Tag Archive for 'semanticweb'

New UMBEL Concept Noun Tagger Web Service & Other Improvements

Last week, we released the UMBEL Concept Plain Tagger web service endpoint. Today we are releasing the UMBEL Concept Noun Tagger. umbel_ws

This noun tagger uses UMBEL reference concepts to tag an input text, and is based on the plain tagger, except as noted below.

The noun tagger uses the plain labels of the reference concepts as matches against the nouns of the input text. With this tagger, no manipulations are performed on the reference concept labels nor on the input text except if you specify the usage of the stemmer. Also, there is NO disambiguation performed by the tagger if multiple concepts are tagged for a given keyword.

Intended Users

This tool is intended for those who want to focus on UMBEL and do not care about more complicated matches. The output of the tagger can be used as-is, but it is intended to be the input to more sophisticated reference concept matching and disambiguation methods. Expect additional tagging methods to follow.

Stemming Option

This web service endpoint does have a stemming option. If the option is specified, then the input text will be stemmed and the matches will be made against an index where all the preferred and alternative labels have been stemmed as well. Then once the matches occurs, the tagger will recompose the text such that unstemmed versions of the input text and the tagged reference concepts are presented to the user.

Depending on the use case. users may prefer turning on or off the stemming option on this web service endpoint.

The Web Service Endpoint

The web service endpoint is freely available. It can return its resultset in JSON, Clojure code or EDN (Extensible Data Notation).

This endpoint will return a list of matches on the preferred and alternative labels of the UMBEL reference concepts that match the noun tokens of an input text. It will also return the number of matches and the position of the tokens that match the concepts.

The Online Tool

We also provide an online tagging tool that people can use to experience interacting with the web service.

The results are presented in two sections depending on whether the preferred or alternative label(s) were matched. Multiple matches, either by concept or label type, are coded by color. Source words with matches and multiple source occurrences are ranked first; thereafter, all source words are presented alphabetically.

The tagged concepts can be clicked to have access to their full description.


Other UMBEL Website Improvements

We also did some more improvements to the UMBEL website.

Search Autocompletion Mode

First, we created a new autocomplete option on the UMBEL Search web service endpoint. Often people know the concept they want to look at, but they don’t want to go to a search results page to select that concept. What they want is to get concept suggestions instantly based on the letters they are typing in a search box.

Such a feature requires a special kind of search which we call an “autocompletion search”. We added that special mode to the existing UMBEL search web service endpoint. Such a search query takes about 30ms to process. Most of that time is due to the latency of the network since the actual search function takes about 0.5 millisecond the complete.

To use that new mode, you only have to append /autocomplete to the base search web service endpoint URL.

Search Autocompletion Widget

Now that we have this new autocomplete mode for the Search endpoint, we also leveraged it to add autocompletion behavior on the top navigation search box on the UMBEL website.

Now, when you start typing characters in the top search box, you will get a list of possible reference concept matches based on the preferred labels of the concepts. If you select one of them, you will be redirected to their description page.


Tagged Concepts Within Concept Descriptions

Finally, we improved the quality of the concept description reading experience by linking concepts that were mentioned in the descriptions to their respective concept pages. You will now see hyperlinks in the concept descriptions that link to other concepts.


New UMBEL Web Services

umbel_logo_260_160I am happy to announce the immediate availability of a brand new UMBEL website and a new set of eight UMBEL web services.

UMBEL (Upper Mapping and Binding Exchange Layer) is a general reference structure of 28,000 concepts, which provides a scaffolding to link and interoperate other datasets and domain vocabularies. This project is now six years old.

I would recommend that your read Mike’s blog post about this new release if you want more background information about UMBEL and to have a better understanding of how it can help you integrate, manage, publish and reason over your data.

In this blog post, I will focus on the technical aspects of this new web site and the new set of web service endpoints.

Toward a Better Web Experience

The Web is changing fast. Techniques for developing web sites are constantly and quickly evolving. People uses all kind of devices with different sizes of screens to consume Web content. Websites are more and more responsive by their clever architecture design, and their simpler user interfaces. This is the kind of website we wanted to create for the new UMBEL website.

Clojure Web Service Endpoints at the Core

The core of the new UMBEL website are the new web services. As soon as you are performing a search, or looking at the description of a reference concept or a super type, your browser is making a series of asynchronous queries to the UMBEL web service endpoints.

