1.
Corrib.org group OpenSource and Research Adam Gzella Sebastian Ryszard Kruk

2.
Outline <ul><li>Corrib.org and DERI </li></ul><ul><li>SemanticWeb </li></ul><ul><li>Corrib.org achievements and interests </li></ul><ul><li>JeromeDL </li></ul><ul><li>notitio.us </li></ul><ul><li>OpenSource in Reasearch and Academia </li></ul>

3.
Goals for this presentation <ul><li>Show how open source supports research </li></ul><ul><li>Present corrib.org tools and solutions </li></ul><ul><li>I nvite to cooperate with us </li></ul>

4.
Digital Enterprise Research Institute <ul><li>DERI is a Centre for Science, Engineering and Technology (CSET) established in 2003 with funding from the Science Foundation Ireland. </li></ul><ul><li>As National University of Ireland, Galway institute </li></ul><ul><li>More than 120 people now from 27 countries </li></ul><ul><li>Funding: SFI, EI, EU projects. </li></ul><ul><li>The biggest SemanticWeb institute on the planet. </li></ul>

5.
Corrib.org <ul><li>Corrib.org - informal group run within DERI. </li></ul><ul><li>E stablished to manage the collaboration with GUT (Gdańsk University of Technology). </li></ul><ul><li>T urn ed into ecosystem for research and open source development on semantic digital libraries and semantic infrastructure </li></ul><ul><li>Delivered 11 Masters </li></ul><ul><li>Another 5 in progress </li></ul><ul><li>2 PhD coming up </li></ul>

6.
Corrib.org <ul><li>8 core members </li></ul><ul><li>About 10 supporting members and students </li></ul><ul><li>Profesional advisors, including prof. Stefan Decker (DERI), prof. Henryk Krawczyk (GUT), prof. Hong-Gee Kim (DERI Korea) </li></ul><ul><li>Leader – Sebastian Kruk </li></ul>

7.
Corrib.org <ul><li>Corrib.org – vast number of different projects </li></ul><ul><li>2 characteristics stays the same: </li></ul><ul><ul><li>Domain: SemanticWeb </li></ul></ul><ul><ul><li>Open Source </li></ul></ul><ul><li>Main technology that we are using: </li></ul><ul><ul><li>Java (JSE and JEE) </li></ul></ul><ul><li>Open Source - fast research dissemination channel </li></ul>

8.
SemanticWeb – short introduction <ul><li>Current Web vs. Semantic Web? </li></ul><ul><ul><li>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] </li></ul></ul><ul><ul><li>Current Web was designed for humans, and there is little information usable for machines </li></ul></ul><ul><li>Was the Web meant to be more? </li></ul><ul><ul><li>Objects with well defined attributes as opposed to untyped hyperlinks between Internet resources </li></ul></ul><ul><ul><li>A network of relationships amongst named objects, yielding unified information management tasks </li></ul></ul><ul><li>What do you mean by “Semantic”? </li></ul><ul><ul><li>the semantics of something is the meaning of something </li></ul></ul><ul><ul><li>Semantic Web is able to describe things in a way that computers can understand </li></ul></ul>

9.
SemanticWeb - RDF <ul><li>Describing things on the Semantic Web </li></ul><ul><ul><li>RDF (Resource Description Framework) </li></ul></ul><ul><ul><ul><li>a data format for describing information and resources, </li></ul></ul></ul><ul><ul><ul><li>the fundamental data model for the Semantic Web </li></ul></ul></ul><ul><ul><li>Using RDF, we can describe relationships between things like: </li></ul></ul><ul><ul><ul><li>A is a part of B or </li></ul></ul></ul><ul><ul><ul><li>Y is a member of Z </li></ul></ul></ul><ul><ul><ul><li>and their properties ( size , weight , age , price …) in a machine-understandable format </li></ul></ul></ul><ul><ul><li>RDF graph-based model delivers straightforward machine processing </li></ul></ul><ul><ul><li>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 </li></ul></ul>

