Web Science Framework and InterDataNet
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Web Science Framework and InterDataNet

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Introduction to the Web Science for undergraduate students in Information Engineering

Introduction to the Web Science for undergraduate students in Information Engineering

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Web Science Framework and InterDataNet Web Science Framework and InterDataNet Presentation Transcript

  • Introduction to the Web Science For undergraduate students in Information Engineering Maria Chiara Pettenati 2008-2009 DET, University of Florence Italy Web Science Framework
  • Web Science Research Initiative (WSRI)
    • Announced in November 2006
    • A collaboration between MIT and the University of Southampton
    • Stated purpose is “to bridge and formalize the social and technical aspects of collaborative applications running on large-scale networks like the Web.”
    • “ Brings together academics, scientists, sociologists, entrepreneurs and decision makers from around the world. These people will create the first multidisciplinary research body to examine the Web and offer the practical solutions needed to help guide its future use and design.”
    • WebSci’09 – Athens, 3/18-20/2009
    White, B. (2008, Novembre 9). The Emergence of Web Science.
  • Before We Ask “What is Web Science?” White, B. (2008, Novembre 9). The Emergence of Web Science.
  • “ What is ‘The Web?’” (1/2) ? White, B. (2008, Novembre 9). The Emergence of Web Science.
  • “ What is ‘The Web?’” (2/2)
    • is an application (client + server) built on top of the TCP/IP stack providing a system of interlinked hypertext documents .
    • With a Web browser , one can access Web servers hosting Web pages that may contain multimedia objects and navigate between them using hyperlinks .
      • A distributed document delivery system implemented using application-level protocols on the Internet
      • A tool for collaborative writing and community building
      • A framework of protocols that support e-(applications)
      • A network of co-operating computers interoperating using HTTP and related protocols to form a ‘subnet’ of the Internet
      • A large, cyclical, directed graph made up of Web pages and links
      • A Giant Global Graph (GGG): computers, documents, people
    Adapted from White, B. (2008, Novembre 9). The Emergence of Web Science.
  • User Perspectives of ‘The Web’
    • To the Web ‘surfer’ – a network of Web sites
    • To the Web shopper – a network mall
    • To the Web searcher – a network of search results
    • To a user of social bookmarking tools – a network of tags
    • To blog authors/readers – a network of blog posts (‘the blogosphere’)
    • To a social network user – a network of contacts/people
    • etc.,etc.
    White, B. (2008, Novembre 9). The Emergence of Web Science.
  • Scientific Perspectives of ‘The Web’
    • Physical/biological science perspectives -laws/processes that generate or explain observed phenomena
    • Telecommunication perspectives - infrastructure and connectivity
    • Computer science perspective – middleware, applications, intelligent systems
    • Information science and knowledge management perspectives - data, information, knowledge, wisdom hierarchy
    • Social perspectives – social network, collective intelligence, participation, regulation, economy
    • Application perspectives -e-commerce, e-learning, e-government, etc.
    Adapted from: White, B. (2008, Novembre 9). The Emergence of Web Science.
  • Which Science Explains the Web? (1/2)
    • Given
      • Neither the Web nor the world is static
      • The Web is both technology (connectivity), content (documents) and people (net society)
      • The Web is influenced/influences
        • Social structures
        • Political systems
        • Commercial organizations
        • Educational institutions
        • Technology
        • Etc., etc.
    Adapted from: White, B. (2008, Novembre 9). The Emergence of Web Science.
  • It’s an Issue of Scale (1/2)
    • At the micro scale , the Web is an infrastructure of artificial languages and protocols; it is a piece of engineering
    • It’s the interactions of human beings creating, linking, and consuming information that generates the Web’s behavior as emergent properties at the macro scale
    • These properties often generate surprising properties that require new analytic methods to be understood
    Hendler, J., Shadbolt, N., Hall, W., Berners-Lee, T., and Weitzner, D. 2008.
  • It’s an Issue of Scale (2/2) Hendler, J., Shadbolt, N., Hall, W., Berners-Lee, T., and Weitzner, D. 2008.
