Neurocommons

The Neurocommons is an open RDF database developed by Science Commons. It was compiled from major life sciences databases with a focus on neuroscience. It is accessible via a web-based front end using the SPARQL query language.

The Neurocommons project is creating an Open Source knowledge management platform for biological research and has two distinct phases. The first phase is a project to apply text mining and natural language processing to open biomedical abstracts.

The second phase is the development of a data analysis software system.

A prerequisite for automated categorization of scientific information is that it be in a consistent format that can be processed meaningfully and accurately by software.  Literature searches are the primary method by which scientists obtain up to date information about the subject matter in their particular field.

Links among literature, data records, real-world entities, and abstract concepts, with formal definitions of each link’s endpoints and type. Applications need to use common identifiers for endpoints so that mentions of shared entities can be matched. This discipline of links, definitions, and identification is exactly what the framework of the semantic web provides.

In collaboration with the W3C Semantic Web Health Care and Life Science interest group, information from a variety of standard sources to establish core RDF content that can be used as a basis for bioinformatics applications. 

The neurocommons project started with one of the primary repositories for Biomedical literature.  The randomly selected 874,727 PubMed/Medline abstracts and fed them into Temis IDE equipped with the “biological entity recognizer” (BER). BER was able to perform some degree of processing on 368,688 of the abstracts.

BER categorizes terms and phrases in the input text in various ways (e.g. as a genetic population, chemical entity), but the only controlled vocabulary handled by BER is one for proteins and genes.

Each concept tree generated by BER was pruned to remove information not related to proteins/genes and their interactions, converted to a canonical format, and then rendered as RDF. Each leaf of the RDF concept tree is a protein/gene substance node, and internal nodes are called ‘associations.’

The images below describe the resulting organization: 

Beyond processes and other associations, the RDF captures additional annotations that relate the annotations to the originating PubMed record and to other data sources. Protein/gene nodes are linked to their identified gene and protein public databases.

FOAF

A more popular application of the semantic web is the Friend of a Friend Project (FOAF) which describes relationships among people and other agents in terms of RDF. The Friend of a Friend (FOAF) project is creating a Web of machine-readable pages describing people, the links between them and the things they create, places they visit, etc.

FOAF is an RDF vocabulary. FOAF data is decentralized and within user control. An example application that uses these files might be a community directory where members maintain their own records.  Many communities have evolved and grown on the Internet, from companies through professional organizations to soley social groups. The FOAF vocabulary gives a basic identifiers for community membership by describing people through their basic properties.

Some of the benefis of the potential resulting from this project's efforts include:

• Augment e-mail filtering by prioritizing mails from colleagues
• Provide assistance to new members in a particular community.
• Locate people with similar interests, location, etc

Simple properties to characterize an individual

By aggregating and merging the FOAF files, you can achieve the same effect as operating a centralized directory service, without any of the issues of single points of failure or control.

This is a very attractive feature for many communities for which decentralized control is necessary.

Our tutorial for FOAF

SIOC

The SIOC initiative (Semantically-Interlinked Online Communities) aims to enable the integration of online community information. SIOC provides a Semantic Web ontology for representing data from the social web 2.0 in RDF. It has recently achieved significant adoption through its usage in a variety of commercial and open-source software applications, and is commonly used in combination with the FOAF vocabulary for expressing personal profile and social networking information.

SIOC enables usage scenarios for online community site data, and allows semantic applications to be built on top of existing social websites.

• Create distributed conversations across blogs, forums and mailing lists
• Enhanced export/import format, with access to either the entire content or summaries
• Enable publishing and subscribing to decentralized discussion channels and communities

A list of SIOC data sources can be found on the SIOC “Enabled Sites” wiki page, or by downloading the export list from PingtheSemanticWeb.com

PingtheSemanticWeb.com is a web service archiving the location of recently created/updated RDF documents on the Web. If one of those documents is created or updated, its author can notify PTSW that the document has been created or updated by pinging the service with the URL of the document.

PingtheSemanticWeb.com is used by crawlers or other types of software agents to know when and where the latest updated RDF documents can be found

SIMILE

SIMILE is a joint project conducted by the MIT Libraries.

