Tutorial on Semantic Digital Libraries (ESWC'2007)

Tutorial – Semantic Digital Libraries - Introduction - Sebastian R. Kruk , Bernhard Haslhofer, Philipp Nußbaumer , Sandy Payette, Tomasz Woroniecki

Tutorial overview Who we are Sebastian R. Kruk, DERI Galway – Ireland Bernhard Haslhofer, University of Vienna - Austria Phillip Nußbaumer, Research Studios - Austria Sandy Payette, Cornell University – USA Tomasz Woroniecki, DERI Galway – Ireland Today we want to give you a brief introduction to the Semantic Web, and show how SW is related to digital libraries present existing semantic digital library systems discuss the current problems and future directions of semantic digital libraries and get feedback from you After this tutorial you will know what is the semantic digital library system existing solutions in various degrees of detail how to run semantic digital library solutions on your machine

Tutorial Schedule Comparison and the future of SemDL 12:15 – 12:30 Existing solutions - JeromeDL 9:45 – 10:30 Conclusions, discussio n 16: 45 - 17: 3 0 Lunch break 12:30 – 1 4 : 0 0 Hands-on session (part I) 14:00 – 15: 3 0 Coffee break 15: 3 0 – 1 6 : 0 0 Hands-on session (part II) 1 6:0 0 – 16: 45 Existing Semantic Digital Libraries solutions 1 1:00 - 12: 15 Coffee break 10:30 – 1 1:00 Introduction to Semantic Digital Libraries 9:00 - 9 : 45 Time

Outline Introduction to Semantic Web Semantic Digital Libraries

The Semantic Web – A Brief Introduction Current Web vs. Semantic Web? An extension of the current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. [Tim Berners-Lee] Current Web was designed for humans, and there is little information usable for machines Was the Web meant to be more? Objects with well defined attributes as opposed to untyped hyperlinks between Internet resources A network of relationships amongst named objects, yielding unified information management tasks What do you mean by “Semantic”? the semantics of something is the meaning of something Semantic Web is able to describe things in a way that computers can understand

The Semantic Web – A Brief Introduction Where are we in the “S emantic W eb layer cake”? You Are Here!

The Semantic Web – A Brief Introduction The challenge for the Semantic Web The Semantic Web can’t work all by itself For example, it is not very likely that you will be able to sell your car just by putting your RDF file on the Web Need society-scale applications: Semantic Web agents and/or services, consumers and processors for semantic data, more advanced collaborative applications

The Semantic Web – What is RDF ? Describing things on the S emantic W eb RDF (Resource Description Framework) a data format for describing information and resources, the fundamental data model for the Semantic Web Using RDF, we can describe relationships between things like: A is a part of B or Y is a member of Z and their properties ( size , weight , age , price …) in a machine-understandable format where each thing has a RDF graph-based model delivers straightforward machine process ing Putting information into RDF files makes it possible for “scutters” or RDF crawlers to search , discover , pick up , collect , analyse and process information from the Web

The Semantic Web – What is RDF ? A simple RDF example Statement: “ Stefan Decker is the creator of the resource (web page) http://www.stefandecker.org ” Structure: Resource (subject) http://www.stefandecker.org Property (predicate) http://purl.org/dc/elements/1.1/creator Value (object) “ Stefan Decker ” Directed graph: http://www.stefandecker.org dc:creator Stefan Decker

The Semantic Web – How RDF can help us? How RDF can help us? identify objects establish relationships express a new relationship  just add a new RDF statement integrate information from different sources  copy all the RDF data together RDF allows many points of view

What is an Ontology? „ An ontology is a specification of a conceptualization.“ Tom Gruber, 1993 Ontologies are social contracts Agreed, explicit semantics Understandable to outsiders (Often) derived in a community process Ontology markup and representation languages: RDF and RDF Schema OWL Other: DAML+OIL , EER , UML , Topic Maps , MOF , XML Schemas The Semantic Web – Ontologies and Schemata

Defines small vocabulary for RDF: Class, subClassOf, type Property, subPropertyOf domain, range Vocabulary can be used to define other vocabularies for your application domain The Semantic Web – RDF Schema Person Student Researcher subClassOf subClassOf Jeen type hasSuperVisor domain range Frank type hasSuperVisor

OWL – The Web Ontology Language Owl took Christopher Robin’s notice from Rabbit and looked at it nervously. He could spell his own name WOL , and he could spell Tuesday so that you knew it wasn’t Wednesday, and he could read quite comfortably when you weren’t looking over his shoulder and saying "Well?" all the time... provides a vocabulary for defining classes, their properties and their relationships among classes. The Semantic Web – OWL owl :disjointWith s s s s Animal Herbivore Carnivore Omnivore Based on Description Logics OWL is a W3C Recommendation

The Semantic Web – Applications Semantic Web cannot be and is not only a set of recommendations Semantic Web is becoming reality by applications that support it and are based on it Enabling technologies: RDF Storages: Sesame, Jena, YARS Reasoners: KAON, Racer Editors: Protege, SWOOP, MarcOnt Portal End-User applications: Semantic wikis: Makna, SemperWiki Semantic blogs Semantic digital libraries

