David S. Read

Last week I had the pleasure of attending Semantic Arts’ training class entitled, “Designing and Building Business Ontologies.”  The course, led by Dave McComb and Simon Robe, provided an excellent introduction to semantic technologies and tools as well as coverage of ontological best practices.  I thoroughly enjoyed the 4-day class and achieved my principle goals in attending; namely to understand the semantic web landscape, including technologies such as RDF, RDFS, OWL, SPARQL, as well as the current state of tools and products in this space.

Both Dave and Simon have a deep understanding of this subject area.  They also work with clients using this technology so they bring real-world examples of where the technology shines and where it has limitations.  I recommend this class to anyone who is seeking to reach a baseline understanding of semantic technologies and ontology strategies.

Why am I so interested in semantic web technology?  I am convinced that structuring information such that it can be consumed by systems, in ways more automated than current data storage and association techniques allow, is required in order to achieve any meaningful advancement in the field of information technology (IT). Whether wiring together web services or setting up ETL jobs to create data marts, too much IT energy is wasted on repeatedly integrating data sources; essentially manually wiring together related information in the absence of the computer being able to wire it together autonomously!

What do I mean?  Consider a flat file containing phonebook data.  In order to read that file I have to create a program (or configure a utility) to import the information, assigning the fields within the file to data attributes I name.  These names, which would be things like name, address, home_phone and the like, don’t mean anything to the computer.  They are for my (the human’s) convenience.

Once processed I can then create a report, laying out the data in a way that is easily read by people.  Alternatively I can place it in a relational database.  However, that structure doesn’t address the semantic issue.  The database will simplify access to the data.  Tables will have meaningful names like people and phone_numbers while columns will be labeled as person_id, first_name, last_name, phone_type and phone_number.  The tables will be normalized so that I can join them to get the set of phone numbers for each person.

However, for any use of that data, it will be people writing SQL statements or configuring O/R mapping tools to tell the computer how to join the tables and what data to read.  The metadata within the relational database doesn’t provide semantic association of the data.  So it seems that we really haven’t moved the needle very far in terms of enabling true automated data association over the last 40 years of computer software development.

One goal of a semantic web is to remove the need for manually wiring together data.  Data should already know how it relates to other data.  We indirectly wire data together in relational databases, we just don’t do it in a way that maintains the meaning of the association.

For instance, in a phone book database we carefully create rows containing phone numbers that have a foreign key back to a person.  Unfortunately, the key is generic; it doesn’t house the meaning of the association.  That meaning is vital to being able to automatically create associations between data.

Meaning is a word we use a lot with semantics – since in itself semantics is a study of meaning.  The structured support for meaning is provided by an ontology. We must unify our meanings within our domain.  It isn’t that everyone has to agree on what a word means.  Rather, each business, industry or individual creating data must associate his or her data relationships with a strict definition that can be used to relate it to other data.  Upper ontologies play a role in this as well.

Over the coming months I’ll be using my new knowledge regarding semantic tools and standards, spending time  focusing my attention on exploiting their capabilities for both personal and professional work.  I will write about my experiences as I progress.  I hope others who share my excitement over this potential step change in the IT field will provide their feedback as well.

I find strong similarities between the arrival of semantic technologies and the introduction of relational databases in place of VSAM files.  Myriad aspects of application design, implementation and operation will change as a result of exploiting these new techniques and tools.  It will also take a long time for tools, techniques and standards to mature to a level that makes them ubiquitous within our IT solution stack.

I’m looking forward to joining the semantic adventure.  It appears to be a field wide open to possibilities and positioned to fundamentally change the way we approach many aspects of information systems delivery.

Tags: efficient coding, enterprise applications, enterprise systems, Information Systems, linkedin, ontology, Public Data, semantic web, semantics, system integration, web services

This entry was posted on Sunday, May 9th, 2010 at 23:26 and is filed under Architecture, Information Systems, Public Data, Software Composition, Software Development, Tools and Applications. You can follow any responses to this entry through the RSS 2.0 feed. You can skip to the end and leave a response. Pinging is currently not allowed.