SIMILE seeks to enhance inter-operability among digital assets including schmemas, ontologies, and metadata.  A key challenge is that the collections which must inter-operate are often distributed across individual, community, and organizations.

In addition, SIMILE wants to implement a digital asset dissemination architecture based upon web standards. The dissemination architecture will provide a mechanism to add useful views to digital object including metadata, schemas, vocabularies.

Applications that have originated from the SIMILE project include: 

Babel: converts standard formats to web semantic formats

• Can convert between RSS, N3, Turtle, and RDF/XML as well as other formats

Fresnal: Fresnel is a vocabulary for displaying RDF. The prefix fresnel: is often used. The main goals are to help developers stop reinventing the wheel provide portable descriptions of resources that function similarly independent of the rendering browser, making it easy for users to visually reconcile what they see with what they already recognize regardless of which software they use.

Longwell: Longwell mixes the flexibility of the RDF data model with the effectiveness of the faceted browsing UI paradigm and enables you to visualize and browse any arbitrarely complex RDF dataset, allowing you to build a user-friendly web site out of your data within minutes and without requiring any code at all.

• Demo search for 3.0 within the MIT Library

PiggyBank: Piggy Bank is a Firefox extension that turns your browser into a mashup platform, by allowing you to extract data from different web sites and mix them together. Piggy Bank also allows you to store this extracted information locally for you to search later and to exchange at need the collected information with others.

• Demo of Piggy Bank
  

RDFizers: Converts content into RDF format. Plug-ins avialable for a variety of existing formats including e-mail, bibliographies, and raw image files

Seek: Mozilla firefox plug-in demo to view e-mail in RDF format

• Demo of Seek

Welkin:

Commerical Interests: Utilizing Existing Content

FreeBase - Commerical program from MetaWeb that is in the early stages of cateogrizing, tagging, and databasing existing content on the web (different from Googlebase and Wikipedia in that it is compiling information from sources)

Leiki - Uses machine learning and algorithms to parse information and categorize for the purpose of personalization (goal: is targeted adveritsing)

Twine: utilizes a combination of RDF, OWL, and machine-learning techniques to gather information about individual's interests

Powerset: Natural Language Processing (NLP) search engine for the web.

As it stands today, there are two primary approaches to categorizing content for the Web 3.0 objectives.

The first is the "bottom up" approach, which involves embedding semantical annotations (meta-data) right into the data. Primary technologies involved in the re-annotation of existing web content are based on RDF organizational schemas.  New ontologies are emergenging to simplify the process and include languages such as Turtle. Many research driven pursuits in the semantic web are focused on implementing these technologies into the Internet today in order to ease the organization, navigation, and structure of the data contained on the web today.

The second approach is "top down" and relies on analyzing existing information across the Internet and considers using natural language processing to understand and interpret information.  Many commercial interests have developed from trying to "understand" the content of the web.  Various mechanisms including tagging and extensive databasing are being used.  

However, what will likely emerge, and what is currently emerging, are more hybrid models that integrate both the bottom up approach where new information, including Web 2.0 content of the future, begins to take the underlying structure of the technologies we have discussed, which existing data across the Internet, and that data that remains resistent to these new technologies will rely on more sophisticated NLP programming for compiling and data mining.

A large-scale analysis of Web 3.0 technologies and applications has yet to be performed. As technologies to support the semantic web are developed, they are beginning to shape how the next stage of Internet will function.  In our examination of the semantic web, we focus on the underlying technologies to better understand how they will integrate with existing Web 2.0 technologies and what possibilities they will offer different industries including education, business, government and health. We hope to identify how the semantic web is bridging the enormous gap between available knowledge and mining these tremendous information sets.