  • Which Science explains the Web? (2/2)
    • Web Cosmology ; The scientific study of the origin, evolution, and structure of the universe (or Web) (Bebo White, 2008)
    • Web Ecology ; –Quantitatively measuring and testing theories of human behavior and social interaction of the Web seen as a gigantic informational ecosystem ( Zhuge, Hai and Xiaoqing, Shi, 2008 )
    • Web Engineering – methodologies, techniques and tools that are the foundation of Web application development and which support their design, development, evolution, and evaluation (ISWE)
    • Web Architecture and Planning ; applying to the Web the criteria of urban studies and planning (Nicola Lonzi, 2009)
    • Computational Social Science ; AA.VV. Science 6 February 2009
  • Web Science
    • Web Science is a new field of science that involves a multi-disciplinary study and inquiry for the understanding of the Web and its relationships to us
    • "social machines" (Berners-Lee and Fischetti, 1999);
      • the social machine includes the underlying technology but also the rules, policies and organizational structures that are used to manage the technology.
      • Eg. mediaWiki in Wikipedia
  • Challenges for the Web Science (1/2)
    • What are the fundamental theoretical properties of social machines , and what kinds of algorithms are needed to create them?
    • What are the underlying architectural principles to guide the design and efficient engineering of new Web infrastructure components for this social software?
    • How can we extend the current Web infrastructure to provide mechanisms that make the social properties of information sharing explicit and that guarantee that the uses of this information conforms to the relevant social policy expectations?
    • How do cultural differences effect the development and use of social mechanisms on the Web? As the Web is now truly "World Wide," the properties desired by one culture may be seen as counter-productive by another. Can Web infrastructure help in bridging cultural divides and/or increase cross-cultural understanding?
    Hendler, J., Shadbolt, N., Hall, W., Berners-Lee, T., and Weitzner, D. 2008.
  • Challenges for the Web Science (2/2)
    • How can we understand and develop?
      • The “dot-com” business models
      • Effective social networking environments
      • New “real-time” tools (Twittering,
      • Etc., etc.
    • How can we address?
      • trustworthiness, reliability, and tacit expectations Internationalization
      • privacy, copyright, and other legal rules
    • How will/can the Web affect the way we “do” science, education, governance, communication, etc.?
    • Why the Semantic Web has not yet arrived?
    • How will a “Web of objects” (Internet of Things) operate?
    • How will we address the issue of digital identity? (Miller, 2009)
    These are not pure technical questions
  • Why Web Science is Not Computer Science (1/2) Shneiderman, B. 2007. Web science: a provocative invitation to computer science. Commun. ACM 50, 6 (Jun. 2007)
  • Why Web Science is Not Computer Science (2/2) Shneiderman, B. 2007. Web science: a provocative invitation to computer science. Commun. ACM 50, 6 (Jun. 2007)
  • History Teaches – Computing curriculums stages Riera, Daniel (2009) Web science: a new computer-related curriculum.
  • Computing Curriculum
    • Computer Engineering (CE); it is included in the first two stages. It combines hardware and software, and does not work in the Web’s level.
    • Computer Science (CS); it deeps into theoretical foundations of computers and those problems solved using intelligent systems, etc. Users are mainly not taken into account.
    • Information Systems (IS); it is based on organizations and their information management. It is more centred on business.
    • Information Technology (IT); it treats the technological aspects of enterprises. Thus, this is a little less web-related than IS.
    • Software engineering; it is raised around software systems and everything surrounding them (efficiency, reliability, maintenance, etc.).
    • Curriculums proposed in the last half century by the major American org. developing computing curriculum guidelines (ACM, AIS, AITP and IEEE-CS1)
    Riera, Daniel (2009) Web science: a new computer-related curriculum.
  • Colliding Web Science Philosophy “ Phylosophy” has been added to the butterfly upon explicit agreement declared at the first WebScience Conference, held in Athens, March2009
  • Video Showcase
    • Information R/ evolution
    • The machine is us / ing us
  • Why do we watch this videos?
    • Because they provide thought provoking messages on the need to rethink a lot of things for the future Web
  • From Web 2.0 to Web 3.0 Towards the Semantic Web
  • Milestones of Web evolution
    • Internet: allowed programmers to communicate without concern of the network oc cable through which the communication had to flow
    • WWW; allowed users to work with a set of interconnected documents without the concern of the details of the computers storing and exchanging them
    • Semantic Web; will allow users to refer to real-word objects without concern for the underlyin documents in which these things, abstract and concrete, are described
    Which are the effect of this new capabilities on the connections whithin the Web of people who use them?
