- RDF/XML: statements of facts or assertions about resources in the form of triples, e.g.: doc.html has author Jeremy and is about Genetics
- RDF Schema:
- definition of the vocabulary or ontology used in the triples, e.g. author, first name, article, etc.
- description of hierarchies of concepts and relations, e.g.:
- article is a kind of document
- firstname is a kind of designation
- firstname applies to persons
- provides formal characterisation of types and relations, e.g.:
- hasSpouse is a symmetric relation
- hasChild is the inverse of hasParent
- a Mother is a woman with at least one child
- allows data merging
- SWRL: semantic web rule language
"an extension of the current web with metadata for machines" (Fabien Gandon)
"an initiative to enable cross-platform data exchange and reuse through well-defined ontologies and a common XML-based framework."
"The goal of the Semantic Web initiative is to create a universal medium for the exchange of data where data can be shared and processed by automated tools as well as by people." 
- allows to model real things, not just documents or database tables (knowledge representation)
- consists of statements about resources in the form of triples:
SUBJECT -> PROPERTY -> VALUE
SUBJECT -> PREDICATE -> OBJECT
- identifies every resource with a globally unique URI: don't say "color", say <http://example.com/2005/std6#col>
- allows “serendipitous reuse”: integration with data sources in other fields (“web join”)
A semantic Web will not require proof generation to be useful: proof validation will be enough.
The first uses, such as access control on web sites, involve validation of a previously prepared proof, not a requirement to answer an arbitrary question, find the path the construct a valid proof. It is well known that to search for and generate a proof for an arbitrary question is typically an intractable process for many real world problems, and RDF does not require this (unsolvable) problem to be solved to be useful.
(from Semantic Web roadmap)
- Basic model contains just the concept of an assertion, and the concept of quotation - making assertions about assertions.
- Schema layer makes simple assertions about permitted combinations
- Conversion language contains rules for converting a document in one RDF schema into another one (which presumably one has an innate understanding of how to process).
- Logical layer - ways of writing logic into documents to allow such things as rules the deduction of one type of document from a document of another type; the checking of a document against a set of rules of self-consistency; and the resolution of a query by conversion from terms unknown into terms known. A simple example of the application of this layer is when two databases, constructed independently and then put on the web, are linked by semantic links which allow queries on one to converted into queries on another.
Annotation problem (evolvability)
- In the case of a program which finds a version 2 document and wants to find the rules to convert it into a version 1 document, then the version 2 schema would naturally contain or point to the rules.
- In the case of retrospective documentation of the relationship between two independently invented schemas, then of course pointers to the rules could be added to either schema, but if that is not (socially) practical, then we have another example of the the annotation problem. This can be solved by third party indexes which can be searched for connections between two schemata. In practice of course search engines provide this function very effectively - you would just have to ask a search engine for all references to one schema and check the results for rules which like the two.
- If an engine of the future combines a reasoning engine with a search engine, it may be able to get the best of both worlds, and actually be able to construct proofs in a certain number of cases of very real impact. It will be able to reach out to indexes which contain very complete lists of all occurrences of a given term, and then use logic to weed out all but those which can be of use in solving the given problem.
- Many real life problems can be solved using just a few (say two) steps of inference out on the wild web.
- Engines and algorithms which will efficiently tackle specific types of problem.
Semantic Web and Entity-Relationship models (from http://www.w3.org/DesignIssues/RDFnot.html)
- RDF is more general than ER and can be a basis for it.
- The mapping is very direct:
- a record is an RDF node;
- the field (column) name is RDF propertyType; and
- the record field (table cell) is a value.
(access control, user authentication, etc)
Lowercase semantic web
- International Journal on Semantic Web and Information Systems
- Biological Knowledge is an open access, peer-reviewed, online journal. The fields covered by the journal include, but are not limited to: ontologies, knowledge representation, and knowledge bases; reasoning, discovery, and machine learning; natural language processing and linguistics; history, philosophy, sociology, and anthropology; cognitive science, including cognitive and social psychology; education; and system design and software for knowledge creation, extraction, and manipulation.
Semantic Web for Life Sciences
"Browsers that can automatically identify entities such as protein and gene names, molecular processes, diseases, types of tissue, etc. and the relationships between them, in any Web document, collect these entities and then apply further analyses to them using applicable Web and Grid services." (Fabien Gandon)
- ESW Wiki
- BioIT World
- Berners-Lee - Semantic Web Life Sciences - BioIT World Expo 2005 (May 2005)
- Masters of the Semantic Web - Oct 2005
- RDF — The Web’s Missing Link by Eric Neumann (Mar 2006)
- "Many suggest that ontologies will be the key to integrate data properly. Although I see clear value in defining and using ontologies, there is nothing intrinsic to them that will make data integration any easier for scientists. Ontologies will require a lot of consensus building between community members (see BioPAX.org), and a common enterprise architecture that validates and connects data using ontologies is still lacking (though OWL makes this tractable). I for one see connecting existing data first through RDF’s triple model as a way to greatly facilitate the building of ontologies in a practical bottom-up approach."
- XML, RDF, Ontologies and Bioinformatic Data Mining - comment on article
- "I would argue without both the bottom up and the top down approach to semantic mapping of biomedical data (raw, reduced, analyzed and the research literature), we will not be able to capture the labyrinthine interactions complemented by subtle, real-world detail critical to understanding complex phenotype and disease."
- W3C Workshop on Semantic Web for Life Sciences
- Which gene did you mean? BMC Bioinformatics
- W3C Semantic Web Health Care and Life Sciences Interest Group
- email@example.com - mail archives
- Scientific publishing on the 'semantic web' - nature.com
- A Little Semantic Web Goes a Long Way in Biology
- Relations in biomedical ontologies
- Biosemantics Group at the University Medical Center Rotterdam (Netherlands) aims at developing and validating advanced techniques for the processing and analysis of large, complex, and heterogeneous medical and biological data sets