REFERENCES

1. V.R. Benjamins, J. Contreras, O. Corcho, A. Gomez-Perez, Six Challenges for the Semantic Web. In Proceedings of the 2002 International Semantic Web Conference 2002.
2. T. Berners-Lee, J. Hendler, and O. Lassila, "The Semantic Web," Scientific Am., May 2001.
3. L. Ding, L. Zhou, T. Finin, A. Joshi, How the Semantic Web is Being Used: An Analysis of FOAF Documents. Proceedings of the 38th Annual Hawaii International Conference on System Sciences. 03-06 Jan. 2005 Page(s):113c - 113c.
4. O. Lassila, J. Hendler, "Embracing "Web 3.0"," IEEE Internet Computing, vol. 11, no. 3, pp. 90-93, May/Jun, 2007.
5. R. MacManus, Eric Schmidt Defines Web 3.0, ReadWriteWeb, August 7, 2007. Retrieved from http://www.readwriteweb.com/archives/eric_schmidt_defines_web_30.php on April 22nd 2008.
6. N. Spivack, The Third-Generation Web is Coming, KurzweilAI.net, December 17, 2006. Retrieved from http://www.kurzweilai.net/meme/frame.html?main=/articles/art0689.html?m%3D3 on April 22nd, 2008.
7. A Toffler (1970). Future Shock, Bantam Books, 1970.
8. Wikipedia (2008) Internet Map. Retrieved from http://upload.wikimedia.org/wikipedia/commons/d/d2/Internet_map_1024.jpg on April 22^nd, 2008.
9. W3C (2008) Semantic Web Activity. Retrieved from http://www.w3.org/2001/sw/ on April 28th, 2008.
10. W3C (2008) Semantic Web Road Map. Retrieved from http://www.w3.org/DesignIssues/Semantic.html on April 28th, 2008.
11. Wikipedia (2008) Semantic Web. Retrieved from http://en.wikipedia.org/wiki/Semantic_Web on April 28^th, 2008.
12. W3C (2008) Resource Description Framework (RDF). Retrieved from http://www.w3.org/RDF on April 30th, 2008.
13. W3 schools (2008). Retrieved from http://www.w3schools.com/rdf on April 26th 2008.
14. P. Champin, RDF Tutorial, April 04, 2005. Retrieved from http://www710.univ-lyon1.fr/~champin/rdf-tutorial/ on April 30th, 2008.
15. E. Miller, An Introduction to the Resource Description Framework, D-Lib Magazin, May 1998. Retrieved from http://www.dlib.org/dlib/may98/miller/05miller.html on April 29th, 2008.
16. Wikipedia (2008) Resource Description Framework. Retrieved from http://en.wikipedia.org/wiki/Resource_Description_Framework on April 28th, 2008.
17. Wikipedia (2008) Web Ontology Language. Retrieved from http://en.wikipedia.org/wiki/Web_Ontology_Language on April 28th, 2008.
18. The RDF.net Challenge, May 21, 2005. Retrieved from http://www.tbray.org/ongoing/When/200x/2003/05/21/RDFNet on April 27th, 2008.
19. W3C (2008) RDF/XML Syntax Specification (Revised). Retrieved from http://www.w3.org/TR/rdf-syntax-grammar/#example7 on April 29th, 2008.
20. Wikipedia (2008) Ramanathan V. Guha. Retrieved from http://en.wikipedia.org/wiki/Ramanathan_V._Guha on April 28th, 2008.
21. W3C (2008) OWL Web Ontology Language. Retrieved from http://www.w3.org/TR/owl-features/ on April 30th, 2008.
22. G. Schreiber, The making of a Web Ontology Language a chair's perspective, March 12, 2004. Retrieved from http://www.cs.vu.nl/~guus/public/2004-webont-zeist/all.htm on April 31st, 2008.
23. P. Krill, OWL files as Web ontology Language, August 19, 2003. Retrieved from http://www.infoworld.com/article/03/08/19/HNowl_1.html on May 1st, 2008.
24. W3C (2008) Turtle - Terse RDF Triple Language. Retrieved from http://www.w3.org/TeamSubmission/turtle/ on May 1st, 2008
25. David Beckett, Modernising Semantic Web Markup, April 18-21 2004. Retrieved from http://www.idealliance.org/papers/dx_xmle04/papers/03-08-03/03-08-03.html on May 1st, 2008
26. Tim Berners-Lee, Notation 3, March 9, 2006. Retrieved from http://www.w3.org/DesignIssues/Notation3 on May 2nd, 2008
27. W3C (2008) Resource Description Framework (RDF): Concepts and Abstract Syntax. Retrieved from http://www.w3.org/TR/rdf-concepts/ on May 3rd, 2008.
28. W3C (2008) RDF Semantics. Retrieved from http://www.w3.org/TR/rdf-mt/ on May 3rd, 2008.
29. W3C (2000) Primer - Getting into RDF and Semantic Web using N3. Retrieved from http://www.w3.org/2000/10/swap/Primer.html on May 3rd, 2008
30. Edutech Wiki (2008), RDF. Retrieved from http://edutechwiki.unige.ch/en/RDF on May 3rd, 2008.
31. Science Commons (2008) Neurocommons Project.  Retrieved from http://sciencecommons.org/projects/data/ on May 1st, 2008.
32. MIT (2008) SIMILE Project.  Retrieved from http://simile.mit.edu/ on May 2nd, 2008.
33. FOAF Project (2008).  Firend of a Friend (FOAF) Project. Retrieved from http://www.foaf-project.org/ on May 3rd, 2008.

