Showing papers by "Peter Brusilovsky published in 2010"

Second workshop on information heterogeneity and fusion in recommender systems (HetRec2011)

Abstract: 1. MOTIVATION AND GOALS In recent years, increasing attention has been given to finding ways for combining, integrating and mediating heterogeneous sources of information for the purpose of providing better personalized services in many information seeking and ecommerce applications. Information heterogeneity can indeed be identified in any of the pillars of a recommender system: the modeling of user preferences, the description of resource contents, the modeling and exploitation of the context in which recommendations are made, and the characteristics of the suggested resource lists.

Guiding students to the right questions: adaptive navigation support in an E-Learning system for Java programming

Abstract: Rapid growth of the volume of interactive questions available to the students of modern E-Learning courses placed the problem of personalized guidance on the agenda of E-Learning researchers. Without proper guidance, students frequently select too simple or too complicated problems and ended either bored or discouraged. This paper explores a specific personalized guidance technology known as adaptive navigation support. We developed JavaGuide, a system, which guides students to appropriate questions in a Java programming course, and investigated the effect of personalized guidance a three-semester long classroom study. The results of this study confirm the educational and motivational effects of adaptive navigation support.

Learning SQL Programming with Interactive Tools: From Integration to Personalization

Abstract: Rich, interactive eLearning tools receive a lot of attention nowadays from both practitioners and researchers. However, broader dissemination of these tools is hindered by the technical difficulties of their integration into existing platforms. This article explores the technical and conceptual problems of using several interactive educational tools in the context of a single course. It presents an integrated Exploratorium for database courses, an experimental platform, which provides personalized access to several types of interactive learning activities. Several classroom studies of the Exploratorium have demonstrated its value in both the integration of several tools and the provision of personalized access.

Social networks and interest similarity: the case of CiteULike

Abstract: In collaborative filtering recommender systems, there is little room for users to get involved in the choice of their peer group. It leaves users defenseless against various spamming or ''shilling'' attacks. Other social Web-based systems, however, allow users to self-select peers and build a social network. We argue that users' self-defined social networks could be valuable to increase the quality of recommendation in CF systems. To prove the feasibility of this idea we examined how similar are interests of users connected by self-defined relationships in a collaborative tagging systems Citeulike. Interest similarity was measured by similarity of items and meta-data they share and tags they use. Our study shows that users connected by social networks exhibit significantly higher similarity on all explored levels (items, meta-data, and tags) than non-connected users. This similarity is the highest for directly connected users and decreases with the increase of distance between users. Among other interesting properties of information sharing is the finding that between-user similarity in social connections on the level of metadata and tags is much larger than similarity on the level of items. Overall, our findings support the feasibility of social network based recommender systems and offer some good hints to the prospective authors of these systems.

Conference Navigator 2.0: Community-Based Recommendation for Academic Conferences

Abstract: As the sheer volume of information grows, information overload challenges users in many ways. Large conferences are one of the venues suffering from this overload. Faced with several parallel sessions and large volumes of papers covering diverse areas of interest, conference participants often struggle to identify the most relevant sessions to attend. The Conference Navigator 2.0 system was created to help conference participants go examine the schedule of paper presentation, add most interesting papers to individual schedule, and export this schedule to a calendar application. In addition, as a social system, the Conference Navigator 2.0 collects the wisdom of the user community and make it available through community-based recommendation interface to help individuals in making scheduling decisions.

Semantic annotation based exploratory search for information analysts

Abstract: The system presented in this article aims to improve information access through the use of semantic annotation utilizing a non-traditional approach. Instead of applying semantic annotations to enhance the internal information access mechanisms, we use them to empower the user of an information access system through an innovative named entity-based user interface - NameSieve. NameSieve was built to support an intelligence analyst during the process of exploratory search, an advanced type of search requiring multiple iterations of retrieval interleaved with browsing and analyzing the retrieved information. The proposed approach was implemented in the NameSieve system so that the system can transparently present a summary of search results in the form of entity ''clouds.'' Therefore, these clouds allow the analyst to further explore the results in a novel manner, acting together as a faceted browsing interface. We ran a user study (with ten subjects) to examine the effect of NameSieve, and the study results reported in the paper demonstrate that this new way of applying semantic annotation information was actively used and was evaluated positively by the subjects. It enabled the subjects to work more productively and bring back most relevant documents.