10.
SemanticWeb - RDF <ul><li>How RDF can help us? </li></ul><ul><li>identify objects </li></ul><ul><li>establish relationships </li></ul><ul><li>express a new relationship </li></ul><ul><ul><li>just add a new RDF statement </li></ul></ul><ul><li>integrate information from different sources </li></ul><ul><ul><li>copy all the RDF data together </li></ul></ul><ul><li>RDF allows many points of view </li></ul>

11.
SemanticWeb - Ontologies <ul><li>What is an Ontology? </li></ul><ul><ul><li>„ An ontology is a specification of a conceptualization.“ </li></ul></ul><ul><li>Tom Gruber, 1993 </li></ul><ul><li>Ontologies are social contracts </li></ul><ul><ul><li>Agreed, explicit semantics </li></ul></ul><ul><ul><li>Understandable to outsiders </li></ul></ul><ul><ul><li>(Often) derived in a community process </li></ul></ul><ul><li>Ontology markup and representation languages: </li></ul><ul><ul><li>RDF and RDF Schema </li></ul></ul><ul><ul><li>OWL </li></ul></ul><ul><ul><li>Other: DAML+OIL, EER, UML, Topic Maps, MOF, XML Schemas </li></ul></ul>

12.
SemanticWeb – RDFS and OWL <ul><li>RDF Schema - small vocabulary for RDF: </li></ul><ul><ul><li>Class, subClassOf, type </li></ul></ul><ul><ul><li>Property, subPropertyOf </li></ul></ul><ul><ul><li>domain, range </li></ul></ul><ul><li>OWL – The Web Ontology Language </li></ul><ul><ul><li>provides a vocabulary for defining classes, their properties and their relationships among classes. </li></ul></ul><ul><ul><ul><li>Based on Description Logics </li></ul></ul></ul><ul><ul><ul><li>OWL is a W3C Recommendation </li></ul></ul></ul>

13.
SemanticWeb and KOS <ul><li>KOS – Knowledge Organisation System </li></ul><ul><li>tools that present the organized interpretation of knowledge structures </li></ul><ul><li>semantic tools - meaning of words and other symbols as well as (semantic) relations between symbols and concept </li></ul><ul><li>organize information and promote knowledge management </li></ul><ul><li>Examples: </li></ul><ul><ul><li>classification and categorization schemata (organize materials at a general level) </li></ul></ul><ul><ul><li>subject headings (provide more detailed access) </li></ul></ul><ul><ul><li>authority files (control variant versions of key information such as geographic names and personal names) </li></ul></ul><ul><ul><li>highly structured vocabularies, such as thesauri </li></ul></ul><ul><ul><li>traditional schemes, such as semantic networks and ontologies </li></ul></ul>

14.
Understanding KOS <ul><li>controlled vocabulary - a list of terms that have been enumerated explicitly </li></ul><ul><li>taxonomy - a collection of controlled vocabulary terms organized into a hierarchical structure. </li></ul><ul><li>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. </li></ul><ul><li>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. </li></ul><ul><ul><li>as a set of building blocks and rules used to build models </li></ul></ul><ul><ul><li>as a model of a domain of interest, and </li></ul></ul><ul><ul><li>as an instance of another model. </li></ul></ul>

15.
SemanticWeb - Appliacations <ul><li>Semantic Web cannot be and is not only a set of recommendations </li></ul><ul><li>Semantic Web is becoming reality by applications that support it and are based on it </li></ul><ul><li>Enabling technologies: </li></ul><ul><ul><li>RDF Storages: Sesame, Jena, YARS </li></ul></ul><ul><ul><li>Reasoners: KAON, Racer </li></ul></ul><ul><ul><li>Editors: Protege, SWOOP, MarcOnt Portal </li></ul></ul><ul><li>End-User applications: </li></ul><ul><ul><li>Semantic wikis: Makna, SemperWiki </li></ul></ul><ul><ul><li>Semantic blogs </li></ul></ul><ul><ul><li>Semantic digital librarie s </li></ul></ul>