Syntax

- URIs are written enclosed by "< >" or abbreviated using Turtle's @prefix directive which allows using a short prefix name instead of a long prefix of repreated URIs.

- Literals are written using double quotes for text without linebreaks and in betweem "*** ***" for longer text (e.g. ***long literal***)

- Blank nodes are written as _:nodeID to provide a blank node at given nodeID. It can also be written with "[ ]".

Abbreviations

The @base directive along with the @prefix can be used to greatly simplify and abbreviate URIs.

The "," symbol is used to repeat subjects and predicates of triples that only differ at object.

The ";" is used to repeat subjects that differ at predicate and object RDF terms.

Decimal integers, floating point doubles and floating point arbitrary precision numbers may all be written directly and correspond to the XML Schema Datatype in both syntax and datatype URI. Similarly Boolean may be written directly as "true" or "false" and correspond to the XML Schema Datatype in both syntax and datatype URI.

An RDF Collection can be written using a sequence of RDF terms enclosed in "()" and separated by white space.

Grammar

White space, inputted "ws" is used to separate two tokens which may otherwise be mistaken for one. Note: In programming languages, a token is a single element of the programming language. For instance a token maybe a keyword, an operator or a punctuation mark.

Comments in turtle are made using "#" at the beginning of the comment and continue on until the end of the line.

Turtle strings and URIs can use "\-escape" sequences to represent Unicode code points.

URIs are resolved relative to the In-scope base URI. In practice this means the the URI is resolved relative to the last @base directive set. (This will be further clarified in the examples section.)

In introducing Turtle it is necessary to first introduce its established ancestors and nearest kin. Of particular importance is introducing Notation 3 (N3) and N-Triples since Turtle is in essence and extension of N-Triples which in turn was designed as a fixed subset of Notation 3.

Notation 3 was developed as early as 2000, or at least the earliest documentation dates back then. It was developed in the context of the Semantic Web Interest Group, as a sort of shorthand non-XML serialization of Resource Description Framework, RDF, models. Notation 3 is a simplified teaching language, which is basically equivalent to RDF in its XML syntax, but easier to grasp, make entries and to tailor. This is a language which is a compact and readable alternative to RDF's XML syntax, but also is extended to allow greater expressiveness. It has subsets, one of which is RDF 1.0 equivalent, and one of which is RDF plus a form of RDF rules.

Recall that RDF is the language used to input information regarding things of the web, such as webpages, and web resources. In RDF, information is simply a collection of statements, each with a subject, verb and object. In Notaion 3, of which Turtle is somewhat a derivative, such statements are called triples for the obvious reason, that it contains three parts. In Notation 3 you can write such a triple just as is with a period. For instance,

<#pat> <#knows> <#jo> .  

