corrib.org - opensource and research

Copyright 2008 Digital Enterprise Research Institute. All rights reserved.

Digital Enterprise Research Institute www.deri.ie

Corrib.org groupOpenSource and Research

Adam GzellaSebastian Ryszard Kruk

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Outline

Corrib.org and DERI SemanticWeb Corrib.org achievements and interests JeromeDL notitio.us OpenSource in Reasearch and Academia

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Goals for this presentation

Show how open source supports research Present corrib.org tools and solutions Invite to cooperate with us

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Digital Enterprise Research Institute

DERI is a Centre for Science, Engineering and Technology (CSET) established in 2003 with funding from the Science Foundation Ireland.

As National University of Ireland, Galway institute More than 120 people now from 27 countries Funding: SFI, EI, EU projects. The biggest SemanticWeb institute on the

planet.

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Corrib.org

Corrib.org - informal group run within DERI. Established to manage the collaboration with GUT

(Gdańsk University of Technology). Turned into ecosystem for research and open

source development on semantic digital libraries and semantic infrastructure

Delivered 11 Masters Another 5 in progress 2 PhD coming up

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Corrib.org

8 core members About 10 supporting members and students Profesional advisors, including prof. Stefan

Decker (DERI), prof. Henryk Krawczyk (GUT), prof. Hong-Gee Kim (DERI Korea)

Leader – Sebastian Kruk

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Corrib.org

Corrib.org – vast number of different projects 2 characteristics stays the same:

Domain: SemanticWeb Open Source

Main technology that we are using: Java (JSE and JEE)

Open Source - fast research dissemination channel

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SemanticWeb – short 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

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SemanticWeb - RDF

Describing things on the Semantic Web 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 RDF graph-based model delivers straightforward machine

processing 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

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SemanticWeb - RDF

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

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SemanticWeb - Ontologies

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

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SemanticWeb – RDFS and OWL

RDF Schema - small vocabulary for RDF: Class, subClassOf, type

Property, subPropertyOf

domain, range

OWL – The Web Ontology Language provides a vocabulary for defining classes,

their properties and their relationships among classes.

– Based on Description Logics– OWL is a W3C Recommendation

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SemanticWeb and KOS

KOS – Knowledge Organisation System 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

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Understanding KOS

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.

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SemanticWeb - Appliacations

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

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SemanticWeb - Applications

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

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Corrib.org mission

Help SemanticWeb to emerge by providing suitable infrastructure, tools and by building SemanticWeb applications.

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FOAFRealm

User management system based on FOAF metadata.

FOAF (Friend-Of-A-Friend) a Web of machine-readable pages describing people, the

links between them and the things they create and do. Standard for describing persons.

Important extensions to FOAF friendshipLevel – allows us to specify how good someone

knows someone First goals of the project:

Quick registration with FOAF profile Plugin to Apache Tomcat server that would allow to

authenticate users using FOAF profiles.

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FOAFRealm

Current role of FOAFRealm Providing social network features for other applications Providing flexible access rights control based on the

social network.– Based on the distance and friendship level in the social

graph

Full-fledged REST SOA build for the system.

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HyperCuP

Scalable P2P communication protocol. Our approach was to deliver more lightweight

implementation than these delivered in the Edutella project

Supports P2P network based on hypercube Provides most efficient P2P broadcast algorithm

We have delivered prototype Java implementation http://hypercup.corrib.org/

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MarcOnt Initiative

Motivation: Build a bibliographic ontology for Semantic

Digital Libraries

MarcOnt Initiative goals: Deliver a set of tools for collaborative ontology

development Collaboration Tools for domain experts Enable mediation between formats

(MMS)

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MarcOnt

Marcont Ontology Central point of MarcOnt Initiative Translation and mediation format Continuous collaborative ontology improvement Knowledge from the domain experts Community influence and evaluation

MarcOnt Portal Collaborative ontology development. Portal provides:

– Suggestions– Annotations– Versioning– Ontology editor with diff and visualisations and on-line editing

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MarcOnt

MarcOnt OntologyMarcOnt RDF

MARC21 RDF

MARC21 XML

MARC21

Dublin Core RDF

Dublin Core XML

Dublin Core

New format RDF

New format XML

New format

Format translationInteroperability

MarcOnt Mediation Services RDF Translator

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Didaskon

Didaskon delivers components for composing suggestion of elearning course based on learning objects coming from both courseware and informal learning.

Architecture of the future e-Learning system Ontology for user model – delivering personalised

content Ontology for content - ensuring cooperation of

heterogeneous environments which use different formats

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Didaskon

Content sources: Formal: e-Learning courses (LOM standard), books,

articles (data provided by digital library) Informal: Internet, social networks, Web2.0 portals

Informal knowledge – 80% of whole learning process!