Improving Collaborative Filtering in Social Tagging Systems for the Recommendation of Scientific Articles

Abstract: Social tagging systems pose new challenges to developers of recommender systems. As observed by recent research, traditional implementations of classic recommender approaches, such as collaborative filtering, are not working well in this new context. To address these challenges, a number of research groups worldwide work on adapting these approaches to the specific nature of social tagging systems. In joining this stream of research, we have developed and evaluated two enhancements of user-based collaborative filtering algorithms to provide recommendations of articles on Cite ULike, a social tagging service for scientific articles. The result obtained after two phases of evaluation suggests that both enhancements are beneficial. Incorporating the number of raters into the algorithms, as we do in our NwCF approach, leads to an improvement of precision, while tag-based BM25 similarity measure, an alternative to Pearson correlation for calculating the similarity between users and their neighbors, increases the coverage of the recommendation process.

Final report, independent Study during Fall 2009 "Improving Collaborative Filtering in Social Tagging Systems for the Recommendation of Scientific Articles"

Abstract: This report describes our study of different ways to improve existing collaborative filtering techniques in order to recommend scientific articles. Using data crawled from CiteUlike, a collaborative tagging service for academic purposes, we compared the classical user-based collaborative filtering algorithm as described by Schafer et al. [2], with two enhanced variations: 1) using a tag-based similarity calculation, to avoid depending on ratings to find the neighborhood of a user, and 2) incorporate the amount of raters in the final recommendation ranking to decrease the noise of items that have been rated by too few users. We provide a discussion of our results, describing the dataset and highlighting our findings about applying collaborative filtering on folksonomies instead of the classic bipartite user-item network, and providing guidelines of our future research.

User-adaptive explanatory program visualization: evaluation and insights from eye movements

Abstract: User-adaptive visualization and explanatory visualization have been suggested to increase educational effectiveness of program visualization. This paper presents an attempt to assess the value of these two approaches. The results of a controlled experiment indicate that explanatory visualization allows students to substantially increase the understanding of a new programming topic. Furthermore, an educational application that features explanatory visualization and employs a user model to track users' progress allows students to interact with a larger amount of material than an application which does not follow users' activity. However, no support for the difference in short-term knowledge gain between the two applications is found. Nevertheless, students admit that they prefer the version that estimates and visualizes their progress and adapts the learning content to their level of understanding. They also use the application's estimation to pace their work. The differences in eye movement patterns between the applications employing adaptive and non-adaptive explanatory visualizations are investigated as well. Gaze-based measures show that adaptive visualization captivates attention more than its non-personalized counterpart and is more interesting to students. Natural language explanations also accumulate a big portion of students' attention. Furthermore, the results indicate that working memory span can mediate the perception of adaptation. It is possible that user-adaptation in an educational context provides a different service to people with different mental processing capabilities.

Social navigation for educational digital libraries

Abstract: An educational digital library may store a wealth of diverse educational resources targeting different audiences from young schoolchildren to graduate students to school and college teachers. With the growth of the volume and the diversity of the library, it becomes increasingly difficult for the users to find resources, which are relevant to their age, educational needs, and personal interests. Social navigation techniques could provide valuable help in this context guiding users to the most useful information. Social navigation works by processing traces of past user behavior and using the assembled “collective wisdom” to guide future users. The paper reports our work on the design of social navigation infrastructure for Ensemble, a major educational digital library. We present the organization of both sides of the social navigation process: how social wisdom is collected and how it can be used to guide portal users to valuable resources. We also report the results of our most recent evaluation of the social navigation infrastructure.

ImageSieve: exploratory search of museum archives with named entity-based faceted browsing

Abstract: Over the last few years, faceted search emerged as an attractive alternative to the traditional "text box" search and has become one of the standard ways of interaction on many e-commerce sites. However, these applications of faceted search are limited to domains where the objects of interests have already been classified along several independent dimensions, such as price, year, or brand. While automatic approaches to generate faceted search interfaces were proposed, it is not yet clear to what extent the automatically-produced interfaces will be useful to real users, and whether their quality can match or surpass their manually-produced predecessors. The goal of this paper is to introduce an exploratory search interface called ImageSieve, which shares many features with traditional faceted browsing, but can function without the use of traditional faceted metadata. ImageSieve uses automatically extracted and classified named entities, which play important roles in many domains (such as news collections, image archives, etc.). We describe one specific application of ImageSieve for image search. Here, named entities extracted from the descriptions of the retrieved images are used to organize a faceted browsing interface, which then helps users to make sense of and further explore the retrieved images. The results of a user study of ImageSieve demonstrate that a faceted search system based on named entities can help users explore large collections and find relevant information more effectively.