N-Triples is a line-based, plain text format for encoding an RDF graph and in particular for representing the correct answers for parsing RDF/XML[RDFMS] test cases as part of the RDF Core working group. It was designed to be a fixed subset of N3 and hence N3 tools such as cwm and Euler can be used to read and process it. Documentation and articles referring to N-Triples date as far back as April 2003.

An RDF graph is set of RDF triples. A subgraph is intuitively defined as a subset of the triples in the graph (i.e. RDF graph). Technically a single triple in a graph is considered a subgraph, hence to be more specific a proper subgraph is a proper subset of the triples in the graph.

Turtle which stands for Terse RDF Triple Language is a solution proposed by the W3C team for XML/RDF code which is quite verbose and a pain to write manually. We'll later indicate how Turtle improves on Notation 3.

Turtle allows for writing down an RDF graph in a compact text form. It consists of a sequence of directives, triple generating statements or blank lines. Simple triples, as defined earlier, are a sequence of terms (subject, predicate, object) separated in Turtle by whitespace and terminated by periods after each triple.

Before delving further we must define a few more terms.

Any expression in RDF is a collection of triples, each consisting of a subject, predicate and object. A set of such triples is called a graph, and can be represented as below.

As mentioned earlier, and depicted above, the triple consists of a subject and an object and how they are related, a predicate indicated by the directioned arrow above. The nodes of the triple are the subject and the object. In all instances the arrow points from the subject to the object.

An RDF triple contains three components:

• The subject, which is an RDF URI reference or a blank node
• The predicate, which is an RDF URI reference
• The object, which is an RDF URI reference, a literal or a blank node.

The predicate is also sometimes termed the 'property' of the triple.

URI

A Uniform Resource Identifer is, as the name says, something used to identify or name resources. Technically it is a compact string of characters meant to be used for identifying and or naming a resource. Resources such as a webpage, a text, a video clip, a program and the list goes on. Typically the URI describres three things: the mechanism for the resource, the computer the resource is hosted on, and the specifc name of the resource (a file name) on the host computer.

The most common type of URI is the URL.

Literal

A literal is a way to identify values such as numbers and dates by means of a lexical representation. In all cases a literal may be replaced by a URI, but literals are more convenient and intuitive to use.

Blank Node

A blank node is a node that is not a URI reference nor a literal but instead is a unique node that can be used in one or more RDF statements, but has no intrinsic name. The blank nodes in an RDF are drawn from an infinite set.

The following example is related to the URI Reference section on the Turtle grammar page. It clearly shows that the in-scope base URI at any point in the document is determined by the @base directive which sets a new base URI relative to the current in-scope base URI. Below this example we show how the same would be encoded in N-Triples. (Note: The lines in N-Trples are so long they are cut off in this screen format.)

***************************URI Reference*******************************

# In-scope base URI is http://www.w3.org/2001/sw/DataAccess/df1/tests/ at this point
<test-00.ttl> <test-01.ttl> <test-02.ttl> .
@base <http://example.org/ns/> .
# In-scope base URI is http://example.org/ns/ at this point
<a2> <http://example.org/ns/b2> <c2> .
@base <foo/> .
# In-scope base URI is http://example.org/ns/foo/ at this point

<a3> <b3> <c3> .
@prefix : <bar#> .
:a4 :b4 :c4 .
@prefix : <http://example.org/ns2#> .
:a5 :b5 :c5 .

*************************Same Code in N-Triples************************* 

 <http://www.w3.org/2001/sw/DataAccess/df1/tests/test-01.ttl> <http://www.w3.org/2001/sw/DataAccess/df1/tests/test-02.ttl> 

<http://example.org/ns/a2> <http://example.org/ns/b2> <http://example.org/ns/c2&>

<http://example.org/ns/foo/a3> <http://example.org/ns/foo/b3> <http://example.org/ns/foo/c3>

<http://example.org/ns/foo/bar#a4> <http://example.org/ns/foo/bar#b4> <http://example.org/ns/foo/bar#c4>

<http://example.org/ns2#a5> <http://example.org/ns2#b5> <http://example.org/ns2#c5>

****************************End of Example*****************************

The following is an example written in turtle followed by the original code in RDF. It highlights the terseness and simplicity which are the earmarks of Turtle.