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SemanticWeb - Applications <ul><li>The challenge for the Semantic Web </li></ul><ul><ul><li>The Semantic Web can’t work all by itself </li></ul></ul><ul><ul><li>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 </li></ul></ul><ul><ul><li>Need society-scale applications: Semantic Web agents and/or services, consumers and processors for semantic data, more advanced collaborative applications </li></ul></ul>

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Corrib.org mission <ul><li>Help SemanticWeb to emerge b y providing suitable infrastructure , tools and by building SemanticWeb applications. </li></ul>

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FOAFRealm <ul><li>User management system based on FOAF metadata. </li></ul><ul><li>FOAF (Friend-Of-A-Friend) </li></ul><ul><ul><li>a Web of machine-readable pages describing people, the links between them and the things they create and do. </li></ul></ul><ul><ul><li>Standard for describing persons. </li></ul></ul><ul><li>Important extensions to FOAF </li></ul><ul><ul><li>friendshipLevel – allows us to specify how good someone knows someone </li></ul></ul><ul><li>First goals of the project: </li></ul><ul><ul><li>Quick registration with FOAF profile </li></ul></ul><ul><ul><li>Plugin to Apache Tomcat server that would allow to authenticate users using FOAF profiles. </li></ul></ul>

19.
FOAFRealm <ul><li>Current role of FOAFRealm </li></ul><ul><ul><li>Providing social network features for other applications </li></ul></ul><ul><ul><li>Providing flexible access rights control based on the social network. </li></ul></ul><ul><ul><ul><li>Based on the distance and friendship level in the social graph </li></ul></ul></ul><ul><li>Full-fledged REST SOA build for the system. </li></ul>

20.
HyperCuP <ul><li>Scalable P2P communication protocol. </li></ul><ul><li>Our approach was to deliver more lightweight implementation than these delivered in the Edutella project </li></ul><ul><li>Supports P2P network based on hypercube </li></ul><ul><ul><li>Provides most efficient P2P broadcast algorithm </li></ul></ul><ul><li>We have delivered prototype Java implementation </li></ul><ul><li>http:// hypercup.corrib.org / </li></ul>

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MarcOnt Initiative <ul><li>Motivation: </li></ul><ul><li>Build a bibliographic ontology for Semantic Digital Libraries </li></ul><ul><li>MarcOnt Initiative goals: </li></ul><ul><li>Deliver a set of tools for collaborative ontology development </li></ul><ul><li>Collaboration </li></ul><ul><li>Tools for domain experts </li></ul><ul><li>Enable mediation between formats (MMS) </li></ul>

22.
MarcOnt <ul><li>Marcont Ontology </li></ul><ul><ul><li>Central point of MarcOnt Initiative </li></ul></ul><ul><ul><li>Translation and mediation format </li></ul></ul><ul><ul><li>Continuous collaborative ontology improvement </li></ul></ul><ul><ul><li>Knowledge from the domain experts </li></ul></ul><ul><ul><li>Community influence and evaluation </li></ul></ul><ul><li>MarcOnt Portal </li></ul><ul><ul><li>Collaborative ontology development. </li></ul></ul><ul><ul><li>Portal provides: </li></ul></ul><ul><ul><ul><li>Suggestions </li></ul></ul></ul><ul><ul><ul><li>Annotations </li></ul></ul></ul><ul><ul><ul><li>Versioning </li></ul></ul></ul><ul><ul><ul><li>Ontology editor with diff and visualisations and on-line editing </li></ul></ul></ul>

23.
MarcOnt Format translation Interoperability MarcOnt Mediation Services RDF Translator

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Didaskon <ul><li>Didaskon delivers components for composing suggestion of elearning course based on learning objects coming from both courseware and informal learning. </li></ul><ul><li>Architecture of the future e-Learning system </li></ul><ul><li>Ontology for user model – delivering personalised content </li></ul><ul><li>Ontology for content - ensuring cooperation of heterogeneous environments which use different formats </li></ul>