How to capture informal knowledge and use it toghether with formal sources? ->

Maybe utilise SemanticWeb interoperability -> IKHarvester

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IKHarvester

Informal Knowledge Harvester Harvesting RDF data and

Creating LOM objects from the informal sources If page provided reach

information –> IKH allows to read RDF from a given resource

If there is no RDF data on the page (most of the pages) -> Translate given resource to RDF (Wikipedia pages, blogs and foras

Blade-architecture to support new types of sources

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IKHarvester

Harvesting pipeline

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S3B - Social Semantic Search and Browsing

Middleware that delivers searching, browsing, filtering, and sharing information with support of RDF storage and full text index.

Consists of a number of components

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S3B – SQE

SQE – Semantic Query Expansion Why simple full-text search is not enough?

Too many results (low precision) One needs to specify the exact keyword (low recall) How to distinguish between: Python and python? (high

fall-out) How?

Disambiguation through a context– Query context– Short-term context (User’s goal, Location, Time)– Long-term context (User’s interest, Search engine specific)

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S3B – SQE Techniques

Query refinement Spread activation Types mapping Pruning

Acquiring the context information: Previous searches of the user Semantically annotated user’s bookmarks Community profile

Manual query refinement “Tell me why” button and the transcript of refinement

process Continue to faceted navigation

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S3B – MBB

MBB – MultiBeeBrowse faceted navigation solution, which allows to access

current browsing context, history of browsing. keeps the track of relations between performed queries adaptive hypermedia techniques to improve usability

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S3B – MBB - Motivations

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

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S3B – MBB - Solutions

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

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S3B – MBB

Helping users with different problems Finding results Going back and forth in the refinement process Overview of current browsing context Replaying previous queries

4 views: Basic browsing view Structured history view HoneyComb view Life-long history view

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S3B – MBB

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S3B – TTM

TagsTreeMaps filtering based on clustered tags using treemaps to present the tag space zoomable interface paradigm

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S3B – TTM

Problems with Tag Clouds: information overload (for large tag clouds) cannot carry structure and/or semantics querying model: only conjunctive queries

Solution: limits the information overload

– clustering tagging space– limiting popularity range

zoomable browser on the tagging space selecting multiple tags

– fulltext filtering - easy highlight matching tags– optional conjunctive (AND) and union (OR) mode

defined interfaces for delivering processors in the pipeline (e.g., clustering, filtering, coloring)

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S3B – TTM

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S3B – NLQ

Natural Language Query Templates allows to perform complex queries using natural

language can be created and modified based on the needs of

users easily internationalized

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Find articles related to mission in the context of aerospace

...Query

Templates

(Regular

Expressions)English Portuguese

Aerospa

cemission

skos:related

results

marcont:hasKeyword marcont:hasDomain

SELECT * FROM ....

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S3B – Recommendations

Resource-based Recommendations customizable view of recommendations extensible with new similarity plugins

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S3B – Recommendations

Library resourceLibrary resource

hasKeywordhasKeyword

hasDomainhasDomain

hasCreatorhasCreator

AA

CC

DD

EE

FF

Step 1: Find similar resourcesStep 1: Find similar resources

Step 2: Rank and filter according to user’s settingsStep 2: Rank and filter according to user’s settings

GG

......

by keyword (max. 2)by keyword (max. 2)

by author (max. 2)by author (max. 2)

by domain (max. 2)by domain (max. 2)

EE

CC

BB

AA

summary (max. 3)summary (max. 3)

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JOnto and Tagging

Unified Java and REST API for accessing KOS Representing complete KOS in RDF

SKOS WordNet in OWL/RDF TagOntology

Support for: taxonomies (UDC, DDC, LoC, ACM, DMoz, PKT) thesauri (WordNet, OpenThesaurus) free tagging

Easily extensible: with new taxonomies (RDF or flat file source) thesauri in RDF (WordNet in OWL/RDF ontology)

Fulltext indexing for faster filtering and retrieval

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Tagging

Support for semantic tagging Using ontology based on Toms Gruber tagging

ontology

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S3B – 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)

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S3B – SSCF

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

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S3B – SSCF

Goal: to enhance individual bookmarks with shared knowledge within a community

Users annotate catalogues of bookmarks with semantic information taken from DMoz 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