What is a Semantic Digital Library? Semantic digital libraries integrate information based on different metadata, e.g.: resources, user profiles, bookmarks, taxonomies – high quality semantics = highly and meaningfully connected information provide interoperability with other systems (not only digital libraries) on either metadata or communication level or both – RDF as common denominator between digital libraries and other services delivering more robust, user friendly and adaptable search and browsing interfaces empowered by semantics

Old days of hard-copy books Library: Archive (storage space) Bibliographic cards (metadata) Librarian (interface) Pros: Someone to talk to, to understand us, to explain, help in searching Cons: Based on physical location Libraries are not connected – we have to visit every place

Yesterday of digital books Digital library Database and archive (storage) Digital bibliographic descriptions (metadata) Full-text search (interface) Pros: Content accessible online Federations of libraries – visit less places Cons: Lonely user - n o one to talk to, we need to find the right keywords, what if we do not know them (“man without an ear” paintings example) Still many problems with interconnecting (different) libraries

Today of interconnected content Semantic Digital Libraries Database and archive (storage) Semantic bibliographic description (interconnected metadata) Search and browsing on ontologies (interface) Pros: Search and browsing based on semantics can help in substituting the librarian It is easier to interconnect heterogeneous libraries (RDF as common denominator) Cons: Semantics created from legacy formats – still hard to capture by most of average users

Tomorrow of social media Social Semantic Digital Libraries Database and archive (storage) Bibliographic descriptions with annotations provided by users (metadata) Collaborative search and browsing (interface) Pros: Users contribute to the classification process Users can understand community driven annotations Users enhance digital content using blogs, wikis on the side Cons: Not everyone is convinced

How are Semantic Digital Libraries different? Semantic digital libraries extend digital libraries by describing and exposing its resources in a machine ‘understandable’ way resources can be contents, digital artefacts organization of objects (e.g. collections) users, user communities controlled vocabularies, thesauri, taxonomies expose the semantics of their metadata in terms of an ontology defined using a formal language deliver mediation services for communication with other systems

Semantic Web Technologies for Digital Libraries? Metadata is the key concept the Web does not have metadata the idea of a Semantic Web is nice but difficult to implement many digital libraries do have metadata in place we simply must make them available in a machine understandable format the Semantic Web provides the format: RDF

Semantic Web Technologies for Digital Libraries? Knowledge in bibliographic records Digital Libraries already have controlled vocabularies, taxonomies or even ontologies in place the challenge is to model this knowledge in a machine understandable way the Semantic Web provides ontology language s: RDF Schema OWL SKOS

A Sample Bibliographic Record Copyright 2000 The J. Paul Getty Trust & College Art Association, Inc . Terms taken from Controlled Vocabularies Vincent van Gogh; painter: Gogh, Vincent van (Dutch painter, 1853-1890) Creation-Creator/Role J. Paul Getty Museum Current Location-Repository Name irises , nature , soil , etc. Subject-Matter 1889, earliest: 1889, latest: 1889 Creation-Date Irises Title paintings Object/Work type Paintings Classification

Knowledge Organization Systems tools that present the organized interpretation of knowledge structures semantic tools - meaning of words and other symbols as well as (semantic) relations between symbols and concept organize information and promote knowledge management Examples: classification and categorization schemata (organize materials at a general level) subject headings (provide more detailed access) authority files (control variant versions of key information such as geographic names and personal names) highly structured vocabularies, such as thesauri traditional schemes, such as semantic networks and ontologies

Taxonomy of Knowledge Organization Systems Term Lists Authority files ( FOAF ) Glossaries Dictionaries Gazetteers Classifications and Categories ( DMoz ) Subject headings Classification schemes Taxonomies Categorization Schemes. Relationship Lists Thesauri ( WordNet, MeSH ) Semantic networks Ontologies (Hodge, 2000)

Understanding Knowledge Organization Systems controlled vocabulary - a list of terms that have been enumerated explicitly taxonomy - a collection of controlled vocabulary terms organized into a hierarchical structure. formal ontology – a controlled vocabulary expressed in an ontology representation language. This language has a grammar for using vocabulary terms to express something meaningful within a specified domain of interest. meta-model - an explicit model of the constructs and rules needed to build specific models within a domain of interest. A valid meta-model is an ontology, but not all ontologies are modeled explicitly as meta-models. as a set of building blocks and rules used to build models as a model of a domain of interest, and as an instance of another model.