The average query time is about 60 milliseconds for any of the web service query. This means that a web page is fully loaded within 300 to 500 milliseconds where most of the time is spent downloading the web files (the JavaScript, CSS, HTML and image files) and not querying the web service endpoints. Bearing in mind that the website currently run on a small server with a single core and 1.8G of RAM, these are really good performance figures.

We are initially releasing 8 web service endpoints (with more to follow). They have been created to help developers quickly start using the reference structure without having to download and deploy the entire structure on their own infrastructure. The 8 web services are:

  1. Search concept
  2. Get concept
  3. Get super type
  4. Get narrower concepts
  5. Get broader concepts
  6. Get sub-classes
  7. Get super-classes
  8. Degree

All these web services are calculating the results at runtime. For example, if you want to find the degree between two reference concepts, then the degree is calculated at runtime. It is the same for all the web services that does inferencing like the Get narrower concepts or Get broader concepts web service endpoints.

What we did to get these excellent performance measures is to use Clojure as the programming language and framework to develop the new web service endpoints. Then we define the UMBEL structure as Clojure code.

Each web service endpoint is comprised of simple pure functions that perform calculations on the UMBEL graph of 28 000 nodes. None of the functions are more than 30 lines of code (per endpoint) which greatly simplifies their creation, debugging, maintenance and optimization. Then we use contributed libraries such as Ring and Compojure to manage the creation of the web service endpoints, and Clucy/Lucene for the search engine.

The web services can easily be scaled horizontally since everything is self contained in a single WAR file that can be deployed on new servers in a few clicks. Then the new servers can participate into a cluster of UMBEL web service servers.

Another advantage of using this technology stack for creating the UMBEL web service endpoints is that UMBEL is not just a reference structure nor a set of web service endpoints. It is also a programming API that could be used in any Clojure or Java applications. The UMBEL reference structure, along with all the functions that uses it will be available as a JAR file. That way, UMBEL become portable. It could be used as a library in any JVM application without requiring it to send queries to external web services, or to create complex stacks to deploy and use the UMBEL reference structure in different applications.

Bootstrap as the HTML/CSS/JavaScript Framework

The previous UMBEL website was using Drupal 6. For the ones that were using it, it was sometimes clunky, less responsive and more heavy weight. The problem is that we were not requiring a full CMS system for developing a simple UMBEL website that is only informational.

We wanted a responsive experience for the UMBEL user. We wanted to have the fastest experience possible and we wanted to have this experience on any kind of device: desktop computers, tables, mobile phones, etc.

This is why we choose to develop the new UMBEL website using Twitter’s Bootstrap HTML, CSS and JavaScript framework. This is a framework that anybody can use to quickly create simple, beautiful and modern websites. It uses a grid system to create responsive user interfaces on any kind of device (screen size). That way, UMBEL users have the same kind of experience whether they are using a normal desktop screen, a tablet of their mobile phone.

This choice enabled us to create a simple, modern, nice looking and responsive website for UMBEL.

Introduction to the UMBEL Web Services

Now let’s take the time to introduce each of the UMBEL web service endpoint. The first thing to know is that the UMBEL web service endpoints are free to use, have no usage limits and there is no throttling.

Search Concept Web Service

The Search Web service is used to find UMBEL reference concepts that match a search string. This is the primary tool for finding available concepts in the reference structure. It supports the Lucene query syntax and search queries can be constrained on different fields like the preferred label, alternative labels, descriptions and URI.

Get Concept Web Service

The Get Concept Web service is used to get the full description of a UMBEL Reference Concept. By querying this Web service endpoint, you will get the preferred label, all the alternative labels (namely, the items in the semset), the sub/super classes of the concept, the broader/narrower concepts and the description of that concept.

This is the Web service endpoint that should be used to get the direct relationships with any other reference concept.

Reference concepts descriptions are available as N-Triples, RDF+XML, structJSON or Clojure code.

Get Super Type Web Service

The Get Super Type Web service is used to get the full description of a UMBEL Super Type. By querying this Web service endpoint, you will get the preferred label, all of the alternative labels, the description, and the disjoint super types of a target super type.

Get Narrower Concept Web Service

The Get Narrower Concept Web service is used to get the list of all the narrower concepts of a given reference concept. This processing is done by inference, which means that if A -> B -> C are narrower concepts, then the narrower concepts of A are both B and C, which is what will be returned by the endpoint.

Get Broader Concept Web Service

The Get Broader Concept Web service is used to get the list of all the broader concepts for a given reference concept. This processing is done by inference, which means that if A -> B -> C are broader concepts, then the broader concepts of C are both A and B, which is thus what will be returned by the endpoint.

