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Personalised Access to Cultural Heritage Spaces using Pathways
Mark Stevenson University of Sheffield
Overview
• Background
• Information access in cultural heritage • PATHS project
– Processing Cultural Heritage data
Information access in cultural heritage
• Significant amounts of Cultural Heritage material available online – Web portals, digital libraries, Wikipedia …
• Users find it difficult to navigate and interpret the wealth of information – users are normally not subject experts – systems offer limited support for knowledge exploration and
discovery
Traditional Access
Online Access
PATHS http://www.paths-project.eu
• Supporting user’s knowledge discovery and exploration
• Use of pathways/trails to navigate and explore the information space
• Personalisation to adapt views/paths to specific users or groups of users
• Links to items within the information space and externally to contextualise and aid interpretation
PATHS: Basic facts
• STREP funded under the European Commission's Seventh Framework Programme
• 36 months – 1st January 2011 to 31st December 2013
• Budget – 3,199,299 euros in total – 2,300,000 euros EU grant
• 6 partners in 5 countries
PATHS consortium
• Universities – Sheffield University (co-ordinator) – Universidad del Pais Vasco
• Technology enterprises – i-sieve technologies Ltd – Asplan Viak Internet Ltd
• Cultural heritage enterprises – MDR Partners – Alinari 24 Ore Spa
• With an additional content provider – Europeana
Project objectives
• Analysis of users’ requirements for discovering knowledge in Cultural Heritage collections and construction of pathways/trails
• Automated organisation and enrichment of Cultural Heritage content for use within a navigation system
• Implementation of a system for navigating Cultural Heritage resources
• Techniques for providing personalised access to Cultural Heritage content (e.g. recommender systems)
• Porting the navigation system for use on mobile devices and Facebook
• Evaluation with user groups and in field trials
Research areas • Information Access
– user-driven navigation through collections – knowledge of users’ requirements for access to cultural heritage
collections – modeling of user preferences and context
• Educational Informatics – adapting to individual learners in relation to being directed and
being allowed the freedom to explore autonomously
• Content Interpretation and Enrichment – representation and sharing of information about items in Digital
Libraries – identifying background information related to the items in cultural
heritage collections (e.g. links to Wikipedia pages)
Pathways for navigation
• Navigation through a collection via metaphor of “pathways”
• A path is a ‘route’ through an information space – defined as collections of cultural heritage resources – consists of items, links connecting them and narrative
Presentation at Glasgow University, 14th March 2011
• Users can follow pre-defined “guided paths” – created by domain experts, such as scholars or teachers
• Provide an easily accessible entry point to the collection – can be followed in their entirety or left at any point
• Users can also create and share their own paths
• Paths can be based around any theme – artist and media (“paintings by Picasso”) – historic periods (“the Cold War”) – places (“Venice”) – famous people (“Muhammed Ali”) – or any other topic (e.g. “Europe”, “food”)
Guided and user generated paths
• Trails (Memex, 1945) – Associative trails explicitly created by users forming links
between stored materials to help others navigate • Destinations (search engines and web analytics)
– Origin/landing page (from query), intermediate pages and destination page
• Search strategies (information seeking) – Users moving between information sources, perhaps due to
changes in their information needs • Guided tours (hypertext)
– authors create sequence of pages useful to others (manual) – automatically generated trails to assist with web navigation – used in educational informatics and cultural heritage
Paths and trails have been studied in many fields
Learning and knowledge discovery
• A particular area of focus in PATHS – Aims to help people to learn and discover new knowledge as
they use cultural heritage resources
• People learn and solve problems differently – some people require a lot of guiding; others are self-directed – some people welcome irrelevant material; others are intolerant – some people creatively explore and come up with new ideas;
others want to answer a set problem
• Users may perform information seeking – must navigate through information spaces – different people may require different levels of assistance
Autonomous
Dependent
Local (analytic) Global
Key cognitive dimensions (Pask and Witkin)
Adopting a navigation path that matches one’s predominant style can influence the effectiveness of the resultant learning.
Local (analytic) Global
Learning/problem-solving goals
Convergent goals. “Find an answer”. Learn pre-defined content.
Divergent goals. Creatively explore. Come up with new ideas.
Process goals
Concerned with procedures and vertical deep detail (procedure building).
Concerned with conceptual overview and horizontal broad inter-relationships (description building).
Navigation styles
Serialist navigation style Narrow focus. One thing at a time. Short logical links between nodes. Intolerance of strictly irrelevant material. Finish with one topic before going on to the next.
