reify macro. So carefully read this section to understand the meaning of the concept in this context.

In RDF, reifying a triple means that we want to add additional information about a specific triple. Let’s take this example:

  (foo :bar) (iron :prefLabel) (literal "Bar"))

In this example, we have a triple that specify the preferred label of the :bar entity. Now, let’s say that we want to add “meta” information about that specific triple, like the date when this triple got added to the system for example.

That additional information is considered the “fourth” element of a triple. It is defined like this:

    (foo :bar) (iron :prefLabel) (literal "Bar") (rei
                                                   (foo :date) (literal "2014-10-25" :type :xsd:dateTime)))

What we do here is to specify additional information regarding the triple itself. In this case, it is the date when the triple got added into our system.

So, reification statements are really “meta information” about triples. Also not that reification statements doesn’t change the semantic of the description of the entities.


Here is a list of examples of how this DSL can be used to generate RDF/Turtle data:

Create a new namespace

The first thing we have to do is define the namespaces we will want to use in our code.

(defns iron "")
(defns foo "")
(defns owl "")
(defns rdf "")
(defns xsd "")

Create a simple triple

The simplest example is to create a simple triple. What this triple does is to define the preferred label of a :bar entity:

  (foo :bar) (iron :prefLabel) (literal "Bar"))


<> <> """Bar""" .

Create a series of triples

This example shows how we can describe more than one attribute for our bar entity:

  (foo :bar) (a) (owl :Thing)
  (foo :bar) (iron :prefLabel) (literal "Bar")
  (foo :bar) (iron :altLabel) (literal "Foo"))


<> <> <> .
<> <> """Bar""" .
<> <> """Foo""" .

Note: we prefer having one triple per line. However, it is possible to have all the triples in one line, but this will produce less readable code:

Just use keywords

It is possible to use keywords everywhere, even in (literals)

  (foo :bar) (a) (owl :Thing)
  (foo :bar) (iron :prefLabel) (literal :Bar)
  (foo :bar) (iron :altLabel) (literal :Foo))


<> <> <> .
<> <> """Bar""" .
<> <> """Foo""" .

Just use strings

It is possible to use strings everywhere, even in namespaces:

  (foo "bar") (a) (owl "Thing")
  (foo "bar") (iron :prefLabel) (literal "Bar")
  (foo "bar") (iron :altLabel) (literal "Foo"))


<> <> <> .
<> <> """Bar""" .
<> <> """Foo""" .

Specifying a datatype in a literal

It is possible to specify a datatype for every (literal) you are defining. You only have to use the :type option and to specify a XSD datatype as value:

  (foo "bar") (foo :probability) (literal 0.03 :type :xsd:double))

Equivalent codes are:

  (foo "bar") (foo :probability) (literal 0.03 :type (xsd :double)))
  (foo "bar") (foo :probability) (literal 0.03 :type (iri "")))


<> <> """0.03"""^^xsd:double .

Specifying a language for a literal

It is possible to specify a language string using the :lang option. The language tag should be a compatible ISO 639-1 language tag.

  (foo "bar") (iron :prefLabel) (literal "Robert" :lang :fr))


<> <> """Robert"""@fr .

Defining a type using the an operator

It is possible to use the (a) predicate as a shortcut to define the rdf:type of an entity:

  (foo "bar") (a) (owl "Thing"))


<> <> <> .

This is a shortcut for:

  (foo "bar") (rdf :type) (owl "Thing"))

Specifying a full URI using the iri operator

It is possible to define a subject, a predicate or an object using the (iri) operator if you want to defined them using the full URI of the entity:

  (iri "") (iri " (iri


<> <> <> .

Simple reification

It is possible to reify any triple suing the (rei) operator as the fourth element of a triple:

  (foo :bar) (iron :prefLabel) (literal "Bar") (rei
                                                 (foo :date) (literal "2014-10-25" :type :xsd:dateTime)))


<> <> """Bar""" .
<rei:6930a1f93513367e174886cb7f7f74b7> <> <> .
<rei:6930a1f93513367e174886cb7f7f74b7> <> <> .
<rei:6930a1f93513367e174886cb7f7f74b7> <> <> .
<rei:6930a1f93513367e174886cb7f7f74b7> <> """Bar""" .
<rei:6930a1f93513367e174886cb7f7f74b7> <> """2014-10-25"""^^xsd:dateTime .