Simple Knowledge Organization Systems (SKOS) basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, 'folksonomies ', other types of controlled vocabulary core concepts: narrower and broader isSubjectOf and subject ; isPrimarySubjectOf and primarySubject member and Collection; memberList and OrderedCollection related and semanticRelation note, definition; altLabel and prefLabel ; symbol and altSymbol

Benefits of Semantic Digital Libraries Problems of today’s libraries rapidly growing islands of highly organized information How to find things in a growing information space? is it enough to have a full-text index (à la Google)? typical “end-users” versus “expert users” converging digital library systems e.g. uniform access to Europe’s digital libraries and cultural heritage

Benefits of Semantic Digital Libraries T he two main benefits of Semantic Digital Libraries new search paradigms for the information space Ontology - based search / facet search Community-enabled browsing providing interoperability on the data level integrating metadata from various heterogeneous sources Interconnecting different digital library systems

Searching the Sample Bibliographic Record Full-text search “ Paintings ” AND “ Van Gogh ” AND “ flowers ”  no result Semantic query if the knowledge that “ irises ” are “ flowers ” is modeled in an ontology (e.g. subclass-hierarchy) we can query for all “ Paintings ” by “ Van Gogh ” with subject “ flowers ” and retrieve also the picture with subject “ irises ” Copyright 2000 The J. Paul Getty Trust & College Art Association, Inc . Vincent van Gogh; painter: Gogh, Vincent van (Dutch painter, 1853-1890) Creation-Creator/Role J. Paul Getty Museum Current Location-Repository Name irises , nature , soil , etc. Subject-Matter 1889, earliest: 1889, latest: 1889 Creation-Date Irises Title paintings Object/Work type Paintings Classification

Semantic Digital Libraries and Existing DL Systems how to handle the legacy (meta-)data problem lifting existing (meta-)data to a semantic level simple solutions like MARC21  DublinCore complex ontologies like MarcOnt Ontology for capturing concepts from different standards legacy libraries expose their metadata via well established protocols - the metadata can be imported into semantic DLs semantic DLs can play a role of integration champions in the information retrieval process in heterogeneous networks: OAI-PMH Z39.50 Dienst

Application A reas for Semantic Web T echnologies Thesauri & Controlled Vocabularies qualified DublinCore DMoz, DDC-based taxonomies SKOS, WordNet and other thesauri Schema Mappings / Crosswalks MarcOnt Ontology – aims to cover concepts from MARC21, BibTeX and DublinCore MarcOnt Mediation Services – an open mediation framework between common legacy metadata standards Metadata Integration RDF as a common data model for integrating metadata from various autonomous and heterogeneous data sources OWL for modeling the data source’s semantics SPARQL as a common query language

Semantic DL as Evolving Knowledge Space In state-of-the-art digital libraries users are consumers Retrieve contents based on available bibliographic records Recent trends: user communities Connetea Flickr In Semantic digital libraries users are contributers as well Tagging (Web 2.0) Social Semantic Collaborative Filtering Annotations Semantic Digital libraries enforce the transition from a static information to a dynamic (collaborative) knowledge space

Existing Semantic Digital Library Systems JeromeDL a social semantic digital library makes use of Semantic Web and Social Networking technologies to enhance both interoperability and usability BRICKS aims at establishing the organizational and technological foundations for a digital library network in order to share knowledge and resources in the cultural heritage domain. FEDORA delivers flexible service-oriented architecture to managing and delivering content in the form of digital objects SIMILE extends and laverages DSpace, seeking to enhance interoperability among digital assets, schemata, metadata, and services

Tutorial – Semantic Digital Libraries - Existing Semantic Digital Libraries Solutions - Sebastian R. Kruk , Bernhard Haslhofer, Philipp Nußbaumer , Sandy Payette, Tomasz Woroniecki

Tutorial 7 – Semantic Digital Libraries - Existing Semantic Digital Libraries Solutions – JeromeDL Sebastian R. Kruk , Tomasz Woroniecki

Outline JeromeDL - Motivation and Overview JeromeDL - Architecture and Ontologies JeromeDL - Semantic Services JeromeDL - Social Services JeromeDL - Semantics in Use

JeromeDL - Introduction Joint effort of DERI, National University of Ireland, Galway and Gdansk University of Technology (GUT) Distributed under BSD Open Source license Digital library build on semantic web technologies to answer requirements from: librarians, scientists and everyone.

Motivation How to integrate and search information from different bibliographic sources? How to share and interconnect knowledge among people?

JeromeDL – Motivations Use Cases Librarians: support for rich metadata (MARC21) in uploading resources, accessing bibliographic information and searching persistent identifiers Scientists: easy publishing (designed as a institute/university digital library) creating hierarchical networks of digital libraries support for accessing, sharing and searching using bibliography metadata (BibTeX) Everyone: simple search (incl. natural language queries) community-aware information sharing and browsing, support for interationalization

JeromeDL - Motivations Support for different kinds of bibliographic medatata, like: DublinCore , BibTeX and MARC21 at the same time. Making use of existing rich sources of bibliographic descriptions (like MARC21) created by human. Supporting users and communities: user s ha ve control over their profile information ; community-aware profiles are integrated with bibliographic descriptions support for community generated knowledge Delivering communication between instances: P2P mode for searching and users authentication Hierarchical mode for browsing

JeromeDL – Architecture Resources and annotations repository Middleware: query processing community space resources management User interface agents: Communication to the outside world Administrative interface

