Metadata Visualization of Cultural Heritage Information within a Collaborative Environment

Cultural content on the Web is available in various domains (cultural objects, datasets, geospatial data, moving images, scholarly texts and visual resources), concerns various topics, is written in different languages, targeted to both laymen and experts, and provided by different communities (libraries, archives museums and information industry) and individuals (Figure 1). The integration of information technologies and cultural heritage content on the Web is expected to have an impact on everyday life from the point of view of institutions, communities and individuals. In particular, collaborative environment scan recreate 3D navigable worlds that can offer new insights into our cultural heritage (Chan 2007). However, the main barrier is to find and relate cultural heritage information by end-users of cultural contents, as well as by organisations and communities managing and producing them. In this paper, we explore several visualisation techniques for supporting cultural interfaces, where the role of metadata is essential for supporting the search and communication among end-users (Figure 2). A conceptual framework was developed to integrate the data, purpose, technology, impact, and form components of a collaborative environment, Our preliminary results show that collaborative environments can help with cultural heritage information sharing and communication tasks because of the way in which they provide a visual context to end-users. They can be regarded as distributed virtual reality systems that offer graphically realised, potentially infinite, digital information landscapes. Moreover, collaborative environments also provide a new way of interaction between an end-user and a cultural heritage data set. Finally, the visualisation of metadata of a dataset plays an important role in helping end-users in their search for heritage contents on the Web.

Generating Awareness from Collaborative Working Environment using Social Data

Nowadays, Internet is a place where social networks have reached an important impact in collaboration among people over the world in different ways. This article proposes a new paradigm for building CSCW business tools following the novel ideas provided by the social web to collaborate and generate awareness. An implementation of these concepts is described, including the components we provide to collaborate in workspaces, (such as videoconference, chat, desktop sharing, forums or temporal events), and the way we generate awareness from these complex social data structures. Figures and validation results are also presented to stress that this architecture has been defined to support awareness generation via joining current and future social data from business and social networks worlds, based on the idea of using social data stored in the cloud.

A Balanced Memory-Based Collaborative Filtering Similarity Measure.

Collaborative filtering recommender systems contribute to alleviating the problem of information overload that exists on the Internet as a result of the mass use of Web 2.0 applications. The use of an adequate similarity measure becomes a determining factor in the quality of the prediction and recommendation results of the recommender system, as well as in its performance. In this paper, we present a memory-based collaborative filtering similarity measure that provides extremely high-quality and balanced results; these results are complemented with a low processing time (high performance), similar to the one required to execute traditional similarity metrics. The experiments have been carried out on the MovieLens and Netflix databases, using a representative set of information retrieval quality measures.

Using online presence to improve online collaborative learning

Social software tools have become an integral part of students? personal lives and their primary communication medium. Likewise, these tools are increasingly entering the enterprise world (within the recent trend known as Enterprise 2.0) and becoming a part of everyday work routines. Aiming to keep the pace with the job requirements and also to position learning as an integral part of students? life, the field of education is challenged to embrace social software. Personal Learning Environments (PLEs) emerged as a concept that makes use of social software to facilitate collaboration, knowledge sharing, group formation around common interests, active participation and reflective thinking in online learning settings. Furthermore, social software allows for establishing and maintaining one?s presence in the online world. By being aware of a student's online presence, a PLE is better able to personalize the learning settings, e.g., through recommendation of content to use or people to collaborate with. Aiming to explore the potentials of online presence for the provision of recommendations in PLEs, in the scope of the OP4L project, we have develop a software solution that is based on a synergy of Semantic Web technologies, online presence and socially-oriented learning theories. In this paper we present the current results of this research work.

Opportunities and Challenges of Implementing P2P Streaming Applications in the Web

P2P applications are increasingly present on the web. We have identified a gap in current proposals when it comes to the use of traditional P2P overlays for real-time multimedia streaming. We analyze the possibilities and challenges to extend WebRTC in order to implement JavaScript APIs for P2P streaming algorithms.

Improving Collaborative Filtering Based Recommender Systems Using Pareto Dominance

Los sistemas de recomendación son un tipo de solución al problema de sobrecarga de información que sufren los usuarios de los sitios web en los que se pueden votar ciertos artículos. El sistema de recomendación de filtrado colaborativo es considerado como el método con más éxito debido a que sus recomendaciones se hacen basándose en los votos de usuarios similares a un usuario activo. Sin embargo, el método de filtrado de colaboración tradicional selecciona usuarios insuficientemente representativos como vecinos de cada usuario activo. Esto significa que las recomendaciones hechas a posteriori no son lo suficientemente precisas. El método propuesto en esta tesis realiza un pre-filtrado del proceso, mediante el uso de dominancia de Pareto, que elimina los usuarios menos representativos del proceso de selección k-vecino y mantiene los más prometedores. Los resultados de los experimentos realizados en MovieLens y Netflix muestran una mejora significativa en todas las medidas de calidad estudiadas en la aplicación del método propuesto. ABSTRACTRecommender systems are a type of solution to the information overload problem suffered by users of websites on which they can rate certain items. The Collaborative Filtering Recommender System is considered to be the most successful approach as it make its recommendations based on votes of users similar to an active user. Nevertheless, the traditional collaborative filtering method selects insufficiently representative users as neighbors of each active user. This means that the recommendations made a posteriori are not precise enough. The method proposed in this thesis performs a pre-filtering process, by using Pareto dominance, which eliminates the less representative users from the k-neighbor selection process and keeps the most promising ones. The results from the experiments performed on Movielens and Netflix show a significant improvement in all the quality measures studied on applying the proposed method.