Using self-defined group activities for improvingrecommendations in collaborative tagging systems

Abstract: This paper aims to combine information about users' self-defined social connections with traditional collaborative filtering (CF) to improve recommendation quality. Specifically, in the following, the users' social connections in consideration were groups. Unlike other studies which utilized groups inferred by data mining technologies, we used the information about the groups in which each user explicitly participated. The group activities are centered on common interests. People join a group to share and acquire information about a topic as a form of community of interest or practice. The information of this group activity may be a good source of information for the members. We tested whether adding the information from the users' own groups or group members to the traditional CF-based recommendations can improve the recommendation quality or not. The information about groups was combined with CF using a mixed hybridization strategy. We evaluated our approach in two ways, using the Citeulike data set and a real user study.

Collaborative information finding in smaller communities: The case of research talks

Abstract: Social navigation and social tagging technologies enable user communities to assemble the collective wisdom, and use it to help community members in finding the right information. However, it takes a significantly-sized community to make a social system truly useful. The question addressed in this paper is whether collaborative information finding is feasible in the context of smaller communities. To answer this question, we developed two social systems specifically focused on smaller communities - CoMeT and Conference Navigator II - and explored several techniques to increase the volume of user contributions. This paper reviews the explored techniques and presents empirical evidence that demonstrate their effectiveness.

Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems

Abstract: The 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems (HetRec 2011) was held in Chicago, IL, USA, on the 27th of October 2011, under the frame of the 5th ACM Conference on Recommender Systems (RecSys 2011). HetRec workshop represented a meeting point for researchers and practitioners interested in addressing the challenges posed by information heterogeneity in recommender systems and studying information fusion in this context. In this second edition, we made available on-line datasets with heterogeneous information from several social systems. These datasets could be used by participants to experiment and evaluate their recommendation approaches, and can be enriched with additional data, which may be published at the workshop website for future use. These datasets are kindly hosted by GroupLens research group at University of Minnesota. A total of ten papers were presented at the workshop. There were six long papers, and four short papers. Fourteen submissions were received, and each of them was reviewed by two members of the Program Committee.

Ensemble PDP-8: eight principles for distributed portals

Abstract: Ensemble, the National Science Digital Library (NSDL) Pathways project for Computing, builds upon a diverse group of prior NSDL, DL-I, and other projects. Ensemble has shaped its activities according to principles related to design, development, implementation, and operation of distributed portals. Here we articulate 8 key principles for distributed portals (PDPs). While our focus is on education and pedagogy, we expect that our experiences will generalize to other digital library application domains. These principles inform, facilitate, and enhance the Ensemble R&D and production activities. They allow us to provide a broad range of services, from personalization to coordination across communities. The eight PDPs can be briefly summarized as: (1) Articulation across communities using ontologies. (2) Browsing tailored to collections. (3) Integration across interfaces and virtual environments. (4) Metadata interoperability and integration. (5) Social graph construction using logging and metrics. (6) Superimposed information and annotation integrated across distributed systems. (7) Streamlined user access with IDs. (8) Web 2.0 multiple social network system interconnection.

Teaching Information Retrieval With Web-based Interactive Visualization

Abstract: Interactive visualization is a powerful educational tool, which has been used to enhance the teaching of various subjects from computer science to chemistry to engineering. This paper describes the use of interactive visualization tools in the context of a graduate course in information retrieval, to demonstrate two well-known retrieval models, the Boolean model and the vector space model. The results of five classroom studies with these tools are reported. The impact of the tools on student learning, as well as student attitudes toward the tools, were investigated. The results of the classroom studies indicate that use of interactive visualization in a homework context can result in significant growth of knowledge. The majority of the students recognize the value of interactive visualization and recommend its use in the context of information retrieval courses. The study also demonstrated that visualization focusing on less known and harder to understand topics causes a larger growth of knowledge and is perceived as more useful. This result suggests placing higher priority on the development of visualization tools for harder to understand topics.

Can concept-based user modeling improve adaptive visualization?