Reify multiple properties

It is possible to add multiple reification statements:

(foo :bar) (iron :prefLabel) (literal "Bar") (rei
                                               (foo :date) (literal "2014-10-25" :type :xsd:dateTime)
                                               (foo :bar) (literal 0.37)))


<> <> """Bar""" .
<rei:6930a1f93513367e174886cb7f7f74b7> <> <> .
<rei:6930a1f93513367e174886cb7f7f74b7> <> <> .
<rei:6930a1f93513367e174886cb7f7f74b7> <> <> .
<rei:6930a1f93513367e174886cb7f7f74b7> <> """Bar""" .
<rei:6930a1f93513367e174886cb7f7f74b7> <> """2014-10-25"""^^xsd:dateTime .
<rei:6930a1f93513367e174886cb7f7f74b7> <> """0.37""" .

Using clj-turtle with clj-osf

clj-turtle is meant to be used in Clojure code to simplify the creation of RDF data. Here is an example of how clj-turtle can be used to generate RDF data to feed to the OSF Crud: Create web service endpoint via the clj-osf DSL:

[require '[clj-osf.crud :as crud])

  (crud/dataset "")
      (iri link) (a) (bibo :Article)
      (iri link) (iron :prefLabel) (literal "Some article")))

Using the turtle alias operator

Depending on your taste, it is possible to use the (turtle) operator instead of the (rdf) one to generate the RDF/Turtle code:

  (foo "bar") (iron :prefLabel) (literal "Robert" :lang :fr))


<> <> """Robert"""@fr .

Merging clj-turtle

Depending the work you have to do in your Clojure application, you may have to generate the Turtle data using a more complex flow of operations. However, this is not an issue for clj-turtle since the only thing you have to do is to concatenate the triples you are creating. You can do so using a simple call to the str function, or you can create more complex processing using loopings, mappings, etc that end up with a (apply str) to generate the final Turtle string.

    (foo "bar") (a) (owl "Thing"))
    (foo "bar") (iron :prefLabel) (literal "Bar")
    (foo "bar") (iron :altLabel) (literal "Foo")))


<> <> <> .
<> <> """Bar""" .
<> <> """Foo""" .


As you can see now, this is a really simple DSL for generating RDF/Turtle code. Even if simple, I find it quite effective by its simplicity. However, even if it quite simple and has a minimum number of operators, this is flexible enough to be able to describe any kind of RDF data. Also, thanks to Clojure, it is also possible to write all kind of code that would generate DSL code that would be executed to generate the RDF data. For example, we can easily create some code that iterates a collection to produce one triple per item of the collection like this:

(->> {:label "a"
      :label "b"
      :label "c"}
      (fn [label]
         (foo :bar) (iron :prefLabel) (literal label))))
     (apply str))

That code would generate 3 triples (or more if the input collection is bigger). Starting with this simple example, we can see how much more complex processes can leverage clj-turtle for generating RDF data.

A future enhancement to this DSL would be to add a syntactic rule that gives the opportunity to the user to only have to specify the suject of a triple the first time it is introduced to mimic the semi-colon of the Turtle syntax.

Major UMBEL Release: 1.10

After more than 2 years, we are now finally releasing a new version of the UMBEL ontology and reference concept structure. One might think that we haven’t worked on the project all that time, but it is not strictly true. umbel_logo_260_160

We did improve the mapping to external vocabularies/ontologies, we worked much on linking Wikipedia pages to the UMBEL structure, but we haven’t had time to release a new version… until now!

For people new to the ontology, UMBEL is a general reference structure of about 28,000 reference concepts, which provides a scaffolding to link and interoperate other datasets and domain vocabularies. Its main purpose is to have a coherent conceptual structure that we can use to link and interoperate unrelated data sources. But it can also be used as a conceptual structure to be used to describe information like any other ontologies.