The broader reference concepts do not include the super type as their top concept (use the Get Super-Class-Of web service endpoint for that).

Get Sub Classes Web Service

The Get Sub Classes Web service is used to get the list of all the sub classes of a given reference concept. This processing is done by inference, which means that if A -> B -> C are sub classes, then the sub classes of A are both B and C, which is what will be returned by the endpoint.

Get Super Classes Web Service

The Get Super Classes Web service is used to get the list of all the super classes of a given reference concept. This processing is done by inference, which means that if A -> B -> C are super classes, then the super classes of C are both A and B, which is what will be returned by the endpoint.

The super classes do include the super types as their top concept (use the Get Super-Class-Of web service endpoint for that).

Degree Web Service

The Degree Web service is used to get the degree (measure of distance) between two UMBEL reference concepts by following the path of a transitive property.


This new website along with these new web service endpoints are still using the UMBEL reference structure version 1.05. However, in the coming month or two, a new version of the reference structure should be released. The structure itself won’t change much except the introduction of a few new reference concepts. But new mechanisms (mostly related to attributes) will be introduced. It will also come with a brand new mapping with external data schemas and data sources such as Schema.org, Wikipedia, etc.

On my side, I will start writing more about UMBEL. New web service endpoints will be released over time. The API available to use, manage and leverage the structure will constantly expand.

On the other side, I will write about how the UMBEL reference structure can be used, how it can be leveraged to integrate data sources, to expend search queries, etc.

Revision of Serializing RDF Data as Clojure Code Specification

In my previous blog post RDF Code: Serializing RDF Data as Clojure Code I did outline a first version of what a RDF serialization could look like if it would be serialized using Clojure code. However, after working with this proposal for two weeks, I found a few issues with the initial assumptions that I made that turned out to be bad design decisions in terms of Clojure code.

This blog post will discuss these issues, and I will update the initial set of rules that I defined in my previous blog post. Going forward, I will use the current rules as the way to serialize RDF data as Clojure code.

What Was Wrong

After two weeks of using the previous set of serializations rules and developing all kind of functions that uses that codes in the context of UMBEL graph traversal and analysis I found the following issues:

  1. Keys and values should be Vars
  2. Ontologies should all be in the same namespace (and not in different namespaces)
  3. The prefix/entity separator for the RDF resources should be a colon and not a slash

These are the three serialization rules that changed after working with the previous version of the proposal. Now, let’s see what caused these changes to occur.

Keys and Values as Vars

The major change is that when we serialize RDF data as Clojure map structures, the keys, and values that are not strings, should be Vars.

There are three things that I didn’t properly evaluated when I first outlined the specification:

  1. The immutable nature of the Clojure data structures
  2. The dependency between ontologies
  3. The non-cyclical namespaces dependency rule imposed by Clojure

In the previous proposal, every RDF property were Clojure functions and they were also the keys of the Clojure maps that were used to serialize the RDF resources. That was working well. However, there was a side effect to this decision: everything was fine until the function’s internal ID changed.

The issue here is that when we work with Clojure maps, we are working with immutable data structures. This means that even if I create a RDF record like this:

(def mike {uri "http://foo.com/datasets/people/mike"
           rdf/type foaf/+person
           iron/pref-label "Mike"
           foaf/knows ["http://foo.com/datasets/people/fred"]})

And that somehow, in the compilation process the RDF ontology file get re-compiled, then the internal ID of the rdf/type property (function) will change. That means that if I create another record like this:

(def mike-2 {uri "http://foo.com/datasets/people/mike"
             rdf/type foaf/+person
             iron/pref-label "Mike"
             foaf/knows ["http://foo.com/datasets/people/fred"]})

that uses the same rdf/type function, then these two records would refer to different rdf/type functions since it changed between the time I created the mike and the mike-2 resources. That may not look like an issue since both functions does exactly the same thing. However, this is an issue since for multiple tasks to manipulate and query RDF data rely on comparing these keys (so, these functions). That means that unexpected behaviors can happen and may even looks like random.

The issue here was that we were not referring to the Var that point to the function, but the function itself. By using the Var as the keys and values of the map, then we fix this inconsistency issue. What happens is that all the immutable data structure we are creating are referring to the Var which point to the function. That way, when we evaluate the Var, we will get reference to the same function whatever when it got created (before or after the creation of mike and/or mike-2). Here is what the mike records looks like with this modification:

(def mike {#'uri "http://foo.com/datasets/people/mike"
           #'rdf/type #'foaf:+person
           #'iron/pref-label "Mike"
           #'foaf/knows ["http://foo.com/datasets/people/fred"]})

We use the #' macro reader to specify that we use the Var as the key and values of the map and not the actual functions or other values referenced by that Var.

