Latest news
May, 30 2010
Version 4.00 of the finance ontology is published.
Until financing of the ontology development is provided, no more updates are planned.
ELEMENTS
Homepage: http://www.fadyart.com Contact: info(a)fadyart.com
The finance ontology and the website pages of Eddy Vanderlinden are licensed according
Creative Commons Attribution-Share alike 2.0 Belgium license.
In a nutshell
Objective
⇓ Reduce risks
⇑ Increase operational efficiency
⇓ Reduce costs
⇑ Increase operational agility
by improving:
⇒ knowledge about products and
their production
⇒ production processes
⇒ production monitoring
⇒ production monitoring
Method
Knowledge management:
1. Collection of product- and process knowledge
2. Setup of a knowledge management system
3. Monitor and interpret generated new knowledge
4. Maintain the knowledge models
by means of an owl-format ontology.
Knowledge implementation:
1. Setup of a knowledge base
2. Build the services
3. Build the interfaces: human and soft
by means of a triple- or quad store.
Services
ý finance ontology usage (creative commons license)
ý knowledge audit
ý assistance with semantic application development
ý continuous development of the ontology
ý consulting around the ontology and its implementation
ý custom development of the ontology on specific areas
ý education on ontologies and their usage
ý organization of co-operative ontology development
Ontology development
We use ontologies as the knowledge storage and management instruments of the finance domain.
RDF and OWL ontologies are read by men and machines.
This ontology is
a good starting point
for developments in
the finance industry.
The ontology is
documented here.
Taxonomy
Ontologies use the
technique to show
specialization of
concepts
with inheritance
of properties.
Version 3.04: After opening the link, right-click on the image in the iFrame and choose 'Save As' if you want a copy.
Version 4.00: The taxonomy is too elaborated to be represented the same way.
Implementation
Find here a context scheme to situate the different contexts involved
Implementation of semantic applications requires a different methodology and technology in
- business process analysis and description
- technical analysis
- IT development
- programming
- data awareness
Here is an overview of these differences.
Eddy Vanderlinden
þ Collected during 30 years strong and weak points of service production and management.
þ Analysed the underlying causes for failure and success.
þ Listed the criteria for an optimal solution.
þ Went on a journey through alternative approaches.
þ Selected semantic technologies as the solution.
þ Advocates them with enthusiasm because of the business case and real world use cases.
þ Hates hypes.
Integration partner
We have chosen OpenLink as integration partner.
The choice was not made overnight.
OpenLink brings the ontology to life. In other words, OpenLink's Virtuoso universal server transforms knowledge into applications in a high demanding environment.
The justifications for the choice are listed here.
Courtesy
The solutions which satisfy our criteria are found in the semantic web community.
It are the technologies which those hard working people apply to web information we re-use in a controlled data environment.
Some references to the community:
Knowledge audit
- The degree of availability
- The accessibility
- The update
- The safeguard
- The application
of knowledge
on:
products
processes
procedures
risks
at different
hierarchical levels.
Financial crisis
In March 2008 by E-mail, in June 2008 by registered letter, we asked for proper action from international and national control authorities to avoid a financial disaster.
Unfortunately, end of September, the worse happened.
The finance ontology is a substantial element in avoiding the same happening in the future.
More.
Ignorance
Breaking the conspiracy for ignorance is a presentation held at several occasions.
It is the most comprehensive description of the reasons why our solution is needed.
Test it for yourself
Find out whether the solution is valid for your situation.
Modelling
The need to model information is justified in a longer dissertation.
Modelling of information can be done in many ways.
Find here an overview and resource locations on different methods.
Blog
Have a look at our blog.
Subjects of the posts are Finance, semantic technologies and application of semantic technologies in Finance.
Software development
The core application can be developed on a tested platform or on the platform of your choice.
A large community of developers is available to deliver customized front-end applications.
The choice of the means is related to balancing notably:
- requested sophistication in the the application: applets versus single widget,
- speed and performance in server communication: (lazy) load versus asynchronous communication,
- appearance of the interface: basic or aesthetic
An example is here.
Sample project
Securities handling is subject to lots of changes:
- UCITS IV EU directive on pan-European investment funds
- Eurosystem: the unified clearing and settlement system of the ECB for T2S securities
- ISO 20022 new SWIFT messages
A sample project plan is available.
Contact us for a quotation on semantic technologies developments.
Annotations
Impact
Choosing for a semantic data solution is a strategy with many impacts.
It revolutionizes the way operations are managed, performed and controlled, as well as the communication and reporting around these topics.
A listing of impacts is found in the frequently asked questions page here.
Utilities
Utilities are mainly used today in browsing the ontology.
Many are instructive
on the nature of
ontologies and
require a manual to
interpret the results.
A selection of tools can is available here.
Storage
RDF/OWL information is :
- represented as triples of subject, predicate, object. See examples
- stored in specially designed databases called triple or quad stores or;
- retrieved and handled by a dedicated language: SPARQL
The choice of the database requires balancing different parameters
like access speed, inference possibilities, reasoning engines to be
coupled, available
database servers,
communication with the
user interface, ...
Read more on our tests here.
Risk management
Operational risks
The reduction of operational risks is treated in the presentation "Breaking the conspiracy for ignorance" (see earlier).
External risks
This page is about how risks profiles are integrated in the ontology.
Universal methodology
Asserted and inferred knowledge
Information accessible by men and machines
Use case
The finance ontology supports, in the field of finance transactions and securities handling, the management, control of- and reporting over products, processes and procedures.
Thesaurus
An ontology contains synonyms, a lexicon, concept descriptions, properties and inverse properties, relations,...
You'll find them through all the browsers.
On the need for a thesaurus please consult here
Knowledge base
While business rules were in the past often dictated by IT possibilities, the approach is inversed in knowledge modelling: without knowledge, no model and no application.
This :
- forces business units to take responsibility for the end-to-end processes;
- allows a common understanding of the products and processes;
- allows an effective real-time risk control: of the processes, of the products, of the positions
Ontology development tools
Many tools are today available.
The choice involves balancing the capabilities in:
- price
- collaborative development possibilities
- tools optimizing reasoning functions
- automation of tasks
- supported data sources
- supported standards: RDF(S), OWL ?, SPARQL, ARQ, ... ?
- documentation generation
To request more information, please use the form here.
What ?
Who ?
Why ?
Annotations
Philosophical background
on ontologies can be found via the links above.
They broaden the vision on our method and form the background of our generic solution.
Consulting
We offer consulting in the domain of finance.
Specific competence areas are:
- domain knowledge acquisition, management and representation
- process management in finance operations
- IT project management (Prince 2 methodology)