Portfolio
Since being founded in 2004, we have developed various complex products,
mainly in the fields of Semantic Web (Linked Data) and text analytics.
Many of our customers are high-tech companies from Europe and North America .
We have been working with some of them for many years now.
The products we have been developing are used by organisations such as HP and NASA,
as well as by pharmaceutical companies currently active in COVID-19 vaccine research.
Please find below descriptions of selected projects.
OWL ontology development software for the web
Client:
A leading UK-based supplier of ontology-driven classification and search software
Project description:
We develop a web-based system for collaborative development of ontologies and taxonomies.
The product is designed for big companies that model their domain knowledge using the Semantic Web approach. They use semantic models to develop products and to drive classification, navigation and fact extraction on their document archive. The system's features include: Semantic Web data model, scalability, efficient and elegant user interface, workflows, auditing, integration with widely used CMS systems, import/export tools.
Technologies:
Java, OSGI, Spring, TypeScript, React, Cypress, GraphQL, RDFS, OWL, SKOS, JSON-LD, Apache Jena, TopBraid, Marklogic, Allegrograph
Project size:
This is on-going work that started a few years ago and involves several software developers and testers.
Ontology-driven classification, text mining and enterprise search software
Client:
A leading UK-based supplier of ontology-driven classification and search software
Project description:
We develop a set of applications for document classification, fact extraction, navigation, and search.
They are designed for big companies interested in getting structured information out of their unstructured document archive. The classification, extraction and navigation rules are inferred from domain-specific or user-specific ontologies (created separately). The system consists of server and web applications that can be combined in many ways to solve the client's individual business needs. The features include: multiple language support, connector modules (FAST, Sharepoint, Google Search Appliance, and Apache Solr), debugging utilities, and real-time responsiveness.
Technologies:
Java, Spring, React, C/C++, RDFS, OWL, SKOS, JSON-LD, Apache Jena, TopBraid, Marklogic, Allegrograph
Project size:
This is on-going work that started a few years ago and involves several software developers and testers.
CL-JSON-LD: Common Lisp library for JSON-LD
Client:
The library is publicly available under GPLv3 to all Lisp developers. If you'd like to use the library under another licence please contact RD Projekt.
Project description:
A Common Lisp library that implements JSON-LD functionality, as described on the JSON-LD website (http://www.json-ld.org/).
Our library was inspired by and closely follows the pyld library. You can find it here: https://github.com/RDProjekt/cl-json-ld
Technologies:
Common Lisp
Project size:
This was several months worth of work for a two-person team.
Enterprise analytics and search software
Client:
A German supplier of analytical and search software
Project description:
We created a system that, given a set of structured documents of different formats, suggests appropriate transformation routines for each of them and then performs distributed processing of the document set so that the output can be used for multi-dimensional search and analytics.
First, the system extracts records from databases, CSV files, Microsoft Sharepoint servers, etc. Given an input record, it looks up the ontologies describing the data schemes and computes a set of appropriate transformation routines by matching the ontologies with transformation routine metadata. During this step, an Ontology Reasoner infers additional ontology properties to extend the set of possible transformations. Once a set of transformations is selected, an execution plan is created and then it is executed on multiple machines, connected with each other using message queues. A flexible and elegant web-based UI allows the system to be quickly customised to the customer's needs.
Technologies:
Python, Javascript, Pyramid, Mako, C++, Java, JCC, RDFS, OWL, Microsoft SharePoint
Project size:
This was an over a year's work that involved several software developers.