Tag Archive for 'data'

Open Semantic Framework 3.0.1 Released

I am happy to announce the immediate availability of the Open Semantic Framework version 3.0.1. This new version includes a set of fixes to different components of the framework in the last few months.The biggest addition is the new OSF Installer which will deploy OSF on Ubuntu LTS 14.04 servers. triple_120

A Community Effort

This new release of the OSF Installer is an effort of the growing Open Semantic Framework community. The upgrade of the installer to deploy the OSF stack on the lastest Ubuntu Long Term Support (LTS) version 14.04 has been created by William (Bill) Anderson.

Samar Acharya also suggested to decouple the PHP5 Debian packages from the core OSF Installer repository to cope with the support of future version of Ubuntu or other Linux distributions. This led to the creation of the new OSF-Installer-Ext repository, which is only used to host these distribution specific files like the PHP5 Debian files.

Upgrading Existing Installations

Existing OSF installations can be upgraded using the OSF Installer. The first thing is to upgrade the installer itself:

# Upgrade the OSF Installer
./usr/share/osf-installer/upgrade.sh

Then you can upgrade the components using the following commands:

# Upgrade the OSF Web Services
./usr/share/osf-installer/osf --upgrade-osf-web-services="3.0.1"

# Upgrade the OSF WS PHP API
./usr/share/osf-installer/osf --upgrade-osf-ws-php-api="3.0.1"

# Upgrade the OSF Tests Suites
./usr/share/osf-installer/osf --upgrade-osf-tests-suites="3.0.1"

# Upgrade the Datasets Management Tool
./usr/share/osf-installer/osf --upgrade-osf-datasets-management-tool="3.0.1"

# Upgrade the Data Validator Tool
./usr/share/osf-installer/osf --upgrade-osf-data-validator-tool="3.0.1"

Big Structures: Where the Semantic Web Meets Artificial Intelligence

Mike Bergman just published the second part1 of his series of blog posts that summarize the evolution of the Semantic Web in the last decade, and how our experience of the last 7 years of research in that field has led to these observations.

The second part of that series is: Big Structure: At The Nexus of Knowledge Bases, the Semantic Web and Artificial Intelligence.

He continues to outline some issues with the Semantic Web, but more importantly how it fits in a much broader ecosystem, namely KBAI (Knowledge Based AI). He explains the difference between data integration and data interoperability and how these problems could benefit leveraging a sub-set of the Artificial Intelligence domain related to data interoperability:


ai_data_interoperability
These two blog posts set the foundation and the direction where Structured Dynamics is heading in the coming years and where we will focus our research projects and how we will help our clients with their data integration and interoperability issues.

We welcome hearing from you!

New UMBEL Concept Tagger Web Service

We just released a new UMBEL web service endpoint and online tool: the Concept Tagger Plain. umbel_ws

This plain tagger uses UMBEL reference concepts to tag an input text. The OBIE (Ontology-Based Information Extraction) method is used, driven by the UMBEL reference concept ontology. By plain we mean that the words (tokens) of the input text are matched to either the preferred labels or alternative labels of the reference concepts. The simple tagger is merely making string matches to the possible UMBEL reference concepts.

This tagger uses the plain labels of the reference concepts as matches against the input text. With this tagger, no manipulations are performed on the reference concept labels nor on the input text (like stemming, etc.). 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 initial input to more sophisticated reference concept matching and disambiguation methods. Expect additional tagging methods to follow (see conclusion).

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 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.

reference_concept_tagger_uiEDN and ClojureScript

An interesting thing about this user interface is that it has been implemented in ClojureScript and the data serialization exchanged between this user interface and the tagger web service endpoint is in EDN. What is interesting about that is that when the UI receives the resultset from the endpoint, it only has to evaluate the EDN code using the ClojureScript reader (cljs.reader/read-string) to consider the output of the web service endpoint as native data to the application.

No parsing of non-native data format is necessary, which makes the code of the UI simpler and makes the data manipulation much more natural to the developer since no external API is necessary.

What is Next?

This is the first of a series of tagging web service endpoints that will be released. Our intent is to release UMBEL tagging services that have different level of sophistication. Depending on how someone wants to use UMBEL, he will have access to different tagging services that he could use and supplement with their own techniques to end up with their desired results.

The next taggers (not in order) that are planned to be released are:

  • Plaintagger – no weighting or classification except by occurrence count
    • Entity plain tagger (using the Wikidata dictionary)
    • Scones plain tagger – concept + entity
  • Nountagger – with POS, only tags the nouns; generally, the preferred, simplest baselinetagger
    • Concept noun tagger
    • Entity noun tagger
    • Scones noun tagger
  • N-gramtagger – a phrase-basedtagger
    • Concept n-gram tagger
    • Entity n-gram tagger
    • Scones n-gram tagger
  • Completetagger – combinations of above with different machine learning techniques
    • Concept complete tagger
    • Entity complete tagger
    • Scones complete tagger.

So, we welcome you to try out the system online and we welcome your comments and suggestions.




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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