Bibliographic Description in JeromeDL <?xml version ="1.0" encoding ="UTF-8" ?> <rdf:Description rdf:about ="http://...id=828374765" > <dc:title> JeromeDL - Adding Semantic Web Technologies to DLs </dc:title> <dc:creator> Sebastian Kruk </dc:creator> <dc:description> In recent years... </dc:description> </rdf:Description> 01450cas 922004331i 450000100...019c19329999gw qr|p| ||||0 |0ger | a0044-2992 9a200412140219bVLOADc200404071525dvkulc200310071018dvbjc200303101205dkopumky200209211341zVLOAD aGD U/MPcGD U/MPdGD U/MFdGD U/KKsdWR O/EJ0 ager1 aZ. Kunstgesch. 0aZeitschrift für Kunstgeschichte00aZeitschrift für Kunstgeschichte.18aZfK aMünchen ;aBerlin :bDeutscher Kunstverlag,c1932-. c26-29 cm. aKwart.0 a1 Bd. (Juni 1932)-. aOpis na podst.: LCC. aW 1932 założycielami czasopisma byli Wilhelm Waetzoldt i Ernst Gall.... These all can be represented in RDF @ InProceedings { jeromedexa2005, author = "Sebastian Ryszard Kruk and ... ", title = "{JeromeDL - Adding Semantic ...}", booktitle = "{In Proceedings to DEXA 2005}", year = 2005}

Structure ontology in JeromeDL

Bibliographic (MarcOnt) Ontology in JeromeDL

Community-aware (FOAFRealm) ontology

Metadata and Services in JeromeDL

Semantic Metadata and Services

MarcOnt Initiative – Overview Motivation: Provide set of tools for collaborative ontology development MarcOnt Initiative goals: Create a framework for collaborative ontology improvement (E-learning) Provide domain experts with tools to share their knowledge Offer tools for data mediation between different data formats

MarcOnt Portal and MarcOnt Ontology MarcOnt Ontology: Central point of MarcOnt Initiative Translation and mediation format Continuos collaborative ontology improvement Knowledge from the domain experts MarcOnt Portal (source of knowledge): Suggestions Annotations Versioning Ontology editor

MarcOnt Mediation Services for Legacy Metadata Format translation RDF Translator Format co-operation MarcOnt Mediation Services

Browsing the data graph – why? The search does not end on a (long) list of results The results are not a list (!) but a graph „ Lost in hyperspace” A need for unified UI and services for filter/narrow and browse/expand services Share browsing experience – navigate collaboratively

Browsing the data graph – how? Defines REST access to services and their composition Basic services: access, search, filter, similar, browse, combine Meta services : RDF serialization, subscription channels, service ID generation , Context services : manage contexts, manage service calls/compositions in the context, lists contexts Statistics services : properties, values, tokens

Browsing the data graph JeromeDL exploits interconnected data

Browsing the data graph … to allow browsing

Social Services in JeromeDL Involve users into sharing knowledge Blogs – comments and discussions about documents and resources Tagging – collaborative classification Wikis – collaboratively edited additional descriptions, such as summaries and interesting facts Preserve knowledge for future use Users can learn from experience of others instantly Recommend new, interesting resources based on users’ profiles

FOAF - Describing Social Networks FOAF - Stands for Friend-of-a-Friend Defines properties for a person (but it does not have to be a person, can be an “agent”) Does not only have to contain one person per file Can build a network of people with foaf:knows links FOAF can be easily extended to meet requirements, as in the case of FOAFRealm for identity management…

Identity management with FOAFRealm Identity defined with extended FOAF metadata Policies expressed by social networking Distance between owner and requester Friendship level between owner and requester, calculated across digraph of social network Support for single registration and sign on Distributed identity management with HyperCuP (“D-FOAF”) FOAFRealm is currently implemented as a plugin for Tomcat (Realm/Valve implementation), with PHP and .NET versions coming soon

Social Semantic Collaborative Filtering Why? The bottom-line of acquiring knowledge: informal communication (“word of mouth”) How? Everyone classifies (filters) the information in bookmark folders ( user-oriented taxonomy ) Peers share (collaborate over) the information ( community-driven taxonomy ) Result? Knowledge “flows“ from the expert through the social network to the user System amass a lot of information on user/community profile (context)

Social Semantic Collaborative Filtering Problems? The horizon of a social network (2-3 degrees of separation) How to handle fine-grained information (blogs, wikis, etc.) Solutions? Inference engine to suggest knowledge from the outskirts of the social network Support for SIOC metadata : SIOC browser in SSCF Annotations and evaluations of “local” resources

What is S ocial S emantic C ollaborative F iltering? Goal: t o enhance individual bookmarks with shared knowledge within a community Users annotate catalogues of bookmarks with semantic information taken from DM oz or WordNet vocabularies Catalogs can include ( transclusion ) friend's catalogues Access to catalogues can be restricted with social networking-based polices SSCF delivers: Community-oriented, semantically-rich taxonomies Information about a user's interest Flows of expertise from the domain expert Recommendations based on users previous actions Support for SIOC metadata

Social Semantic Collaborative Filtering foaf:knows xfoaf:include xfoaf:bookmark

Social Networks in Digital Libraries Resource xfoaf:Annotation user_C creator_B foaf:knows marcont:hasCreator creator_A foaf:knows foaf:knows xfoaf:Directory user_D xfoaf:owns xfoaf:linksTo xfoaf:isIn