Aplicación web para la realización de experimentos astronómicos del proyecto GLORIA en la plataforma Facebook

La Ciencia Ciudadana nace del resultado de involucrar en las investigaciones científicas a todo tipo de personas, las cuales pueden participar en un determinado experimento analizando o recopilando datos. No hace falta que tengan una formación científica para poder participar, es decir cualquiera puede contribuir con su granito de arena. La ciencia ciudadana se ha convertido en un elemento a tener en cuenta a la hora de realizar tareas científicas que requieren mucha dedicación, o que simplemente por el volumen de trabajo que estas implican, resulta casi imposible que puedan ser realizadas por una sola persona o un pequeño grupo de trabajo. El proyecto GLORIA (GLObal Robotic-telescopes Intelligent Array) es la primera red de telescopios robóticos del mundo de acceso libre que permite a los usuarios participar en la investigación astronómica mediante la observación con telescopios robóticos, y/o analizando los datos que otros usuarios han adquirido con GLORIA, o desde otras bases de datos de libre acceso. Con el objetivo de contribuir a esta iniciativa se ha propuesto crear una plataforma web que pasará a formar parte del Proyecto GLORIA, en la que se puedan realizar experimentos astronómicos. Con el objetivo de fomentar la ciencia y el aprendizaje colaborativo se propone construir una aplicación web que se ejecute en la plataforma Facebook. Los experimentos los proporciona la red de telescopios del proyecto GLORIA mediante servicios web y están definidos mediante XML. La aplicación web recibe el XML con la descripción del experimento, lo interpreta y lo representa en la plataforma Facebook para que los usuarios potenciales puedan realizar los experimentos. Los resultados de los experimentos realizados se envían a una base de datos de libre acceso que será gestionada por el proyecto GLORIA, para su posterior análisis por parte de expertos. ---ABSTRACT---The citizen’s science is born out of the result of involving all type of people in scientific investigations, in which, they can participate in a determined experiment analyzing or compiling data. There is no need to have a scientific training in order to participate, but, anyone could contribute doing one’s bit. The citizen’s science has become an element to take into account when carrying out scientific tasks that require a lot dedication, or that, for the volume of work that these involve, are nearly impossible to be carried out by one person or a small working group. The GLORIA Project (Global Robotic-Telescopes Intelligent Array) is the first network of free access robotic telescopes in the world that permits the users to participate in the astronomic investigation by means of observation with robotic telescopes, and/or analyzing data from other users that have obtained through GLORIA, or from other free-access databases. With the aim of contributing to this initiative, a web platform has been created and will be part of the GLORIA Project, in which astronomic experiments can be carried out. With the objective of promoting science and collaborative apprenticeship, a web application carried out in the FACEBOOK platform is to be built. The experiments are founded by the telescopes network of the GLORIA project by means of web services and are defined through XML. The web application receives the XML with the description of the experiment, interprets it and represents it in the FACEBOOK platform in order for potential users may perform the experiments. The results of the experiments carried out are sent to a free-access database that will be managed by the GLORIA Project for its analysis on the part of experts.

Global research alliance modelling platform (GRAMP): an open web platform for modelling greenhouse gas emissions from agro-ecosystems

Carbon (C) and nitrogen (N) process-based models are important tools for estimating and reporting greenhouse gas emissions and changes in soil C stocks. There is a need for continuous evaluation, development and adaptation of these models to improve scientific understanding, national inventories and assessment of mitigation options across the world. To date, much of the information needed to describe different processes like transpiration, photosynthesis, plant growth and maintenance, above and below ground carbon dynamics, decomposition and nitrogen mineralization. In ecosystem models remains inaccessible to the wider community, being stored within model computer source code, or held internally by modelling teams. Here we describe the Global Research Alliance Modelling Platform (GRAMP), a web-based modelling platform to link researchers with appropriate datasets, models and training material. It will provide access to model source code and an interactive platform for researchers to form a consensus on existing methods, and to synthesize new ideas, which will help to advance progress in this area. The platform will eventually support a variety of models, but to trial the platform and test the architecture and functionality, it was piloted with variants of the DNDC model. The intention is to form a worldwide collaborative network (a virtual laboratory) via an interactive website with access to models and best practice guidelines; appropriate datasets for testing, calibrating and evaluating models; on-line tutorials and links to modelling and data provider research groups, and their associated publications. A graphical user interface has been designed to view the model development tree and access all of the above functions.