25.
Didaskon <ul><li>Content sources: </li></ul><ul><ul><li>Formal: e-Learning courses (LOM standard), books, articles (data provided by digital library) </li></ul></ul><ul><ul><li>Informal: Internet, social networks, Web2.0 portals </li></ul></ul><ul><li>Informal knowledge – 80% of whole learning process! </li></ul><ul><li>How to capture informal knowledge and use it toghether with formal sources? -> </li></ul><ul><li>Maybe utilise SemanticWeb interoperability -> IKHarvester </li></ul>

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IKHarvester <ul><li>Informal Knowledge Harvester </li></ul><ul><li>Harvesting RDF data and Creating LOM objects from the informal sources </li></ul><ul><ul><li>If page provided reach information –> IKH a llows to read RDF from a given resource </li></ul></ul><ul><ul><li>If there is no RDF data on the page (most of the pages) -> T ranslate given resource to RDF (Wikipedia pages, blogs and foras </li></ul></ul><ul><li>Blade- architecture to support new types of sources </li></ul>

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IKHarvester <ul><li>Harvesting pipeline </li></ul>

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S 3 B - Social Semantic Search and Browsing <ul><li>M iddleware that deliver s searching, browsing, filtering, and sharing information with support of RDF storage and full text index. </li></ul><ul><li>C onsists of a number of component s </li></ul>

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S 3 B – SQE <ul><li>SQE – Semantic Query Expansion </li></ul><ul><li>Why simple full-text search is not enough? </li></ul><ul><ul><li>Too many results (low precision) </li></ul></ul><ul><ul><li>One needs to specify the exact keyword (low recall) </li></ul></ul><ul><ul><li>How to distinguish between: Python and python? (high fall-out) </li></ul></ul><ul><li>How ? </li></ul><ul><ul><li>Disambiguation through a context </li></ul></ul><ul><ul><ul><li>Query context </li></ul></ul></ul><ul><ul><ul><li>Short-term context ( User’s goal , Location , Time ) </li></ul></ul></ul><ul><ul><ul><li>Long-term context ( User’s interest , Search engine specific ) </li></ul></ul></ul>

30.
S 3 B – SQE Techniques <ul><li>Query refinement </li></ul><ul><ul><li>Spread activation </li></ul></ul><ul><ul><li>Types mapping </li></ul></ul><ul><ul><li>Pruning </li></ul></ul><ul><li>Acquiring the context information: </li></ul><ul><ul><li>Previous searches of the user </li></ul></ul><ul><ul><li>Semantically annotated user’s bookmarks </li></ul></ul><ul><ul><li>Community profile </li></ul></ul><ul><li>Manual query refinement </li></ul><ul><ul><li>“ Tell me why” button and the transcript of refinement process </li></ul></ul><ul><ul><li>Continue to faceted navigation </li></ul></ul>

31.
S 3 B – MBB <ul><li>MBB – MultiBeeBrowse </li></ul><ul><ul><li>faceted navigation solution, which allows to access current browsing context, history of browsing. </li></ul></ul><ul><ul><li>keeps the track of relations between performed queries </li></ul></ul><ul><ul><li>adaptive hypermedia techniques to improve usability </li></ul></ul>

32.
S 3 B – MBB - Motivations <ul><li>The search does not end on a (long) list of results </li></ul><ul><li>The results are not a list (!) but a graph </li></ul><ul><li>„ Lost in hyperspace” </li></ul><ul><li>A need for unified UI and services for filter/narrow and browse/expand services </li></ul><ul><li>Share browsing experience – navigate collaboratively </li></ul>

33.
S 3 B – MBB - Solutions <ul><li>Defines REST access to services and their composition </li></ul><ul><li>Basic services: access, search, filter, similar, browse, combine </li></ul><ul><li>Meta services : RDF serialization, subscription channels, service ID generation, </li></ul><ul><li>Context services : manage contexts, manage service calls/compositions in the context, lists contexts </li></ul><ul><li>Statistics services : properties, values, token s </li></ul>