Support for online communities in SSCF

JeromeDL – Delivering Semantic Content Providing semantic annotations during uploading process: open module for handling any taxonomies keywords based on WordNet and free tagging defining structure of resources in the JeromeDL ontology Lifting legacy metadata to MarcOnt ontology Community maintained annotations social semantic collaborative filtering semantic descriptions based on the FOAF metadata

JeromeDL – Semantic Information In Use Searching: Keyword-based search with semantic query expansion Semantic search: Direct RDF quering Natural language templates Browsing Exibit MultiBeeBrowse Sharing: Social Semantic Collaborative Filtering Semantically Interlinked Online Communities Heterogeneous communication: Bibster , A9 , OAI -PMH

Filtering Resources in JeromeDL

Information Retrieval in JeromeDL Fulltext Index Structure Repository MarcOnt Repository Resources’ Content FOAFRealm Repository (typed) keywords RDF & NL Query OpenSearch RSS collaborative filtering types translation semantic query expansion RDF Repositories Secure Snapshot local interface distributed interface

Networks of Digital Libraries ELP (Extensible Library Protocol) implementation communication within JeromeDL network adapters for communication with other networks D-FOAF integration (distributed user profile management) single sign on and single registration within D-FOAF network HyperCuP integration (scalable P2P network) Independent ELP network entry point: http://search.jeromedl.org/ 0 0 1 1 0 0 1 1 0 2 2 2 2

Tutorial – Semantic Digital Libraries - Existing Semantic Digital Libraries Solutions – BRICKS Bernhard Haslhofer University of Vienna Austria Philipp Nußbaumer Research Studios Austria

Outline BRICKS Overview BRICKS Components BRICKS Applications

What is BRICKS? A software infrastructure for building digital library networks Transparent access to distributed resources Multilinguality Easy installation & maintainance A set of end-user applications Network & content management Web 2.0 tagging/annotations Domain specific applications A business model Open source, platform independent Low cost infrastructure User communities  sustainability

BRICKS Architecture A decentralized P2P network Avoid central coordination Highly Scalable, increased reliability Minimized maintainance costs Each P2P Node is a set of SOA components Web Service interface Platform independent Flexible composition Components for Storing, accessing and protecting digital objects (Semantic) search & browsing P2P commmunication

Collection Manager Single access point for all content and metadata related operations (local and remote) Physical Collection Similar to folder/directory hierarchy in a file system Bound to a single BNode Each digital content object belongs to exactly one collection Logical Collection Virtual folder for organizing content items independent of their physical location Links to content items from various physical collections on different BNodes A content item might belong to many of them Stored Query similar to database views

Content Manager Two ways to handle content in BRICKS Stored locally at site of a member party, accessed via URL Stored within BRICKS Based on Java Content Repository (JCR) Provides a meta-content model Re-use of existing content models Use standard models

Metadata Manager Metadata descriptions  RDF Suitable for any application scenario Express relationships between objects React to changes without changing the model Schema defintions  OWL No fixed schema Extensible (e.g. Application profiles) Semantic concepts instead of schematic strucutures SPARQL Metadata queries over ontology concepts Queries for graph patterns

Security Manager Transparently invoked by the Framework any service call is checked Context-aware policies based on RBAC (via XACML rules) supporting Roles, Groups, at DLObject level Permission declaration through Javadoc @tags Federated identity is managed through an adapted version of OpenSAML Reputation-based Trust calculation integrated Web-based GUI for security configuration

Digital Rights Management DRM Component Support for licenses based on MPEG-21 REL license declaration standard Generic API for the integration of commercial DRM systems Watermarking Open-source watermarking tool for images Other tools can be integrated BRICKS Store web application for commercial content Creative Commons support for other content in BRICKS

Application: BRICKS Workspace What does it demonstrate? A web application (thin client) accessing BRICKS Foundation services Web 2.0 image annotations Reference application Primary customers General end-users (citizens) Application developers Technology Struts based interface to the BCH

Application: BRICKS Desktop What does it demonstrate? A rich client application accessing BRICKS foundation services Direct access to the BCHN Primary customers Expert end-users (researchers, educators) Application developers Technology Eclipse based rich client interface

Application: Annotation Tool What does it demonstrate? Tool which allows end-users to annotate images Creation of annotation threads Supervised Annotations Primary customers End-users Institutions with large image collections Technology Web Application

Application: Online Exhibition Authoring Tool What does it demonstrate? Creating and publishing online exhibitions using contents that is available in the BRICKS network Primary customers? Expert end-users (curators) Technology Web Application

Application: Archeological Finds Identifier What does it demonstrate? A web application for comparing findings (e.g. ancient coins) with objects in reference collections Application of complex domain ontology (CIDOC-CRM) Map visualization of GIS-Metadata Primary customers? Museum curators, archaeologists, students, amateurs, Technology Struts based interface

References BRICKS Community Web Site http://www.brickscommunity.org/ Main Contact: silvia.boi@metaware.it Related (de-facto) standards Resource Description Framework (RDF) http://www.w3.org/TR/rdf-primer/ OWL Web Ontology Language (OWL) http://www.w3.org/TR/owl-guide/ SPARQL http://www.w3.org/TR/rdf-sparql-query/ Java Content Repository (JCR) http://www.jcp.org/en/jsr/detail?id=170 Tools and Libraries Jackrabbit http://jackrabbit.apache.org/ Jena Semantic Web Framework http://jena.sourceforge.net/