  • Web 2.0
    • Read/Write, two-way, anyone can be a publisher
    • Social Web
    • The term “Web 2.0” defines an era; like “Dot Com”
    • Search (Google, Alternative Search Engines)
    • Social Networks (MySpace, Facebook, OpenSocial)
    • Online Media (YouTube, Hulu, Last.fm)
    • Content Aggregation / Syndication (Bloglines, Google Reader, Techmeme, Topix)
    • Mashups (Google Maps, Flickr, Amazon)
    • Image credit: catspyjamasnz
    Richard MacManus Web 3.0 or Not, There's Something Different About 2009
  • Web Trends Beyond Web 2.0
    • Web Sites Become Web Services
      • “ Unstructured information will give way to structured information - paving the road to more intelligent computing.” (Alex Iskold, ReadWriteWeb, Mar 07)
      • Examples: Amazon E-Commerce API, del.icio.us API, Twitter API, Dapper, Yahoo! Pipes (scraping technologies)
      • Pages not center of Web now, Data & Services are
      • 90% of Twitter activity happens through its API
    • Intelligent Web = data is getting smarter (ref: Nova Spivack, Twine, Oct 07)
      • Semantic Web / Linked Data
      • Filters / recommendations
      • Personalization
    • Beyond PC - mobile, IPTV, physical world integration
    Richard MacManus Web 3.0 or Not, There's Something Different About 2009
  • Web 3.0?
    • “ People keep asking what Web 3.0 is. I think maybe when you've got an overlay of scalable vector graphics […] on Web 2.0 and access to a semantic Web integrated across a huge space of data […]” Tim Berners-Lee, 2006
    • ” The Web of Openness . A web that breaks the old siloes, links everyone everything everywhere, and makes the whole thing potentially smarter .” Greg Boutin, May 2009
    • “ The Web 3.0 term misleads organizations by implying that a new version of the web is upon us.” Anthony Bradley, Gartner, April 2009
    Richard MacManus Web 3.0 or Not, There's Something Different About 2009
  • Web 3.0 in a Nutshell
    • Cartoon by
    • Geek and Poke
    Richard MacManus Web 3.0 or Not, There's Something Different About 2009
  • Web 3.0 or No, We’re Seeing Something New
    • There is a difference in the products we're seeing in 2009 compared to the ones we saw at the height of 'Web 2.0' (2005-08).
      • More products based on open, structured data e.g. Wolfram Alpha
      • More real-time e.g. Twitter, OneRiot
      • Better filters e.g. FriendFeed (and Facebook, which copies FF )
      • Google evolves (Search Options and Rich Snippets, Search Wiki, Google Squared)
        • real-time information , adding more meaning to the data (aka Semantic Search ), and filtering results . The new features show that Google is adapting to this environment.
    • Open data, structured data, filtering content, real-time, personalization
    Richard MacManus Web 3.0 or Not, There's Something Different About 2009
  • Web 3.0?
    • If Web 2.0 was about user generated content and social applications such as YouTube and Wikipedia, then Web 3.0 is about open and more structured data - which essentially makes the Web more 'intelligent'.
    • Web 3.0 is an amorphous term, and possibly one that people shouldn't even attempt to use. Nevertheless, it's clear to us that the time for structured data has come. We're beginning to see it in the current wave of Linked Data sets being released, and in the support that big companies, like Google and Yahoo, are showing for structured data. Who knows, maybe the Semantic Web is nearly upon us too.
    Richard MacManus Understanding the New Web Era: Web 3.0, Linked Data, Semantic Web May 14 2009
  • Linked Data A vision within the Web Science and a bottom-up approach to Semantic Web
  • Linked Data: Let A Thousand Flowers Bloom
    • Linked Data enables data to be opened up and connected so that people can build interesting new things from it. (via Tim Berners-Lee) Linked Data is Blooming; ReadWriteWeb, May 2009
  • What is Linked Data?
    • Linked Data offers a new medium to link structured data that is then more machine-readable ." However, he added that Linked Data "does not by itself add any semantic meaning to the information, but it better carries that semantic information once you have it.