The second and third issues I mentioned are tightly related. In a RDF & OWL world, there are multiple examples of ontologies that re-use external ontologies to describe their own semantic. There are cases where an ontology A use classes and properties from an ontology B and where the ontology B use classes and properties from an ontology A. They cross-use each other. Such usage cycles exists in RDF & OWL and are not that uncommon neither.

The problem with that is that at first, I was considering that each OWL ontologies that were to be defined as Clojure code would be in their own Clojure namespace. However, if you are a Clojure coder, you can envision the issue that is coming: if two ontologies cross-use each other, then it means that you have to create a namespace dependency cycles in your Clojure code… and you know that this is not possible because this is restricted by the compiler. This means that everything works fine until this happens.

To overcome that issue, we have to consider that all the ontologies belong to the same namespace (like clojure.core). However, in my next blog post that will focus on these ontologies description I will show how we can split the ontologies in multiple files while keeping them in the same namespace.

Now that we should have all the ontologies in the same namespace, and that we cannot use the namespaced symbols of Clojure anymore, I made the decision to use the more conventional way to write namespaced properties and classes in other RDF serializations which is to delimit the ontology’s prefix with a colon like that:

(def mike {#'uri "http://foo.com/datasets/people/mike"
           #'rdf:type #'foaf:+person
           #'iron:pref-label "Mike"
           #'foaf:knows ["http://foo.com/datasets/people/fred"]})

Revision of the RDF Code Rules

Now let’s revise the set of rules that I defined in the previous blog post:

  1. A RDF resource is defined as a Clojure map where:
    1. Every key is a Var that point to a function
    2. Every value is a:
      1. string
        1. A string is considered a literal if the key is a owl:DatatypeProperty
        2. A string is considered a URI if the key is a owl:ObjectProperty
      2. map
        1. A map represent a literal if the value key is present
        2. A map represent a reference to another resource if the uri key is present
        3. A map is invalid if it doesn’t have a uri nor a value key
      3. vector
        1. A vector refer to multiple values. Values of a vector can be stringsmaps, symbols or Vars
      4. symbol
        1. A symbol can be created to simplify the serialization. However, these symbols have to reference a string or a var object
      5. var
        1. A var reference another entity

In addition to these rules, there are some more specific rules such as:

  1. The value of a uri key is always a string
  2. If the #’rdf:type key is not defined for a resource, then the resource is considered to be of type #’owl:+thing (since everything is at least an instance of the owl:Thing class in OWL)

Finally, there are two additional classes and datatypes creation conventions:

  1. The name of the classes starts with a + sign, like: #’owl:+thing
  2. The name of the datatypes starts with a * sign, like: #’xsd:*string

As you can see, the rules that govern the serialization of RDF data as Clojure code are minimal and should be simple to understand for someone who is used to Clojure code and that tried to write a few resource examples using this format. Now, let’s apply these rules with a series of examples.

Note 1: in the examples of this blog post, I am referring to Vars like #’uri, #’value, #’lang, #’datatype, etc. To make the rules simpler to read and understand, consider that these Vars are defined in the user‘s namespace. However, they are vars that are defined in the rdf.core namespace that will be made publicly available later.

Note 2: All the properties and classes resource Vars have been defined in the same namespace. They should be included with :require or :use like (:use [ontologies.core]) from the ns function of the Clojure source code file that define this RDF resource. We will discuss about these namespaces in a subsequent blog post.

Revision of Serializing RDF Code in N-Triples

The serialize-ntriples function got modified to comply with the new set of rules:

(declare serialize-ntriples-map-value serialize-ntriples-string-value is-datatype-property?)

(defn serialize-ntriples
  (let [n3 (atom "")
        iri (get resource #'rdf.core/uri)]
    (doseq [[property prop-vals] resource]
      (let [property-uri (get (meta property) #'rdf.core/uri)]
        ; Don't do anything with the "uri" key
        (if (not= property #'rdf.core/uri)
          (if (vector? prop-vals)
            ; Here the value is a vector of maps or values
            (doseq [v prop-vals]
              (let [val (if (var? v) @v v)]
                (if (map? val)
                  ; The value of the vector is a map
                  (reset! n3 (str @n3 (serialize-ntriples-map-value val iri property-uri)))
                  (if (string? val)
                    ; The value of the vector is a string
                    (reset! n3 (str @n3 (serialize-ntriples-string-value val iri property-uri property)))))))
            (let [vals (if (var? prop-vals) @prop-vals prop-vals)]
              (if (map? vals)
                ; The value of the property is a map
                (reset! n3 (str @n3 (serialize-ntriples-map-value vals iri property-uri)))
                (if (string? vals)
                  ; The value of the property is some kind of literal
                  (reset! n3 (str @n3 (serialize-ntriples-string-value vals iri property-uri property))))))))))