Tutorial – Semantic Digital Libraries - Existing Semantic Digital Libraries Solutions – Fedora Sandy Payette Director, Fedora Project Cornell University

Outline Fedora Examples: PLoS ONE and National Science Digital Library

Fedora Semantic Digital Libraries enable … Scholarly and Scientific Workbenches “ Web 2.0” Collaborative Repositories Museum Exhibits with Lesson Plans Linking Data and Publications blog and wiki

The Fedora Project Fedora F lexible E xtensible D igital O bject R epository A rchitecture History Cornell Research (1997-2002) DARPA and NSF-funded research and reference implementations Distributed, Interoperable Repositories (experiments with CNRI) Open Source Project (2002-present) Andrew W. Mellon Foundation (2002-2009) Joint development by Cornell University and University of Virginia Transitioning into non-profit organization (Fedora Commons 501c3)

Fedora - Technology Integration Semantic Repository Enterprise Preservation Information Networks Contextualization Relationships Query Inference Workflow Messaging Transactions Replication Digital Objects Manage Access Versioning Storage Integrity Check Monitoring Alerting Migration

Fedora Digital Objects Flexible object model can support Documents, articles, journals Electronic Scholarly Texts Digital Images Complex multimedia publications Datasets Metadata Learning objects More… Create “networks” of objects using RDF Define object relationships and other properties via RDF Collection/member; part/whole; etc.

RDF in the Fedora Digital Object Model

Motivations: Fedora and Semantic Technologies A natural model for exposing repository as network of objects Object-to-object relationships Relationships to external entities Query the graph; traversal to discover related stuff Indexing based on generalizable data model Graph-based data model is a common reduction Avoid fixed schema problems and metadata mud wrestling Extensible enrichment of object descriptions Keep overlaying statements from multiple ontologies Organic evolution Powerful queries and inference for repository management Transitive relationships among objects Dependency analysis; Detection/Extraction of sub-graphs Provenance of disseminations

Digital Objects contain their RDF assertions Assert relationships from Fedora base ontology Collection – member Whole – part Equivalence Description Of More… Assert relationships/properties from community ontologies isAnnotationOf isRecommendedBy isCertifiedBy More ….

Example: Digital Objects with “compositional semantics”

Use Case: scholarly objects and annotation in the humanities musuem and library objects commercial web content scholarly objects URI-100 xx:recommends URI-55 yy:certifies

3 Objects – 3 RDF “Relationships” Datastreams <rdf:Description rdf:about="info:fedora/uva:pid-11> <ais:annotationOf rdf:resource=“info:fedora/uva:pid-3”/> </rdf:Description> </rdf:RDF> <rdf:Description rdf:about="info:fedora/uva:pid-3"> <uva:hasPartLetter rdf:resource="info:fedora/uva:pid-2"/> <uva:hasPartDiagram rdf:resource="info:fedora/uva:pid-1"/> </rdf:Description> </rdf:RDF> <rdf:Description rdf:about="info:fedora/uva:pid-10> <ais:providesContextFor rdf:resource=“info:fedora/uva:pid-3”/> </rdf:Description> </rdf:RDF>

NOT the core object store - RI is a graph-based index of the repository Automatic, incremental indexing into triplestore Search/query the repository via Fedora RI Query Interface Fedora RDF-based Resource Index (RI) RDF Index of Repository RDF datastream Fedora object properties DC datastream Digital Object Store

RI Graph - view 1 (abbreviated) …

RI Graph - view 2 (abbreviated) …

RI Implementation: The Triplestore Challenge Scalability Few triplestores perform well for 100M+ triples Kowari – we tested to 180M triples MPTStore – we tested to 250M triples Performance Jena - easy to get out of memory Sesame Native - slow for complex queries Kowari Fast queries and full-featured query language (iTQL) Instability and corruption problems MPTStore Very fast for SPO queries (limited support for complex queries) Add/modify significantly faster than Kowari Mulgara Fork of Kowari; complex queries; models; inference Major bug fixes to fix stability and corruption problems XA2 transactions Claims support for billions of triples

Fedora Repository – Notable Features Generic Digital Object Model Automatic content versioning and audit trail Web Service Interfaces (REST and SOAP) Authentication Authorization Flexible fine-grained policy enforcement Built-in support for Extensible Access Control Markup Language (XACML) RDF Each object contains its own RDF assertions Repository-wide index of all object (RDF triplestore) Self-healing – rebuild repository via digital object source files

Outline FEDORA Examples: PLoS ONE and National Science Digital Library

PLoS ONE and Topaz Open Access Publishing and Collaboration

NSDL: Semantic Digital Library Architecture NDR

What is NSDL committed to? NSDL 2.0 as a platform for a collaborative, contributory semantic digital library Supporting communities across the full range of science, technology, engineering and mathematics research, learning and education Supporting the creation of context around library resources to enhance discovery, use, and understanding