What is new with the ontology?

The major change in UMBEL is not the structure itself, but the piece of software used to generate it. In fact, the previous system we developed for generating UMBEL was about 7 years old. It was a bit clunky and really not that easy to work with.

Based on our prior experience with UMBEL, we choose to dump it and to create a brand new UMBEL reference structure generator. This new generator has been developed in Clojure and uses the latest version of the OWL API. It makes the management of the structure much simpler, which means that it will help in releasing new UMBEL version more regularly. We also have a suite of tools to analyze the structure and to pinpoint possible issues.

Other than that, we updated the, DBpedia Ontology and Geonames Ontology mappings to UMBEL. This is a major effort undertaken by Mike for this new version. The mappings are composed of:

  • 754 rdfs:subClassOf relationships between classes and UMBEL reference concepts
  • 688 rdfs:subClassOf relationships between DBpedia Ontology classes and UMBEL reference concepts
  • 682 rdfs:subClassOf relationships between Geonames Ontology classes and UMBEL reference concepts

These new mappings will help manage data instances that use these external ontologies/schemas in a broader conceptual structure (which is UMBEL). This enables us to be able to reason over this external data using the UMBEL conceptual structure even if these external data sources didn’t originally use UMBEL to describe their data. That is one of the main features of UMBEL.

We also managed to add a few hundred UMBEL reference concepts. Most of them were added to create these new linkages with the external ontologies. Others have been added because they were improving the overall structure.

A few weeks back, we found an issue with the umbel:superClassOf assignations, which has also now been resolved in version 1.10.

In the previous versions of UMBEL, the preferred labels were not unique. There were a few hundred of the concepts that were having the same preferred labels. This was not an issue in itself, but this was not a best practice to create an ontology. We managed to remove all these non-distinct preferred labels and to make all of them unique.

We added a few skos:broader and skos:narrower relationships between some of the reference concepts. In the previous versions, all the relationships were skos:broaderTransitive and skos:narrowerTransitive properties only.

Finally we made sure that the entire UMBEL reference structure (Core + the Geo module) was absent of any inconsistencies and that it was satisfiable.

What is new with the portal and web services?

This new version of UMBEL also led us to create a few new features to the UMBEL website. The most apparent feature is the new External Linkage section that may appear at the top of a reference concept page (obviously, it will not appear if there are no external links for a given reference concept). This section shows you the linkage between the UMBEL reference concept and other external classes:


Another feature that you will notice on this screenshot is the Core blue tag at the right of the URI of the reference concept. This tag is used to tell you from where the reference concept is coming. Another tag that you may encounter is the green Geo tag, which tells you that the reference concept comes from the UMBEL Geo module. The same tags appear in the search resultsets:


What is next?

Because UMBEL is an ontology, by nature it will always evolve over time. Things change, and the way we see the World can always improve.

For the next version of UMBEL, we will analyze the entire UMBEL reference concept structure using different algorithms, heuristics and other techniques to analyze the conceptual structure and to find conceptual gaps in it. The goal of this analysis is to tighten the structure, to have a better conceptual hierarchy and a more fine-grained one.

Other things we want to do in other coming versions are to improve the Super Types structure of UMBEL. As you may know, many of the Super Types are non disjoint because some of the concepts belong to multiple Super Type classes. What we want to do here is to create new Super Types classes that are the intersection between two, or more, Super Types that will be used to categorize these concepts that belong to multiple Super Types. That way, we will end-up with a better classification of the UMBEL reference concepts from a Super Types standpoint.

Another thing we want to do related to the UMBEL web services is to update them such that you can query the linkage to the external ontologies. For now, you can see the linkage when querying the sub-classes and super-classes of a reference concept. But you cannot query the web services this way: give me all the sub-classes-of the class, for example.

As you can see, the UMBEL ontology and web services will continue to evolve over time to enable new ways to leverage the conceptual structure and external data sources.

This blog is a regularly updated collection of my thoughts, tips, tricks and ideas about data mining, data integration, data publishing, the semantic Web, my researches and other related software development.

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