(defn- serialize-ntriples-map-value
  [m iri property-uri]
  (if (not (nil? (get m #'rdf.core/uri)))
    ; The value is a reference to another resource
    (format "<%s> <%s> <%s> .\n" iri property-uri (get m #'rdf.core/uri))
    (if (not (nil? (get m #'rdf.core/value)))
      ; The value is some kind of literal
      (let [value (get m #'rdf.core/value)
            lang (if (get m #'rdf.core/lang) (str "@" (get m #'rdf.core/lang)) "")
            datatype (if (get m #'rdf.core/datatype) (str "^^<" (get (deref (get m #'rdf.core/datatype)) #'rdf.core/uri) ">") "")]
        (format "<%s> <%s> \"\"\"%s\"\"\"%s%s .\n" iri property-uri value lang datatype))
      (if (string? m)
        ; The value of the sector is some kind of literal
        (format "<%s> <%s> \"\"\"%s\"\"\" .\n" iri property-uri m)))))

(defn- serialize-ntriples-string-value
  [s iri property-uri property]
  ; The value of the vector is a string
  (if (true? (is-datatype-property? property))
    ; The property referring to this value is a owl:DatatypeProperty
    (format "<%s> <%s> \"\"\"%s\"\"\" .\n" iri property-uri s)
    ; The property referring to this value is a owl:ObjectProperty
    (format "<%s> <%s> <%s> .\n" iri property-uri s)))

(defn is-datatype-property?
  (if (= (-> property
             (get #'ontologies.core/rdf:type)
             (get #'rdf.core/uri))
         (-> #'ontologies.core/owl:+datatype-property
             (get #'rdf.core/uri)))
    (eval true)
    (eval false)))

Serializing a RDF Resource

Now let’s serialize a new RDF resource using the new set of rules:

(def fred {#'uri "http://foo.com/datasets/people/fred"
           #'rdf:type [#'foaf:+person #'owl:+thing]
           #'iron:pref-label "Fred"
           #'iron:alt-label {#'value "Frederick"
                             #'lang "en"}
           #'foaf:skypeID {#'value "frederick.giasson"
                           #'datatype #'xsd/*string}
           #'foaf:knows [{#'uri "http://foo.com/datasets/people/bob"}

One drawback with these new rules (even if essential) is that they complexify the writing of the RDF resources because of the (heavy) usage of the #' macro.

However, on the other hand, they may looks like more familiar to people used to RDF serializations because of the usage of the colon instead of the slash to split the ontology prefix with the ending of the URI.

What we have above, is how the RDF data is represented in Clojure. However, there is a possibility to make this serialization less compact by creating a macro that would change the input map and automatically inject the usage of the #' reader macro into the map structures that define the RDF resources.

Here is the r macro (“r” stands for Resource) that does exactly this:

(defmacro r
  (-> (walk/postwalk
       (fn [x]
         (if (and (symbol? x) (-> x
           `(var ~x)

Then you can use it to define all the RDF resources you want to create:

(def fred (r {uri "http://foo.com/datasets/people/fred"
               rdf:type [foaf:+person owl:+thing]
               iron:pref-label "Fred"
               iron:alt-label {value "Frederick"
                               lang "en"}
               foaf:skypeID {value "frederick.giasson"
                             datatype  xsd/*string}
               foaf:knows [{uri "http://foo.com/datasets/people/bob"}

That structure is equivalent to the other one because the r macro will add the #' reader macro calls to change the input map before creating the resource’s Var.

By using the r macro, we can see that the serialization is made much simpler, and that at the end, it is more natural to people used to other RDF serializations.


I used the initial specification in the context of creating a new series of web services for the UMBEL project. This heavy usage of this kind of RDF data leaded to discover the issues I covered in this blog post. Now that these issues are resolved, I am confident that we can move forward in the series of blog posts that covers how (and why!) using Clojure code to serialize RDF data.

The next blog post will cover how to manage the ontologies used to instantiate these RDF resources.

This blog is a regularly updated collection of my thoughts, tips, tricks and ideas about my semantic Web researches and related software development.

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