NSDL Semantic Digital Library repository requirements Supports storing both content and metadata Allows arbitrary relationships among resource and metadata objects: organization, annotation, citation Accessible through web service architecture of remixable data sources and transformations

NSDL Data Repository (NDR) Implemented in Fedora 2.2 with MPTStore Moderately large 4.7 million digital objects 250 million RDF triples Digital Objects Resources Metadata Agents Metadata providers Aggregators REST API and authentication In production at nsdl.org

NSDL as Semantic Digital Library : collaboration, context, and contribution Platform: Fedora repository and services Applications: Solution 1: Leverage the existing successful models: blogs, wikis, bookmarking/tagging Solution 2: Leverage the existing software: WordPress, MediaWiki, Connotea, Sakai Solution 3: Engage with partners and the broader community to build applications to the platform

Expert Voices - Blogs on top of Fedora

Expert Voices NSDL Blogosphere (http://expertvoices.nsdl.org) Topic-based discussions (e.g. forensics) linked to related library resources A way for NSDL community members to become NSDL contributors of resources, questions, reviews, annotations, metadata Technology: Wordpress-based multi-user multi-blog application (open source, plug-in architecture) Owner controls publication of entries as NSDL resources and visibility of comments (NSDL middleware and Shibboleth) Blog Entries: linked references to NSDL library resources

NSDL 2.0 – The Whole Ecosystem … Protocol: OAI-PMH HTTP REST NDR API STEM Collections Search Service Archive Service Fedora-based NDR

NSDL 2.0 and the Semantic Web NSDL 2.0 applications situate resources in context, aiding both discovery and use Users become contributors, adding new resources, ratings, annotations, and organizational structure – frequently as a side effect of using the library Fedora-based semantic web technology organizes resources, ties context to content, maintains provenance, enables discovery, empowers the user, and powers the library

Fedora Web Site: www.fedora.info Community Open Source Tools: www.fedora.info/tools Fedora Wiki: www.fedora.info/wiki Tutorial: : http://openarchives.org/fedora/ESWC-Fedora.zip

Tutorial – Semantic Digital Libraries - Comparison and the Future - Sebastian R. Kruk , Bernhard Haslhofer, Philipp Nußbaumer , Sandy Payette, Tomasz Woroniecki

Outline SIMILE – short overview Comparison between existing solutions Digital Libraries and Social Web Semantic Digital Libraries Scenarios

SIMILE – Introduction SIMILE - Semantic Interoperability of Metadata and Information in unLike Environments joint project conducted by the W3C, HP, MIT Libraries, and MIT's Lab for Computer Science. extends and laverages DSpace, seeking to enhance interoperability among digital assets, schemata, metadata, and services Goal: Make metadata interoperability easier for digital libraries by providing useful tools for browsing, searching and mapping heterogeneous metadata in RDF [ MacKenzie Smith, MIT Libraries ]

SIMILE – Introduction SIMILE : enhances interoperability and provides end-user services: for digital assets, arbitrary schemata, metadata and services. across distributed individual, community, and institutional stores. though the application of RDF and semantic web techniques. implements a digital asset dissemination architecture based upon web standards

SIMILE – Delivered Components Tools for Metadata Managers Gadget - XML inspector RDFizers - Batch tools to transform existing XML data into RDF Solvent - Firefox extension for Javascript screen scraping Welkin - Graphical tool to inspect/edit RDF graph Tools for End-Users Longwell - Web-based RDF faceted metadata browser Piggy Bank - Firefox extension for personal information management of metadata in RDF Semantic Bank - Web-based server that allows data publishing and sharing by individuals, groups, or communities Exibit - lightweight structured data publishing framework Timeline - AJAXy widget for visualizing time-based events

RDFizers - T ransform XML data into RDF RDFizers - Transform XML data into RDF: tools that allow to transform existing data into an RDF representation List of RDFizers in SIMILE: MARC/MODS  RDF OAI-PMH  RDF OCW  RDF EMail  RDF BibTEX  RDF Flat  RDF Weather  RDF Java  RDF Javadoc  RDF Jira  RDF Subversion  RDF Random  RDF

Solvent - Java S cript screen scraping Solvent - JavaScript screen scraping: a Firefox extension that helps write Javascript screen scrapers for Piggy Bank. Motivation: Piggy Bank needs web pages to embed information in RDF . Unfortunately , not many web pages embed or link to RDF information . Piggy Bank is capable to execute a particular screen scraper on particular pages in order to "extract" the information it needs. turn s a regular web page into a semantic web page, freeing the data from the page/site that contains it.