Abstract: Adaptive visualization can present user-adaptive information in such a way as to help users to analyze complicated information spaces easily and intuitively We presented an approach called Adaptive VIBE, which extended the traditional reference point-based visualization algorithm, so that it could adaptively visualize documents of interest The adaptive visualization was implemented by separating the effects of user models and queries within the document space and we were able to show the potential of the proposed idea However, adaptive visualization still remained in the simple bag-of-words realm The keywords used to construct the user models were not effective enough to express the concepts that need to be included in the user models In this study, we tried to improve the old-fashioned keyword-only user models by adopting more concept-rich named-entities The evaluation results show the strengths and shortcomings of using named-entities as conceptual elements for visual user models and the potential to improve the effectiveness of personalized information access systems.

Interest Similarity of Group Members: The Case Study of CiteULike

Abstract: Web 2.0 era, where users play not only a role of information consumers, but information creators, produced very complicated online landscape consisting of information items and users collected by various ways explicitly and implicitly. A number of researchers now focus on understanding this landscape, discover its connections with real life, and build practical application on the basis of these discoveries. Among these topics, one that attracts considerable attentions is the correlation between user connections in the Web world and their similarities in real life. Recent research demonstrated, for example, that users engaged into active forum discussion have more similar interests than non connected users and users who exchanged instant messages frequently had more similar search queries than random pairs. Unlike other studies focused on friendships, this study considered users’ self-defined group activities as social networks. Group activities are centered on the utility of information usefulness. Users join the same group on the Web because they are interested in the same topic in terms of a community of interest or practice. The relationships in group networks are known to be self-organized by the members and aim to distribute topic-relevant information or contribute related activities. Surprisingly enough, however, the information similarity of self-defined user groups were not yet explored. Most studies about group dynamics and information sharing patterns in groups focused on derived communities which are discovered systematically by pattern mining approaches. This study is to explore users’ self-defined groups and the interactions among the group members. The group networks were collected at a real collaborative tagging system, Citeulike. Out of more than 700 groups, after filtering out single-member groups and groups having insufficient references (n

Social Navigation in Web Lectures: A Study of VirtPresenter

Abstract: Purpose – Social navigation is an emerging trend for navigation in hypermedia. With social navigation, users can be guided through large volumes of learning content by cues which integrate the browsing history of past users. Earlier papers have shown that social navigation is suitable for navigation not only in classic hypermedia but also in time‐based learning media like web lectures by presenting prototype implementations. The purpose of this paper is to report on user experiences with social navigation for web lectures in the classroom.Design/methodology/approach – This paper presents results obtained from a two‐term classroom study with a social navigation interface for web lectures. The study comprises both log file analysis and student questionnaires. The interface used in the study implements a footprint‐based social navigation approach for time‐based continuous media such as web lectures.Findings – The results of the user study show that social navigation cues significantly affect user lecture nav...

The value of adaptive link annotation in e-learning: a study of a portal-based approach

Abstract: Adaptive link annotation is one of the most popular adaptive educational hypermedia techniques. It has been widely studied and demonstrated its ability to help students to acquire knowledge faster, improve learning outcomes, reduce navigation overhead, increase motivation, and encourage the beneficial non-sequential navigation. However, almost all studies of adaptive link annotation have been performed in the context of dedicated adaptive educational hypermedia systems. The role of this technique in the context of widely popular learning portals has not yet been demonstrated. In this paper, we attempt to fill this gap by investigating the value of adaptive navigation support embedded into the learning portal. We compare the effect of portal-based adaptive navigation support to both the effect of the adaptive navigation support in adaptive educational hypermedia systems and to non-adaptive learning portals.

Enhancing digital libraries with social navigation: the case of ensemble

Abstract: A traditional library is a social place, however the social nature of the library is typically lost when the library goes digital. This paper argues social navigation, an important group of social information access techniques, could be used to replicate some social features of traditional libraries and to enhance the user experience. Using the case of Ensemble, a major educational digital library, the paper describes how social navigation could be used to extend digital library portals, how social wisdom can be collected, and how it can be used to guide portal users to valuable resources.