    • So, while Linked Data is not semantic, creating links at the data level paves the way to a true Semantic Web ." (Greg Boutin, Tying Web 3.0, the Semantic Web and Linked Data Together - Part 2/3: Linked Data is a Medium)
    • More specifically, Wikipedia defines Linked Data as "a term used to describe a recommended best practice for exposing, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web using URIs and RDF ." (Chris Bizer, Tom Heath, Kingsley Idehen, Tim Berners-Lee WWW 2008: Linked Data on the Web)
  • Bridging the gap: Semantic Web – Web of Data Data Semantics Linking data entries using URIs powered by RDF and SPARQL helps to create Web applications and portals that use REST-based models, integrating data from multimple sources withouth need of preexisting schema Provide models that can be used to represent expressive semantic descriptions (OWL) of applications domains and provide inferencing power for Web and non-Web applications that need A knowledge base Scalability Linked Data Ontologies
  • The Classic Web
    • Single information space,
    • build on
    • URIs
      • globally unique IDs
      • retrieval mechanism
    • Hyperlinks
      • are the glue that holds everything together
    B C HTML HTML HTML Web Browsers Search Engines hyper- links A hyper- links Chris Bizer, Tom Heath, Kingsley Idehen, Tim Berners-Lee WWW 2008: Linked Data on the Web
  • Linked Data B C Thing typed links A D E typed links typed links typed links Thing Thing Thing Thing Thing Thing Thing Thing Thing
    • Use Semantic Web technologies to
    • publish structured data on the Web,
    • set links between data from one data source to data within other data sources .
    Chris Bizer, Tom Heath, Kingsley Idehen, Tim Berners-Lee WWW 2008: Linked Data on the Web
  • Applications (1/2) B C Thing typed links A D E typed links typed links typed links Thing Thing Thing Thing Thing Thing Thing Thing Thing Search Engines Linked Data Mashups Linked Data Browsers
    • What can I do with this?
    Chris Bizer, Tom Heath, Kingsley Idehen, Tim Berners-Lee WWW 2008: Linked Data on the Web
    • Once the data sets are interconnected (i.e. link to each other like websites), a machine can traverse this independent web of noiseless, structured information to gather semantic knowledge of arbitrary entities and domains .
      • The result is a massive, freely accessible knowledge base forming the foundation of a new generation of applications and services.
      • The data sets currently can be accessed in heterogeneous ways; for example, through a semantic web browser or by being crawled by a semantic search engine .
    Applications (2/2)
    • What can I do with this?
  • LD Principles
    • Use URIs as names for things
    • Use HTTP URIs so that people can look up those names.
    • When someone looks up a URI, provide useful information.
    • Include links to other URIs. so that they can discover more things.
      • The essence of Linked Data comes down to a URI that delivers the following in one go:
        • Named Reference (a Web Space name for something)
        • Conduit to an address (URL) that exposes the Description of a Named Thing in a negotiated representation ( (X)HTML, RDFa, N3, Turtle, RDF/XML etc..)
        • from: Kingsley Idehen, ReadWriteWebm comment to The Web of Data: Creating Machine-Accessible Information , April 19, 2009
  • W3C Linking Open Data Project
    • Community effort to
      • publish existing open license datasets as Linked Data on the Web
      • interlink things between different data sources
    Chris Bizer, Tom Heath, Kingsley Idehen, Tim Berners-Lee WWW 2008: Linked Data on the Web
  • The LOD Cloud Collectively, the data sets consist of over 4.5 billion RDF triples , which are interlinked by around 180 million RDF links (March 2009). Typically, a data set contains knowledge about a particular domain, like books, music, encyclopedic data, companies
  • Web 3.0, Semantic Web, Data and Linked Data
  • Linked Data demo
    • http://delicious.com/kidehen/linked_data_demo
    • the company Yahoo! on CrunchBase ,
    • the city of Berlin or the game Tetris on DBpedia ,
    • the book iPhone : The Missing Manual on O'Reilly Media .
  • InterDataNet (IDN) a Web-wide Collaboration-oriented Infrastructure for Scalable Linked Data Applications Pirri, F., Pettenati M.C., Innocenti, S., Chini D, Parlanti D. and Ciofi L. Proceedings of WebSci'09: Society On-Line, InterDataNet : an Infrastructural Approach for the Web of Data Athens, Greece 18th–20th March, 2009
  • A place for the IDN
    • 1) in a highly dynamic and extremely rapidly growing environment the permanent search, analysis and alignment of new data, is mainly entirely performed by the Linked Data initiative itself, introducing a form of centralization which is not intended
    • 2) reasoning over owl:sameAs relations in distributed ontologies is a computationally complex task
  • IDN objectives
    • provide a scalable and open service to support a consistent reuse of entities identifiers, that is a global reference and addressing mechanism for locating and retrieving resources in a collaborative environment
    • provide basic collaboration-oriented functions, namely authorship control, versioning and replica management.