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S3B – SSCF

Annotated directories Taxonomies Semantic Tags Using JOnto API

Tagged resources Recommendations

based on users’ profile/interest

Prolog engine

DirectoryDirectory

Keyword AKeyword A

Taxonomy ATaxonomy A

Keyword BKeyword BResource R1Resource R1

Resource R2Resource R2


Prolog EngineProlog Engine



Tag 1Tag 2

Tag 3

Tag 2

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JeromeDL and notitio.us

Two main corrib.org projects Utylises aforementioned technologies to provide

and delivers innovative: Digital Library – JeromeDL Knowledge Management System – notitio.us

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Jerome Digital Library

Joint effort of DERI, National University of Ireland, Galway Gdansk University of Technology (GUT)

Distributed under BSD Open Source license Instances all over the world

Ireland Poland Brazil Italy Mexico Korea

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JeromeDL – 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 (legacy, formal, and social annotations)

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JeromeDL – Motivation 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 internationalization

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JeromeDL - Motivation

Support for different kinds of bibliographic metadata, like: DublinCore, BibTeX and MARC21 at the same time making use of existing rich sources of bibliographic

descriptions (like MARC21) created by human Support users and communities

users have control over their profile information community-aware profiles are integrated with

bibliographic descriptions support for community generated knowledge

Deliver communication between instances P2P mode for searching and users authentication hierarchical model for browsing

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JeromeDL

JeromeDL is the semantic digital library that provides

integrated social networking with user profiling.

enhanced personalized search facility.

interconnects meaningful description of resources with

social media.

extensible access control based on social networks.

collaborative browsing and filtering.

dynamic collections.

integration with Web 2.0 services.

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Metadata and Services in JeromeDL

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JeromeDL – Dynamic Collections

Dynamic Collections specified with triples

filter or RDF query can be arranged in a

tree structure easily extensible

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JeromeDL - ontologies

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JeromeDL – flexible access control

Identity management based on social networks support for social networking metadata standard (FOAF) users and authors are part of a community

Access control module apply access control licenses to resources and services defines atomic protections based on IP or position in the

social network easily extensible

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JeromeDL – access to semantics

Exposing underlying semantics rendering RDF in various flavors exposing semantics in JSON and SIOC syndication feeds (RSS)

Querying semantic database RDF query (SPARQL) endpoint OAI-PMH Open Search

Delivering metadata to other services MarcOnt Mediation Services

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JeromeDL – search beyond one JDL

• Distributed search– Extensible Library Protocol– based on HyperCuP P2P infrastructure

• Federated Search– hierarchical order of JeromeDL instances– exposing resources bottom-up

• OAI-PMH– harvesting other libraries– exposing resources to other libraries

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Towards Library 2.0

Users become active producers of the content and metadata

JeromeDL turns a single resources into a blog post users can annotate it users can rank it metadata about user annotations is exported in SIOC

Community annotations for multimedia (alpha) region of interest (ROI) tagging in photos time-tagging of video streams

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JeromeDL – Conclusions

JeromeDL is a semantically enhanced DL based on semantic web and social networking technologies enhances users experience through the social

interactions exploits the social networks for recommendations offers extensible access control delivers semantics for other services improves user experience of the information

discovery process (confirmed by evaluation)

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notitio.us

Provide knowledge management solutions for the enterprises and the communities of users

Build upon solution of the Semantic Web research

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notitio.us

service that enables the aggregation of metadata-rich information from various types of social semantic information sources.

allows users to easily discover and share their knowledge.

advanced solution to further information browsing, using either faceted navigation or tags-based filtering

capable of exporting information in a standard way so that its data can be used by other semantically- enabled applications.

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notitio.us – main modules

SSCF – social bookmarking system with recomendations

MBB – browsing on unstructured metadata TTM – browsing resources by tags IKHarvester – providing Semantic information

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notitio.us – information flow

Information discovery

Information browsing and sharing

Information exporting

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notitio.us

Collaborative browsing – sharing MBB quries as a bookmarks

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notitio.us

distinctive features (compared to del.icio.us and similar) Reacher resources organisation.

– Well annotated directories and self created hierarchy

Instant access to social network benefits Recommendation system that takes into account your

resources and your characteristic Innavative browsing features including collaborative

browsing

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Summary – OpenSource in Research

On the corrib.org example you can see how the OpenSource works in Academia.

openSource != freeSource

utilise the scale effect of people using the Open Source solutions for further research and for commercialisation efforts,

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Future

JeromeDL and notitio.us future – commercialisations and further research

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We invite everyone interested to contact and cooperate with us!

Adam Gzella – [email protected] Sebastian Kruk – [email protected]

http://www.corrib.org http://www.jeromedl.org http://notitio.us http://www.deri.org

corrib.org - opensource and research

Technology

semanticweb rdf

rdf files

rdf data

deri semanticweb

rdf schema owl

semanticweb ontologies

web ontology language

new rdf statement