34.
S 3 B – MBB <ul><li>Helping users with different problems </li></ul><ul><ul><li>Finding results </li></ul></ul><ul><ul><li>Going back and forth in the refinement process </li></ul></ul><ul><ul><li>Overview of current browsing context </li></ul></ul><ul><ul><li>Replaying previous queries </li></ul></ul><ul><li>4 views: </li></ul><ul><ul><li>Basic browsing view </li></ul></ul><ul><ul><li>Structured history view </li></ul></ul><ul><ul><li>HoneyComb view </li></ul></ul><ul><ul><li>Life-long history view </li></ul></ul>

35.
S 3 B – MBB

36.
S 3 B – TTM <ul><li>TagsTreeMaps </li></ul><ul><ul><li>filtering based on clustered tags </li></ul></ul><ul><ul><li>using treemaps to present the tag space </li></ul></ul><ul><ul><li>zoomable interface paradigm </li></ul></ul>

37.
S 3 B – TTM <ul><li>Problems with Tag Clouds: </li></ul><ul><ul><li>information overload (for large tag clouds) </li></ul></ul><ul><ul><li>cannot carry structure and/or semantics </li></ul></ul><ul><ul><li>querying model: only conjunctive queries </li></ul></ul><ul><li>Solution: </li></ul><ul><ul><li>limits the information overload </li></ul></ul><ul><ul><ul><li>clustering tagging space </li></ul></ul></ul><ul><ul><ul><li>limiting popularity range </li></ul></ul></ul><ul><ul><li>zoomable browser on the tagging space </li></ul></ul><ul><ul><li>selecting multiple tags </li></ul></ul><ul><ul><ul><li>fulltext filtering - easy highlight matching tags </li></ul></ul></ul><ul><ul><ul><li>optional conjunctive (AND) and union (OR) mode </li></ul></ul></ul><ul><ul><li>defined interfaces for delivering processors in the pipeline (e.g., clustering, filtering, coloring ) </li></ul></ul>

38.
S 3 B – TTM

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S 3 B – NLQ <ul><li>Natural Language Query Templates </li></ul><ul><ul><li>allows to perform complex queries using natural language </li></ul></ul><ul><ul><li>can be created and modified based on the needs of users </li></ul></ul><ul><ul><li>easily internationalized </li></ul></ul>

40.
Find articles related to mission in the context of aerospace ... Query Templates (Regular Expressions) English Portuguese Aerospace mission skos:related results marcont:hasKeyword marcont:hasDomain SELECT * FROM ....

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S 3 B – Recommendations <ul><li>Resource-based Recommendations </li></ul><ul><ul><li>customizable view of recommendations </li></ul></ul><ul><ul><li>extensible with new similarity plugins </li></ul></ul>

42.
S 3 B – Recommendations Library resource hasKeyword hasDomain hasCreator A C D E F Step 1: Find similar resources Step 2: Rank and filter according to user’s settings G ... by keyword (max. 2) by author (max. 2) by domain (max. 2) E C B A summary (max. 3)

43.
JOnto and Tagging <ul><li>Unified Java and REST API for accessing KOS </li></ul><ul><li>Representing complete KOS in RDF </li></ul><ul><ul><li>SKOS </li></ul></ul><ul><ul><li>WordNet in OWL/RDF </li></ul></ul><ul><ul><li>TagOntology </li></ul></ul><ul><li>Support for: </li></ul><ul><ul><li>taxonomies (UDC, DDC, LoC, ACM, DMoz, PKT) </li></ul></ul><ul><ul><li>thesauri (WordNet, OpenThesaurus) </li></ul></ul><ul><ul><li>free tagging </li></ul></ul><ul><li>Easily extensible: </li></ul><ul><ul><li>with new taxonomies (RDF or flat file source) </li></ul></ul><ul><ul><li>thesauri in RDF (WordNet in OWL/RDF ontology) </li></ul></ul><ul><li>Fulltext indexing for faster filtering and retrieval </li></ul>

44.
Tagging <ul><li>Support for semantic tagging </li></ul><ul><li>Using ontology based on Toms Gruber tagging ontology </li></ul>

