"linking open data" http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData
freebase DBpedia
"linked data"
“Structured Web”
“Semantic Web” DBpedia
http://blogs.talis.com/nodalities/2007/05/www2007_linked_data_once_again.php
Tim demonstrates using Tabulator to view and navigate the relationships between nuggets of data stored in Linked Data-friendly repositories such as DBpedia. Interestingly - and importantly - Tabulator displays the provenance of the individual data assertions, backing up the point from his keynote that RDF triples are 'actually a quad'; with the fourth - provenance - being absolutely essential in building a trustworthy Data Web.
-------------issues of trust and authority in a linked network of assertions.
http://sites.wiwiss.fu-berlin.de/suhl/bizer/pub/DBpedia-WWW2007-draft-slides.pdf
The “Structured Web” -- http://www.mkbergman.com/?p=354
DBpedia Serves Up Real Meat and Potatoes (but Bring Your Own Knife and Fork!)
NOTE: Due to demand, I am pleased to provide this PDF version of this posting (1.4 MB) for downloading or printing.
DBpedia is the first and largest source of structured data on the Internet covering topics of general knowledge. You may have not yet heard of DBpedia, but you will. Its name derives from its springboard in Wikipedia. And it is free, growing rapidly and publicly available today.
With DBpedia, you can manipulate and derive facts on more than 1.6 million “things” (people, places, objects, entities). For example, you can easily retrieve a listing of prominent scientists born in the 1870s; or, with virtually no additional effort, a further filtering to all German theoretical physicists born in 1879 who have won a Nobel prize [1]. DBpedia is the first project chosen for showcasing by the Linking Open Data community of the Semantic Web Education and Outreach (SWEO) interest group within the W3C. That community has committed to make portions of other massive data sets — such as the US Census, Geonames, MusicBrainz, WordNet, the DBLP bibliography and many others — interoperable as well.
DBpedia has been unfortunately overlooked in the buzz of the past couple weeks surrounding Freebase. Luminaries such as Esther Dyson, Tim O’Reilly and others have been effusive about the prospects of the pending Freebase offering. And, while, according to O’Reilly Freebase may be “addictive” or from Dyson it may be that “Freebase is a milestone in the journey towards representing meaning in computers,” those have been hard assertions to judge. Only a few have been invited (I’m not one) to test drive Freebase, now in alpha behind a sign-in screen, and reportedly also based heavily on Wikipedia. On the other hand, DBpedia, released in late January, is open for testing and demos and available today — to all [2].
Please don’t misunderstand. I’m not trying to pit one service against the other. Both services herald a new era in the structured Web, the next leg on the road to the semantic Web. The data from both Freebase and DBpedia are being made freely available under either Creative Commons or the GNU Free Documentation License, respectively. Free and open data access is fortunately not a zero sum game — quite the opposite. Like other truisms regarding the network effects of the Internet, the more data that can be meaningfully intermeshed, the greater the value. Let’s wish both services and all of their cousins and progeny much success!
Freebase may prove as important and revolutionary as some of these pundits predict — one never knows. Wikipedia, first released in Jan. 2001 with 270 articles and with only 10 editors, only had a mere 1000 mentions a month by July 2003. Yet today it has more than 1.7 million articles (English version) and is ranked about #10 in overall Web traffic (more here). So, while today Freebase has greater visibility, marketing savvy and buzz than DBpedia, so did virtually every other entity in Jan. 2001 compared to Wikipedia in its infancy. Early buzz is no guarantee of staying power.
What I do know is that DBpedia and the catalytic role it is playing in the open data movement is the kind of stuff from which success on the Internet naturally springs. What I also know is that in open source content a community is required to power a promise to its potential. Because of its promise, its open and collaborative approach, and the sheer quality of its information now, DBpedia deserves your and the Web’s attention and awareness. But, only time will tell whether DBpedia is able to nurture a community or not and overcome current semantic Web teething problems not of its doing.
First, Some Basics
DBpedia represents data using the Resource Description Framework (RDF) model, as is true for other data sources now available or being contemplated for the semantic Web. Any data representation that uses a “triple” of subject-predicate-object can be expressed through the W3C’s standard RDF model. In such triples, subject denotes the resource, and the predicate denotes traits or aspects of the resource and expresses a relationship between the subject and the object. (You can think of subjects and objects as nouns, predicates as verbs.) Resources are given a URI (as may also be given to predicates or objects that are not specified with a literal) so that there is a single, unique reference for each item. These lookups can themselves be an individual assertion, an entire specification (as is the case, for example, when referencing the RDF or XML standards), or a complete or partial ontology for some domain or world-view. While the RDF data is often stored and displayed using XML syntax, that is not a requirement. Other RDF forms may include N3 or Turtle syntax, and variants of RDF also exist including RDFa and eRDF (both for embedding RDF in HTML) or more structured representations such as RDF-S (for schema; also known as RDFS, RDFs, RDFSchema, etc.).
The absolutely great thing about RDF is how well it lends itself to mapping and mediating concepts from different sources into an unambiguous semantic representation (my ‘glad‘ == your ‘happy‘ OR my ‘glad‘ is your ‘glad‘), leading to what Kingsley Idehen calls “data meshups“. Further, with additional structure (such as through RDF-S or the various dialects of OWL), drawing inferences and machine reasoning based on the data through more formal ontologies and descriptive logics is also within reach [3].
While these nuances and distinctions are important to the developers and practitioners in the field, they are of little to no interest to actual users [4]. But, fortunately for users, and behind the scenes, practitioners have dozens of converters to get data in whatever form it may exist in the wild such as XML or JSON or a myriad of other formats into RDF (or vice versa) [5]. Using such converters for structured data is becoming pretty straightforward. What is now getting more exciting are improved ways to extract structure from semi-structured data and Web pages or to use various information extraction techniques to obtain metadata or named entity structure from within unstructured data. This is what DBpedia did: it converted all of the inherent structure within Wikipedia into RDF, which then makes it manipulable similar to a conventional database.
And, like SQL for conventional databases, SPARQL is now emerging as a leading query framework for RDF-based “triplestores” (that is, the unique form of databases — most often indexed in various ways to improve performance — geared to RDF triples). Moreover, in keeping with the distributed nature of the Internet, distributed SPARQL “endpoints” are emerging, which represent specific data query points at IP nodes, the results of which can then be federated and combined. With the emerging toolset of “RDFizers“, in combination with extraction techniques, such endpoints should soon proliferate. Thus, Web-based data integration models can either follow the data federation approach or the consolidated data warehouse approach or any combination thereof.
The net effect is that the tools and standards now exist such that all data on the Internet can now be structured and combined and analyzed. This is huge. Let me repeat: this is HUGE. And all of us users will only benefit as practitioners continue their labors in the background. The era of the structured Web is now upon us.
A Short Intro to DBpedia [6]