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Università Politecnica delle Marche SEMEDIA Semantic Web and Multimedia Università Politecnica delle Marche SEMEDIA Semantic Web and Multimedia TOWARD.

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Presentation on theme: "Università Politecnica delle Marche SEMEDIA Semantic Web and Multimedia Università Politecnica delle Marche SEMEDIA Semantic Web and Multimedia TOWARD."— Presentation transcript:

1 Università Politecnica delle Marche SEMEDIA Semantic Web and Multimedia Università Politecnica delle Marche SEMEDIA Semantic Web and Multimedia TOWARD A SCALABLE MULTIMEDIA METADATA INFRASTRUCTURE USING DISTRIBUTED COMPUTING AND SEMANTIC WEB TECHNOLOGIES Patrizia Asirelli 1, Maria Grazia Di Bono 1, Massimo Martinelli 1, Ovidio Salvetti 1, Oreste Signore 1 1 Institute of Information Science and Technologies (ISTI), Italian National Research Council (CNR), via Moruzzi 1, Pisa, Italy Michele Catasta 2, Christian Morbidoni 2, Francesco Piazza 2, Giovanni Tummarello 2 2 SeMedia, Universita' Politecnica delle Marche, Ancona, Italy Semantic Digital Rights Management for Controlled P2P RDF Metadata Diffusion Roberto Garcia, Ph. D (1) Giovanni Tummarello, Ph. D (2) SEMEDIA Semantic Web and Multimedia (1) GRIHO – Human-Computer Interaction Research Group Universitat de Lleida, Spain (2) SEMEDIA – Semantic Web and Multimedia Group, Università Politecnica delle Marche, Italy Research Group on Human Computer Interaction and Databases

2 Scenario: P2P exchange of RDF information  Information is a “resource” itself, exchanged like in file sharing applications  A client might become a server at a later time  Information is expressed in RDF, strictly based on the W3C RDF Semantics specifications [1] (important! It would be much simpler otherwise ;-) ) [1] RDF Semantics - W3C Recommendation 10 February

3 Example: DBin (1)

4 Example: DBin (2)

5 Interconnected communities Users can join multiple groups:  they acquire knowledge to perform cross concerning queries  The diffuse information across groups which are interested in the same resources (e.g. Madonna as a singer, Madonna as an actress.. A new pic is relevant to both)  Seems a wonderfully new, open scenario  But restrictions are needed in some cases!

6 Idea: I’ll tell you if you sign this agreement  Deterministically derive HASHES for parts of the RDF Graph  Use Semantic Digital Right Management ontology to specify the policy and an OWL reasoner to verify  Give out the information if the other party agrees to put his/her digital signature on the RDF reppresentation of the POLICY +Information HASH

7 Minimum Self-contained Graph (MSG) Involves (Def) :An RDF statement involves a name if it has that name as subject or object. MSG (Def). Given an RDF statement s, the Minimum Self-contained Graph (MSG) containing that statement, written MSG(s), is the set of RDF statements comprised of the following:  The statement in question;  Recursively, for all the blank nodes involved by statements included in the description so far, the MSG of all the statements involving such blank nodes;

8 MSG surrounding a URI: example MSG(statement) (approx def). The “blank node closure” of the statement.

9 MSG decomposition of RDF Graphs   Theorem 1. If s and t are distinct statements and t belong to MSG(s), then MSG(t) = MSG(s).   Theorem 2. Each statement belongs to one and only one MSG.   Corollary 1. An RDF model has a unique decomposition in MSGs.

10 MSG decomposition of a graph: example

11 Deterministic, content based Identifiers for MSGs   MSGs are perfectly valid, standalone RDF graphs.   As such they can be processed with algorithms such as canonical serialization. [Carrol 2004]   The canonically serialized MSG is a binary file, as such it can be hashed   Given an hash function with appropriate characteristics, the resulting hash value forms a deterministic, content based identifier for the MSG itself   remote peers derive the same ID for the same MSG in their DB.   Sets of such IDs are used to identify the information covered in the licences.

12 RDF graph decomposition and identifiers MSG ID = MD5(Canonical(MSG)) = 45FA76B61FC0 Graph MSGID list = Sort (MSG ID 1, MSG ID 2,..) Graph ID= Hash(MSGID)

13 RDF/MSG decomposition applications (1)   a graph can be incrementally and differentially (!) transferred between two parties one MSG at a time.   Distributed P2P scenario : RDFGrowth Algorithm [1]   1 to 1 efficient Syncronization: RDFSync Algorithm (new!) RDFSync algorithm Traffic VS delta changes [1] G. Tummarello, C. Morbidoni, J. Petersson, F. Piazza, M. Mazzieri, P. Puliti, "Toward widely deployable Semantic Web P2P: tools, definitions and the RDFGrowth algorithm", Workshop on Semantic Web Technology for Mobile and Ubiquitous Applications at ISWC 2004, November 2004, Hiroshima, Japan.

14 mus:Band mbz:artistid=15290 MD5: mus:Song mus:is_part_of mus:file rdf:type mus:plays rdf:statement IdKtR...j4c= rdf:type dbin:Base64sigvalue rdf:subject rdf:predicate rdf:object dbin:X509Certificate G. Tummarello, C. Morbidoni, P. Puliti, F. Piazza, "Signing individual fragments of an RDF graph", 14th International World Wide Web Conference WWW2005, Poster track, May 2005, Chiba, Japan "Signing individual fragments of an RDF graph" RDF/MSG decomposition applications (2) Signing a Minimum Selfcontained Graph (MSG)

15  This paper!  This paper!  A procedure to serve information in RDF subject to a previous agreement on the use of that very information RDF/MSG decomposition applications (3)

16 The exchange procedure A client R requests information from a server S   R makes a request to S.   S receives the request, creates the RDF for the answer, calculates its MSG IDs and uses them in a new RDF file which defines its usege restrictions (see later). Sends this new RDF, from here on called proposal, to R. Optionally: signs the proposal so to provide S with the guarantee that if agreed, the answer will actually be provided within the specified terms   R receives the proposal and, if it agrees to the terms, signs it and returns it to S. Optionally: thanks to the properties of MSGs, R can check if the answer correspond to information which is already locally known. In this case R could drop the request as not interesting, or proceed, e.g., in case it is important for R to prove that the information was in fact legally acquired.   S receives the signed proposal, stores it and replies with the answer computed in 2). Optionally: the signed proposal might be countersigned to allow R to prove that the information was obtained by legal means.

17 Semantic Digital Rights Management to define usage restrictions  ISO/IEC MPEG-21: about DRM on multimedia  components: Rights Expression Language (REL) which uses terms explained in the Rights Data Dictionary (RDD)  Lack of formal semantics!  the Copyright Ontology (OWL DL based) [1]  As it deals with Reproduction rights and it is in OWL, fits great with this our purpose! [1] García, R.: "A Semantic Web Approach to Digital Rights Management". PhD Thesis, Technologies Department, Universitat Pompeu Fabra, Barcelona, ES,

18 An example licence instance Licences are classes To check an action: create an instance and use a DL classifier!

19 Conclusions  A simple applications of RDF decomposition  OWL based copyright ontology fits the task and stays in the domain of Semantic Web Tools  To make it into a “legally binding” exchange mechanism, specific laws might be needed

20 Thanks for your attention SEMEDIA Semantic Web and Multimedia Research Group on Human Computer Interaction and Databases


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