45.
S 3 B – Social Semantic Collaborative Filtering <ul><li>Why? </li></ul><ul><ul><li>The bottom-line of acquiring knowledge: informal communication (“word of mouth”) </li></ul></ul><ul><li>How? </li></ul><ul><ul><li>Everyone classifies (filters) the information in bookmark folders ( user-oriented taxonomy ) </li></ul></ul><ul><ul><li>Peers share (collaborate over) the information ( community-driven taxonomy ) </li></ul></ul><ul><li>Result? </li></ul><ul><ul><li>Knowledge “flows“ from the expert through the social network to the user </li></ul></ul><ul><ul><li>System amass a lot of information on user/community profile (context) </li></ul></ul>

46.
S 3 B – SSCF <ul><li>Problems? </li></ul><ul><ul><li>The horizon of a social network (2-3 degrees of separation) </li></ul></ul><ul><ul><li>How to handle fine-grained information (blogs, wikis, etc.) </li></ul></ul><ul><li>Solutions? </li></ul><ul><ul><li>Inference engine to suggest knowledge from the outskirts of the social network </li></ul></ul><ul><ul><li>Support for SIOC metadata: </li></ul></ul><ul><ul><ul><li>SIOC browser in SSCF </li></ul></ul></ul><ul><ul><ul><li>Annotations and evaluations of “local” resources </li></ul></ul></ul>

47.
S 3 B – SSCF <ul><li>Goal: to enhance individual bookmarks with shared knowledge within a community </li></ul><ul><li>Users annotate catalogues of bookmarks with semantic information taken from DMoz or WordNet vocabularies </li></ul><ul><li>Catalogs can include (transclusion) friend's catalogues </li></ul><ul><li>Access to catalogues can be restricted with social networking-based polices </li></ul><ul><li>SSCF delivers: </li></ul><ul><ul><li>Community-oriented, semantically-rich taxonomies </li></ul></ul><ul><ul><li>Information about a user's interest </li></ul></ul><ul><ul><li>Flows of expertise from the domain expert </li></ul></ul><ul><ul><li>Recommendations based on users previous actions </li></ul></ul><ul><ul><li>Support for SIOC metadata </li></ul></ul>

48.
S 3 B – SSCF <ul><li>Annotated directories </li></ul><ul><ul><li>Taxonomies </li></ul></ul><ul><ul><li>Semantic Tags </li></ul></ul><ul><ul><li>Using JOnto API </li></ul></ul><ul><li>Tagged resources </li></ul><ul><li>Recommendations based on users’ profile/interest </li></ul><ul><li>Prolog engine </li></ul>Directory Keyword A Taxonomy A Keyword B Resource R1 Resource R2 Resource R3 Prolog Engine Resource R3 Resource R2 Tag 1 Tag 2 Tag 3 Tag 2

49.
JeromeDL and notitio.us <ul><li>Two main corrib.org projects </li></ul><ul><li>Utylises aforementioned technologies to provide and delivers innovative: </li></ul><ul><ul><li>Digital Library – JeromeDL </li></ul></ul><ul><ul><li>Knowledge Management System – notitio.us </li></ul></ul>

50.
Jerome Digital Library <ul><li>Joint effort of </li></ul><ul><ul><li>DERI, National University of Ireland, Galway </li></ul></ul><ul><ul><li>Gdansk University of Technology (GUT) </li></ul></ul><ul><li>Distributed under BSD Open Source license </li></ul><ul><li>Instances all over the world </li></ul><ul><ul><li>Ireland </li></ul></ul><ul><ul><li>Poland </li></ul></ul><ul><ul><li>Brazil </li></ul></ul><ul><ul><li>Italy </li></ul></ul><ul><ul><li>Mexico </li></ul></ul><ul><ul><li>Korea </li></ul></ul>

51.
JeromeDL – Semantic Digital Library <ul><li>Semantic digital libraries </li></ul><ul><ul><li>integrate information based on different metadata, e.g.: resources, user profiles, bookmarks, taxonomies – high quality semantics = highly and meaningfully connected information </li></ul></ul><ul><ul><li>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 </li></ul></ul><ul><ul><li>delivering more robust, user friendly and adaptable search and browsing interfaces empowered by semantics (legacy, formal, and social annotations) </li></ul></ul>