Ensemble: enriching communities and collections to support education in computing: poster session

Abstract: Ensemble is a new NSF NSDL Pathways project working to establish a national, distributed digital library for computing education. Ensemble is building a distributed portal providing access to a broad range of existing educational resources for computing while preserving the collections and their associated curation processes. CITIDEL and CSTA are two of the major educational resources that are part of this expanding collection. We want to encourage contribution, use, reuse, review and evaluation of educational materials at multiple levels of granularity and we seek to support the full range of computing education communities including computer science, computer engineering, software engineering, information science, information systems and information technology as well as other areas often called "computing + X" or "X informatics". The various aspects of the project include: (1) developing a distributed portal, (2) defining appropriate metadata and methods for indexing computing resources - including using an ontology to describe computing topics, (3) instrumenting the portal so that we can track use and reuse of resources (so that faculty can easily get metrics analogous to citation counts for the educational resources that they create), (4) integrating social software into the portal, (5) developing mechanisms to handle use of resources at multiple levels of granularity, (6) articulation of the various topics and how they overlap in the various computing disciplines, (8) user development and dissemination, (9) information finding and collection development, and (10) evaluation. Ensemble provides content, communities, and tools for computing educators and students. The content consists of freely available computing education resources stored within Ensemble or at other locations. Ensemble provides federated search, indexing, annotation, reviews, and other services to make these resources accessible, visible, and more useful to the community. Ensemble also provides other sources of information of interest to computing educators. This content includes information streams such as news, event notices, and blogs. Ensemble communities support interaction among computing educators via facilities such as discussion forums, posting of working papers, and connections to venues such as Twitter and Facebook. These services support open collaborations such as a CS1 community site and also hosts closed working spaces for groups like the ACM Education Board and the Future of Computing Education Summit working groups. Ensemble tools provide access to more advanced facilities to help instructors and students' access and organize materials relevant to computing education. An example is Visual Knowledge Builder, which provides a workspace for collecting and organizing computing education resources. Ensemble also includes an alternate interface accessed via the Ensemble pavilion in Second Life. Ensemble supports the full range of computing disciplines and also programs that blend computing with other STEM areas (e.g., X-informatics and Computing + X). Ensemble is funded by the National Science Foundation via the NSDL Pathways program.

What you see is what you search: adaptive visual search framework for the web

Abstract: Information retrieval is one of the most popular information access methods for overcoming the information overload problem of the Web. However, its interaction model is still utilizing the old text-based ranked lists and static interaction algorithm. In this paper, we introduce our adaptive visualization approach for searching the Web, which we call Adaptive VIBE. It is an extended version of a reference point-based spatial visualization algorithm, and is designed to serve as a user interaction module for a personalized search system. Personalized search can incorporate dynamic user interests and different contexts, improving search results. When it is combined with adaptive visualization, it can encourage users to become involved in the search process more actively by exploring the information space and learning new facts for effective searching. In this paper, we introduce the rationale and functions of our adaptive visualization approach and discuss the approaches' potential to create a better search environment for the Web.

Recommending research colloquia: a study of several sources for user profiling

Abstract: The study reported in this paper is an attempt to improve content-based recommendation in CoMeT, a social system for sharing information about research colloquia in Carnegie Mellon and University of Pittsburgh campuses. To improve the quality of recommendation in CoMeT, we explored three additional sources for building user profiles: tags used by users to annotate CoMeT's talks, partial content of CiteULike papers bookmarked by users, and tags used to annotate CiteULike papers. We also compare different tag integration models to study the impact of information fusion on recommendations outcome. The results demonstrate that information encapsulated in CiteULike bookmarks generally helps to improve several aspects of recommendation. The addition of tags by fusing them into keyword profiles helps to improve precision and novelty of recommendation, but may harm systems ability to recommend generally interesting talks. The effects of tags and bookmarks appeared to be stackable.

Proceedings of the fifth ACM workshop on Research advances in large digital book repositories and complementary media