  • The IDN Views
  • IDN design patterns
    • InterDataNet has been designed using the following set of conceptual and technological design patterns:
      • the Service Oriented Architecture (SOA) approach (allows us the development of loosely coupled and interoperable services which can be combined into more complex systems)
      • the REpresentational State Transfer (REST) style interfaces to enable resource addressability for performance, scalability and abstraction
  • IDN entities
    • The IDN framework is defined through three entities:
      • IDN-IM ( IDN Information Model ): is the shared information model representing a generic document model
      • IDN-SA ( IDN Service Architecture ): is the architectural model handling IDN-IM documents. It exposes an IDN-APIs (Application Programming Interfaces) on top of which IDN-compliant Applications can be developed
      • IDN Compliant Applications
  • Three IDN views Information Model (IDN-IM) Service Architecture (IDN-SA) Overlay Network (IDN-ON)
  • Information Model (IDN-IM) Information Model (IDN-IM) Generic information modelled in IDN is formalized as an aggregation of elementary data units, named “primitive information units (P.I.U.s)” Primitive information units contain generic data and metadata NodeTypes embed the primitive information-unit schema defining the application-level properties contained in the node A primitive information unit is a node in a directed graph
  • IDN-IM Information Unit e Link
    • An IDN-document structures information units and it is recursively composed of nodes related to each other only through “ aggregation links ”
    • Reference links express relations between distinct IDN-documents
    • Cross references (therefore creating cycles in the graph) between documents are handled by IDN applications. This is done through a third type of link, named IDN-Application-level link
  • IDN-IM: example – Identity Card (1/3)
    • Creation of an IC from linked data stores (structuring according to the responsibility principles)
    Indirizzo di Mario Rossi (CATASTO) Residente Mario Rossi (COMUNE RESIDENZA) Anagrafica di Mario Rossi (COMUNE NASCITA) <via,”roma”> <numero,”89”> ... <nome,”mario”> <cognome,”rossi”> ...
  • IDN-IM: example – Identity Card (2/3)
    • Creation of an IC from linked data stores (structuring according to the responsibility principles)
    tempo t 0 Carta Identità di Mario Rossi (COMUNE RESDENZA) tempo t 1 > t 0 Indirizzo di Mario Rossi (CATASTO) Residente Mario Rossi (COMUNE RESIDENZA) Anagrafica di Mario Rossi (COMUNE NASCITA) <via,”roma”> <numero,”89”> ... <nome,”mario”> <cognome,”rossi”> ... Dati Biometrici di Mario Rossi (SANITÀ) <impronta,”123....08”> <capelli,”neri”> <altezza,”175” >
  • IDN-IM: example – Identity Card (3/3)
    • Creation of an IC from linked data stores (structuring according to the responsibility principles)
    <numero,”AF89889”> RIFERIMENTO A ATTO DI NASCITA Indirizzo di Mario Rossi (CATASTO) Residente Mario Rossi (COMUNE RESIDENZA) Anagrafica di Mario Rossi (COMUNE NASCITA) Carta Identità di Mario Rossi (COMUNE RESDENZA) <via,”roma”> <numero,”89”> ... <nome,”mario”> <cognome,”rossi”> ... tempo t 1 > t 0 tempo t 0 Dati Biometrici di Mario Rossi (SANITÀ) <impronta,”123....08”> <capelli,”neri”> <altezza,”175” >
  • IDN-SA (Service Architecture)
  • IDN-SA layers (1/2)
    • Storage Interface (SI) : provides the data storage service
      • Storage systems often depend on the specific platform (hardware and software) and they can be native storage or legacy systems
      • It provides a REST-like uniform view over distributed data through URL names. It provides create, read, update and delete of URL-addressed resources
    • Replica Management (RM) : provides a delocalized view of resources and the resource replication service
      • Upper layer can handle only univocal and persistent identifiers
      • It associates several physical resources to the same identifier and these resources are “replicas” of the same logical information