**************Turtle Translation of Example 7****************

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix dc:  .
@prefix ex: <http://example.org/stuff/1.0/> .


  dc:title "RDF/XML Syntax Specification (Revised)" ;
  ex:editor [
    ex:fullname "Dave Beckett";
    ex:homePage <http://purl.org/net/dajobe/>
  ] .

******************Example 7 in RDF***********************

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
         xmlns:dc="http://purl.org/dc/elements/1.1/"
         xmlns:ex="http://example.org/stuff/1.0/">
  <rdf:Description rdf:about="http://www.w3.org/TR/rdf-syntax-grammar"
		   dc:title="RDF/XML Syntax Specification (Revised)">
    <ex:editor>
      
	<ex:homePage rdf:resource="http://purl.org/net/dajobe/" />
      </rdf:Description>
    </ex:editor>
  </rdf:Description>
</rdf:RDF> 

******************End of Example*************************

The following again higlights how much simpler and concise using Turtle will be.

**********Example of an RDF Collection of two literals***********

@prefix :  .
:a :b ( "apple" "banana" ) .

*************which is the short of example 2.ttl****************

@prefix : <http://example.org/stuff/1.0/> .
@prefix rdf:  .
:a :b
  [ rdf:first "apple";
    rdf:rest [ rdf:first "banana";
               rdf:rest rdf:nil ]
  ] .

******************End of Example*************************

The following is an example of two identical triples containing literal objects containing newlines, written in plain and long literal forms.

********************Two Identical Triples*******************

@prefix :  .

:a :b "The first line\nThe second line\n  more" .

:a :b """The first line
The second line
  more""" .

*********************End of Example**********************

Turtle compared to N-Triples

Turtle as an offshoot of N-Triples adds the following syntax, some of which have been discussed in earlier pages.

1. Whitespace restrictions removed
2. Text content-encoding changed from ASCII to UTF-8
3. @prefix
4. QNames
5. ,
6. ;
7. []
8. a
9. ()
10. Decimal integer literals (xsd:integer)
11. Decimal double literals (xsd:double)
12. Decimal arbitrary length literals (xsd:decimal)
13. Boolean literals
14. @base

Turtle compared to Notation3

The following is not a complete list but highlight some of the syntax which remains in N3 but is not in Turtle.

1. { ... }
2. is of
3. paths like :a.:b.:c and :a^:b^:c
4. @keywords
5. => implies
6. = equivalence
7. @forAll
8. @forSome
9. <=

Turtle compared to SPARQL

The SPARQL Query Language for RDF uses a Turtle/N3 style syntax for Triples including the same abbreviations mentioned earlier. The following syntax however are not in Turtle but are SPARQL. The following is not a complete list.

1. RDF Literals are allowed in triple subjects
2. Variables are allowed in any part of the triple of the form ?name or $name
3. Long literals can use use single quote (') characters: ''' ... '''
4. The constants allowed for XSD booleans: true and false are case independent. In Turtle they are not, only lowercase forms are allowed.
5. SPARQL allows '.'s in names in all positions apart from the first or last. These would correspond to rules:
   name ::= nameStartChar ( ( nameChar | '.' )* nameChar )?
   prefixName ::= ( nameStartChar - '_' ) ( ( nameChar | ' .' )* nameChar )?
6. SPARQL allows digits in the first character of the PN_LOCAL lexical token. In Turtle, the only ascii characters allowed in a nameStartChar are [A-Z] | "_" | [a-z].
7. Turtle allows prefix and base declarations anywhere outside of a triple. In SPARQL, they are only allowed in the Prologue (at the start of the SPARQL query).

RDF is the language used to input such information regarding things of the web, such as webpages, and web resources. In RDF, information is simply a collection of statements, each with a subject, verb and object. In Notation 3, of which Turtle is somewhat a derivative, one can write such a triple just as is with a period. For instance,

<#pat> <#knows> <#jo> . 

Turtle which stands for Terse RDF Triple Language is a solution proposed by the W3C team for XML/RDF code which is quite verbose and a pain to write manually.