52.
JeromeDL – Motivation use cases <ul><li>Librarians </li></ul><ul><ul><li>support for rich metadata (MARC21) in uploading resources, accessing bibliographic information and searching </li></ul></ul><ul><ul><li>persistent identifiers </li></ul></ul><ul><li>Scientists </li></ul><ul><ul><li>easy publishing (designed as a institute/university digital library) </li></ul></ul><ul><ul><li>creating hierarchical networks of digital libraries </li></ul></ul><ul><ul><li>support for accessing, sharing and searching using bibliography metadata (BibTeX) </li></ul></ul><ul><li>Everyone </li></ul><ul><ul><li>simple search (incl. natural language queries) </li></ul></ul><ul><ul><li>community-aware information sharing and browsing, </li></ul></ul><ul><ul><li>support for internationalization </li></ul></ul>

53.
JeromeDL - Motivation <ul><li>Support for different kinds of bibliographic metadata, like: DublinCore, BibTeX and MARC21 at the same time </li></ul><ul><ul><li>making use of existing rich sources of bibliographic descriptions (like MARC21) created by human </li></ul></ul><ul><li>Support users and communities </li></ul><ul><ul><li>users have control over their profile information </li></ul></ul><ul><ul><li>community-aware profiles are integrated with bibliographic descriptions </li></ul></ul><ul><ul><li>support for community generated knowledge </li></ul></ul><ul><li>Deliver communication between instances </li></ul><ul><ul><li>P2P mode for searching and users authentication </li></ul></ul><ul><ul><li>hierarchical model for browsing </li></ul></ul>

54.
JeromeDL <ul><li>JeromeDL is the semantic digital library that provides </li></ul><ul><ul><li>integrated social networking with user profiling. </li></ul></ul><ul><ul><li>enhanced personalized search facility. </li></ul></ul><ul><ul><li>interconnects meaningful description of resources with social media. </li></ul></ul><ul><ul><li>extensible access control based on social networks. </li></ul></ul><ul><ul><li>collaborative browsing and filtering. </li></ul></ul><ul><ul><li>dynamic collections . </li></ul></ul><ul><ul><li>integration with Web 2.0 services. </li></ul></ul>

55.
Metadata and Services in JeromeDL

56.
JeromeDL – Dynamic Collections <ul><li>Dynamic Collections </li></ul><ul><ul><li>specified with triples filter or RDF query </li></ul></ul><ul><ul><li>can be arranged in a tree structure </li></ul></ul><ul><ul><li>easily extensible </li></ul></ul>

57.
JeromeDL - ontologies

58.
JeromeDL – flexible access control <ul><li>Identity management based on social networks </li></ul><ul><ul><li>support for social networking metadata standard (FOAF) </li></ul></ul><ul><ul><li>users and authors are part of a community </li></ul></ul><ul><li>Access control module </li></ul><ul><ul><li>apply access control licenses to resources and services </li></ul></ul><ul><ul><li>defines atomic protections based on IP or position in the social network </li></ul></ul><ul><ul><li>easily extensible </li></ul></ul>

59.
JeromeDL – access to semantics <ul><li>Exposing underlying semantics </li></ul><ul><ul><li>rendering RDF in various flavors </li></ul></ul><ul><ul><li>exposing semantics in JSON and SIOC </li></ul></ul><ul><ul><li>syndication feeds (RSS) </li></ul></ul><ul><li>Querying semantic database </li></ul><ul><ul><li>RDF query (SPARQL) endpoint </li></ul></ul><ul><ul><li>OAI-PMH </li></ul></ul><ul><ul><li>Open Search </li></ul></ul><ul><li>Delivering metadata to other services </li></ul><ul><ul><li>MarcOnt Mediation Services </li></ul></ul>