Abstract: It is our great pleasure to welcome you to the BooksOnline 2012 Workshop on Research Advances in Large Digital Book Repositories and Complementary Media. This year, the fifth edition of the workshop series focuses on the readers, their experiences and their specific needs and preferences in terms of content selection, presentation and adjunct comprehension support technologies. In many domains, such as Web search, content recommendation, and online social networks, personalized services have been able to greatly benefit users. The domain of digital reading is no exception in this trend. When browsing online book stores, reading group discussions or book recommendations shared among friends, the strong personal aspects that apply to book selection become obvious. This becomes especially relevant in the case of user groups with specific or special needs, such as young readers or people with disabilities. The central role of the reader is reflected in the range of accepted contributions to this year's workshop. The accepted contributions naturally showed three salient themes: (1) "Search and Discovery", encompassing work addressing serendipitous content discovery, customizable information filtering as well as faceted topic exploration; (2) "Personalization and Recommendation", introducing reader-centric means of content selection based on comprehensibility and entertainment; and (3) "Reading Experiences beyond Text", proposing novel content presentation paradigms addressing accessibility concerns. We are honoured to welcome as our keynote speakers two industry leaders and visionaries, Maribeth Back (FX Labs Palo Alto) who will share her work on the "Future of Digital Reading" and Natasa Milic-Frayling (Microsoft Research) who will talk about her research on techniques to facilitate long-term access to digital content. We hope that you will find the workshop's program interesting and thought-provoking and that the workshop will provide you with a valuable opportunity to share ideas with other researchers and practitioners from institutions around the world.

Using Numeric Optimization To Refine Semantic User Model Integration Of Adaptive Educational Systems.

Abstract: Nowadays, it is a common practice to use several educational systems in one domain. In this situation, each of the systems should be able to provide the best user modeling based on the integrated data about the user. However, differences in domain conceptualization complicate the ability of the systems to understand each other’s user models and necessitate the use of labor intensive and time consuming alignment procedures that require involvement of knowledge engineers. While the latter are best at detecting associative links between the user model items, they fail to reliably identify the strengths of these associations. In this paper, we are proposing a method to improve the user model mapping by using a numerical optimization procedure. Our results show that numerical weight optimization helped to decrease the amount of manual work and improved the target model accuracy.

Interest Similarity of Group and the Members: the Case study of Citeulike

Abstract: In this Web 2.0 era, many social Web systems support group activities. Groups are centered on the utility of information usefulness. Users join the same group on the Web because they are interested in the same topic in terms of a community of interest or practice. Herein, we examine the information similarity in self-defined group networks and specifically address not only the similarities between the same group members, but also the similarities between a group and the members. Our study found that a pair of users who are the members of the same group share significantly higher similarity in their personal collection than other pairs who are not members of any of the same groups on all explored levels (items, metadata, and tags). Especially, the degrees of similarity on the metadata and tag levels are much larger than the item similarity. The degree of the similarities between a group and the members, however, is much higher than the similarities of the same group members. More than 40% of all users have collections which are at least 50% overlapped with their group’s collections. These results show that group is good source of information, but each member has his own specific information needs and it is rarely similar to other members. Another interesting property of information-sharing in groupbased networks is that the number of groups that a user joined has significantly positive correlation with the size of their personal collection. Lastly, some members play an active role in introducing interesting information to their groups and further, some other members were perfectly influenced by the group collection (100% matches with the group collection). Overall, our findings support that groups could be feasible for guiding users to useful information.

3rd BooksOnline workshop: research advances in large digital book repositories and complementary media

Abstract: The goal of the 3rd BooksOnline Workshop is to bring together researchers and industry practitioners in information retrieval, digital libraries, e-books, human computer interaction, publishing industry, and online book services to foster progress on addressing challenges and exploring opportunities around large collections of digital books and complementary media. Towards this goal, the workshop programme consists of contributions both from academia and industry, including two keynote talks: James Crawford from Google Books and John Mark Ockerbloom from the University of Pennsylvania.

Ensemble: a distributed portal for the distributed community of computing education

Abstract: NSF's NSDL is composed of domain-oriented pathways. Ensemble is the pathway for computing and supports the full range of computing education communities, providing a base for the development of programs that blend computing with other STEM areas (e.g., X-informatics and Computing + X), and producing digital library innovations that can be propagated to other NSDL pathways. Computing is a distributed community, including computer science, computer engineering, software engineering, information science, information systems, and information technology. Ensemble aims to provide much needed support for the many distinct yet overlapping educational programs in computing and their associated communities. To do this, Ensemble takes the form of a distributed portal providing access to the broad range of existing educational resources while preserving the collections and their associated curatorial processes. Ensemble encourages contribution, use, reuse, review, and evaluation of educational materials at multiple levels of granularity.

Multiple sources with multiple portals: a demonstration of the ensemble computing portal in second life

Abstract: This demonstration is an overview of our Ensemble pathway project with group members on-location at the conference and in the virtual world of Second Life from remote locations providing a live walk-through tour of our project online. This approach allows the demonstration to extend beyond the allocated conference session as a means to attract people to JCDL/ICADL.