Solvent - Java S cript screen scraping

Longwell - RDF faceted metadata browser

PiggyBank Firefox extension for managing metadata - Loads RDF into local Longwell server Search and faceted browse of local RDF - Views defined by library, other users Users can find, collect, annotate RDF - Can then publish for access by others

SemanticBank Semantic Bank use cases: persist information remotely on a server share information with other people lets you publish your information, both in RDF or to regular web pages f or individuals, groups, communities - e.g. conference proceedings t he ability to tag resources creates a powerful serendipitous categorization Longwell facetted browsing view of published information

System Features Comparison General Properties JeromeDL BRICKS Fedora OS Support Any Any Any Hardware Requirements 500MB RAM, min 128MB HD 500MB RAM, min 100MB HD 500MB RAM, min 100MB HD Software Requirements Java 1.5, Tomcat 5.5, Sesame Java 1.4/1.5, Jena Java 1.5, Tomcat, Kowari/Mulgara or MPTStore Current Stage Research Stable version 2.0.1 Second Prototype Production Version 2.2 No. Installations 12+ ~ 8 ~50 monitored; large # of downloads unmonitored Support Model Open Source Open Source Open Source

System Features Comparison Architectural Aspects JeromeDL BRICKS Fedora Distribution Distributed searching (P2P), aggregated browsing (hierarchical) Fully decentralized (P2P) federation via nameresolver search services; Alvis P2P Architecture Granularity Low (main building blocks) High (many Components) High (core repository service with configurable modules; loosely coupled services) DB - Support Any Sesame-compliant backend Any Jena compliant backend MySQL, Postgres, Oracle, McKoi; Kowari/Mulgara

System Features Comparison Content & Metadata Aspects JeromeDL BRICKS Fedora Content Types All All All Content Models JeromeDL ontology Any Any Metadata Schema MarcOnt + extensions Any RDF/S & OWL schema Any XML Schema, RDF/S & OWL schema Query types Full-text, Filed-Search, Ontology-based, NL Query Templates Full-text, Field-Search, Ontology-based (sparql) Field Search, Ontology-based (itql, rdql, sparql, spo), Full-Text (Lucene or Zebra backed service)

System Features Comparison Security & DRM Aspects JeromeDL BRICKS Fedora Security Model FOAFRealm RBAC XACML Policy Granularity Resource Component, Method, Object Object, Datastream, Dissemination method DRM Model Fair use DRM under development MPEG-21 REL DRM Datastreams DRM Enabling Tool Support Watermarking

System Features Comparison Semantic Aspects & Community Features JeromeDL BRICKS Fedora Reasoning Recommendation engine based on Prolog Configurable inference engine Holding pattern; look to Mulgara; Tagging Free tagging, Wordnet-based Annotation middleware component middleware/apps (e.g., NSDL/NDR; PLoSONE/Topaz) Taxonomies Any (JOnto) Any Any Knowledge Sharing SSCF component via middleware upon BRICKS via middleware upon Fedora Communities SIOC and FOAF compli a nce

The future - Social Semantic Digital Libraries Why current (semantic) digital libraries are not enough? digital libraries should not be for librarians only but for average people they concentrate on delivering content/information, not on knowledge sharing within a community of users digital libraries have lost human-part of their predecessors

The future - Social Semantic Digital Libraries What could be the solution? make users/readers involved in the content annotation process allow users/readers to share their knowledge within a community provide better communication between users in and across communities

The future - Social Semantic Digital Libraries What is Web 2.0? The Web where “ordinary” users can meet, collaborate, and share using whatever is newly popular on the Web (tagged content, social bookmarking, AJAX, etc.) The term Web 2.0 was made popular by Tim O’Reilly: http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html Popular examples include: Bebo, del.icio.us, digg, Flickr, Google Maps, Skype, Technorati, Wikipedia…

The future - Social Semantic Digital Libraries (3) Web 2.0 focuses include: The Web as a platform for social and collaborative exchange Reusable community contributions Subscriptions to information, news, data flows, services Mass-publishing using web-based social software Social software for communication and collaboration: IM, IRC, Forums, Blogs, Wikis, Social Network Services, Social Bookmarks, MMOGs…

Social Semantic Information Spaces

Comparing Web 1.0 / Web 2.0 / Semantic Web 2.0 Semantic Social Networks Online Social Networks Buddy Lists, Address Books Semantic Social Information Spaces - - Social Semantic Digital Libraries Google Scholar, Book Search CiteSeer, Project Gutenberg Semantic Forums and Community Portals Community Portals Message Boards Semantic Blogs Blogs Personal Websites Semantic Search Google Personalised, DumbFind Altavista, Google Semantic Wikis Wikis Content Management Systems Semantic Web 2.0 Web 2.0 Web 1.0

Geo, Time, and Machine Tagging Geo-tagging for resources with a specific geographical location Time-tagging – community driven process of assigning auxiliary multimedia content Machine-tagging – ability to mix structured annotations into tags ROI-tagging : Regions of interest ERP game Asynchonous version with annealing of annotations for less frequently visited libraries

SDL in eLearning One of potential sources of future e-Learning systems On the verge between formal (libraries) and informal (communities) learning sources Semantic interoperability with Learning Management Systems Improve knowledge creation, delivery and sharing

SDL in Future Museums Museums have physical objects Should bind digital annotations with physical objects Real-virtual tours Start with real, guided tour Ubiquitous browse through context information Locate other exhibitions in the vicinity Share your knowledge and experience with others, leave bread-crumbs for others Get the most of the exhibition during your visit

Discussion – Feedback The Librarian from Unseen University in Ankh-Morpork (formerly Dr. Horace Worblehat)

Tutorial on Semantic Digital Libraries (ESWC'2007)

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