60.
JeromeDL – search beyond one JDL <ul><li>Distributed search </li></ul><ul><ul><li>Extensible Library Protocol </li></ul></ul><ul><ul><li>based on HyperCuP P2P infrastructure </li></ul></ul><ul><li>Federated Search </li></ul><ul><ul><li>hierarchical order of JeromeDL instances </li></ul></ul><ul><ul><li>exposing resources bottom-up </li></ul></ul><ul><li>OAI-PMH </li></ul><ul><ul><li>harvesting other libraries </li></ul></ul><ul><ul><li>exposing resources to other libraries </li></ul></ul>

61.
Towards Library 2.0 <ul><li>Users become active producers of the content and metadata </li></ul><ul><li>JeromeDL turns a single resources into a blog post </li></ul><ul><ul><li>users can annotate it </li></ul></ul><ul><ul><li>users can rank it </li></ul></ul><ul><ul><li>metadata about user annotations is exported in SIOC </li></ul></ul><ul><li>Community annotations for multimedia (alpha) </li></ul><ul><ul><li>region of interest (ROI) tagging in photos </li></ul></ul><ul><ul><li>time-tagging of video streams </li></ul></ul>

62.
JeromeDL – Conclusions <ul><li>JeromeDL is a semantically enhanced DL based on semantic web and social networking technologies </li></ul><ul><ul><li>enhances users experience through the social interactions </li></ul></ul><ul><ul><li>exploits the social networks for recommendations </li></ul></ul><ul><ul><li>offers extensible access control </li></ul></ul><ul><ul><li>delivers semantics for other services </li></ul></ul><ul><ul><li>improves user experience of the information discovery process (confirmed by evaluation) </li></ul></ul>

63.
notitio.us <ul><li>Provide knowledge management solutions for the enterprises and the communities of users </li></ul><ul><li>Build upon solution of the Semantic Web research </li></ul>

64.
notitio.us <ul><li>service that enables the aggregation of metadata-rich information from various types of social semantic information sources. </li></ul><ul><li>allows users to easily discover and share their knowledge. </li></ul><ul><li>advanced solution to further information browsing, using either faceted navigation or tags-based filtering </li></ul><ul><li>capable of exporting information in a standard way so that its data can be used by other semantically- enabled applications. </li></ul>

65.
notitio.us – main modules <ul><li>SSCF – social bookmarking system with recomendations </li></ul><ul><li>MBB – browsing on unstructured metadata </li></ul><ul><li>TTM – browsing resources by tags </li></ul><ul><li>IKHarvester – providing Semantic information </li></ul>

66.
notitio.us – information flow <ul><li>Information discovery </li></ul><ul><li>Information browsing and sharing </li></ul><ul><li>Information exporting </li></ul>

67.
notitio.us <ul><li>Collaborative browsing – sharing MBB quries as a bookmarks </li></ul>

68.
notitio.us <ul><li>distinctive features (compared to del.icio.us and similar) </li></ul><ul><ul><li>Reacher resources organisation. </li></ul></ul><ul><ul><ul><li>Well annotated directories and self created hierarchy </li></ul></ul></ul><ul><ul><li>Instant access to social network benefits </li></ul></ul><ul><ul><li>Recommendation system that takes into account your resources and your characteristic </li></ul></ul><ul><ul><li>Innavative browsing features including collaborative browsing </li></ul></ul>

69.
Summary – OpenSource in Research <ul><li>On the corrib.org example you can see how the OpenSource works in Academia. </li></ul><ul><li>openSource != freeSource </li></ul><ul><li>utilise the scale effect of people using the Open Source solutions for further research and for commercialisation efforts , </li></ul>

70.
Future <ul><li>JeromeDL and notitio.us future – commercialisations and further research </li></ul>

71.
<ul><li>We invite everyone interested to contact and cooperate with us! </li></ul><ul><li>Adam Gzella – [email_address] </li></ul><ul><li>Sebastian Kruk – [email_address] </li></ul><ul><li>http ://www.corrib.org </li></ul><ul><li>http://www.jeromedl.org </li></ul><ul><li>http://notitio.us </li></ul><ul><li>http://www.deri.org </li></ul>