  • IDN-SA (2/2)
    • Information History (IH) : manages primitive information units history
      • Navigation into the history is consequently allowed as a result of the services provided by this layer
    • Virtual Repository (VR) : is seen from the application as the container-repository of all primitive information units
      • It exposes the IDN APIs to the IDN-compliant Applications
      • It provides the maximum abstraction of structured information to the application
    • IDN-Compliant Applications : implement the context-dependent business logic and provide the user interface (they can be multi-tier applications)
  • IDN naminbg system
  • IDN three level naming system
    • IDN architecture provides a three-layer naming system :
      • Human Friendly Names (HFNs) are flexible and descriptive names easily interpretable by people
      • Uniform Resource Names (URNs) are defined in the IDN middleware environment and unambiguously, univocally and persistently identify the resources independently of their physical locations
      • Uniform Resource Locators (URLs) identify resource replicas and allow us to access to them
  • questions? [email_address]
  • References
    • http://webscience.org/
    • White, B. (2008, Novembre 9). The Emergence of Web Science. Bibliotheca Alexandrina. Source: webcast.bibalex.org/Presentations/Bebo91108.ppt
    • Nicola Lonzi (2009)
    • Zhuge, Hai and Xiaoqing, Shi (2008) The Web ecology. pp. 27-34. In: Proceedings of the First International Workshop on Understanding Web Evolution (WebEvolve2008), 22 Apr 2008, Beijing, China. ISBN 978 085432885 7. http://journal.webscience.org/31/1/WebEvolve2008Proc.PDF
    • Hendler, J., Shadbolt, N., Hall, W., Berners-Lee, T., and Weitzner, D. 2008. Web science: an interdisciplinary approach to understanding the web. Commun. ACM 51, 7 (Jul. 2008)
    • Riera, Daniel (2009) Web science: a new computer-related curriculum. In: Proceedings of the WebSci'09: Society On-Line, 18-20 March 2009, Athens, Greece.
    • AA.VV. SOCIAL SCIENCE: Computational Social Science Science 6 February 2009: vol. 323. no. 5915, pp. 721 - 723
    • Chris Bizer, Tom Heath, Kingsley Idehen, Tim Berners-Lee Workshop Introduction WWW 2008 Workshop: Linked Data on the Web (LDOW2008) April 22, 2008 Beijing, China
    • http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData
    • http://linkeddata.org/
    • Richard MacManus Web 3.0 or Not, There's Something Different About 2009, May 20, 2009 http://www.readwriteweb.com/archives/something_new_in_2009.php
    • Richard MacManus Linked Data is Blooming; ReadWriteWeb, May 2009 http://www.readwriteweb.com/archives/linked_data_is_blooming_why_you_should_care.php
    • Weaving the Web (Berners-Lee and Fischetti, 1999)
    • Jim Miller, &quot;One More Take on Identity,&quot; IEEE Internet Computing, vol. 13, no. 2, pp. 99-101, Mar./Apr. 2009, doi:10.1109/MIC.2009.41
    • Shneiderman, B. 2007. Web science: a provocative invitation to computer science. Commun. ACM 50, 6 (Jun. 2007)
    • Richard MacManus Understanding the New Web Era: Web 3.0, Linked Data, Semantic Web, ReadWriteWeb, May 14, 2009
    • Chris Bizer, Tom Heath, Kingsley Idehen, Tim Berners-Lee WWW 2008: Linked Data on the Web Workshop Introduction April 22, 2008 Beijing, China
    • Tim Berners-Lee's talk at TED about the Web of Data. http://www.ted.com/index.php/talks/tim_berners_lee_on_the_next_web.html
    • Alexander Korth The Web of Data: Creating Machine-Accessible Information, ReadWriteWeb, April 2009
    • Greg Boutin Tying Web 3.0, the Semantic Web and Linked Data Together - Part 2/3: Linked Data is a Medium http://www.semanticsincorporated.com/2009/05/tying-web-30-the-semantic-web-and-linked-data-together-part-23-linked-data-is-a-medium.html
    • Pirri, F., Pettenati M.C., Innocenti, S., Chini D, Parlanti D. and Ciofi L. Proceedings of WebSci'09: Society On-Line, InterDataNet: an Infrastructural Approach for the Web of Data Athens, Greece 18th–20th March, 2009
    • http://www.interdatanet.org/en/