Holist navigation style Broad global focus. Many things on the go at the same time. Rich links between nodes. Welcoming of enrichment (but strictly irrelevant) material. Layered approach returning to nodes at different level of detail.
Positive learning outcomes
Good grasp of detailed evidence. Deep understanding of individual topics. In-depth understanding of the parts.
Well developed conceptual overview. Broad inter-relationship of ideas. Good grasp of the “big picture”.
Characteristic learning pathologies
Poor appreciation of topic inter-relationships. Failing to see the “big picture”.
Poor grasp of detail. Over-generalisation.
6/22/11 © The University of Sheffield
Europeana http://www.europeana.eu
• Europe’s Digital Library, Museum and Archive • Vision of six European heads of state (2005) • Launched in November 2008 • 1,500 contributing institutions • Over 15 million items
<record> <dc:creator>Davies, J O</dc:creator> <dc:date>[2001]</dc:date> <dc:title>Stembridge Windmill, High Ham, Somerset</dc:title> <dc:description>This is a random-coursed blue lias stone tower mill, with a unique thatched cap. Built 1822 to replace an earlier mill
which was sited a few hundred metres to the north east. It ceased work in 1908 and was willed to the National Trust in 1969, since when quite extensive repairs have been carried out.</dc:description>
<dc:identifier>http://viewfinder.english-heritage.org.uk/search/detail.asp?calledFrom=oai&imageUID=8</dc:identifier> <dc:language>en</dc:language> <dc:rights>Copyright English Heritage.NMR</dc:rights> <dc:subject>Agriculture</dc:subject> <dc:subject>Windmill</dc:subject> <dc:subject>Tower Mill</dc:subject> <dc:type>Image</dc:type> <dcterms:isPartOf>English Heritage</dcterms:isPartOf> <europeana:country>uk</europeana:country> <europeana:dataProvider>English Heritage - Viewfinder</europeana:dataProvider> <europeana:isShownAt>http://viewfinder.english-heritage.org.uk/search/detail.asp?calledFrom=oai&imageUID=8</
europeana:isShownAt> <europeana:language>en</europeana:language> <europeana:object>http://www.culturegrid.org.uk/dpp/resource/1512084/stream/thumbnail_image_jpeg</europeana:object> <europeana:provider>CultureGrid</europeana:provider> <europeana:rights>http://www.europeana.eu/rights/rr-f/</europeana:rights> <europeana:type>IMAGE</europeana:type> <europeana:uri>http://www.europeana.eu/resolve/record/09405o/AC721E03934115003DEA60494AC9C88441A255ED</
europeana:uri> <europeana:year>2001</europeana:year> </record>
Europeana data
• Positives – Consistent format
• Negatives – Field values not standardised
• Different vocabularies • Different levels of detail
– Very frequent field values
– URIs are not stable!
Europeana data
Content Processing and Enrichment
• Linguistic analysis – Named entity identification
• Identify similar and related items
• Linking to Wikipedia (or other resources) – Link entire Europeana entries – Link items with entries (eg. named entities) – Background context
• Online survey to obtain human similarity judgements
• 30 pairs of items randomly selected from Europeana
• Users asked to rate pair on scale of 0 to 4 – 0 completely unrelated – 4 almost identical
• http://compare.net78.net/ • Over 30 participants so far
Determining Similarity
Survey
• Significant amount of work on computing lexical similarity in NLP – “dog” and “hound” are similar, “cat” and “cap”
are not
• Approaches include – comparing dictionary definitions – measuring distance in hierarchy (eg WordNet) – mapping to another resource (eg Wikipedia)
Computing Similarity
• Word overlap – <dc:title> and <dc:description> fields
• Map items to Wikipedia • Apply graph-based measures
Computing Similarity in Europeana
Graph creation
title: woman title:
reclining title: nude
title: seated
title: thin
title: figure
title: head
Item:925673 930075 929829
930638 981684 title: neck
title: necklace
Graph creation
title: woman title:
reclining title: nude
title: seated
title: thin
title: figure
title: head
Item:925673 930075 929829
930638 981684 title: neck
artist: Pablo
Picasso
artist: Henry Moore
title: necklace
Paths project: • Aim to improve access to large Cultural Heritage
collections • Research areas:
– Information Access – Educational Informatics
– Content Processing and Enrichment
• Processing Europeana data – Determining similarity – Mapping to external resources
Conclusions
