Reflection Support Using Multi-encoded Tag-clouds

Glahn, C., Specht, M., & Koper, R. (2009). Reflection Support Using Multi-encoded Tag-clouds. In F. Wild, M. Kalz, M. Palmér & D. Müller (Eds.), Proceedings of 2nd Workshop Mash-Up Personal Learning Envrionments (MUPPLE'09). Workshop in conjunction with 4th European Conference on Technology Enhanced Learning (EC-TEL 2009): Synergy of Disciplines (pp. 89-97). September, 29, 2009, Nice, France: CEUR workshop proceedings, http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-506/ .This paper reports on a qualitative study about the application of tag clouds for supporting meta-cognition in self-directed and incidental learning. It analyses the use of a personal tag-cloud visualization of the tags that are used at a public social bookmarking service. The study focuses at the types of meta- cognitive control based on reflection notes of the learners. These notes were analyzed regarding the contents of the reflections as well as regarding their meta-cognitive type. The study has two important outcomes. Firstly, a personal tag cloud can stimulate reflection on the tagging activity of a learner. Secondly, reflecting on the tagging activity is not built into the design of a tag cloud.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

Reflecting on Web-readings with Tag Clouds

Tagging has become one of the key activities of Web2.0 applications. This paper analyses the potential of using tag clouds for stimulating and supporting reflection of individual users in informal learning. We introduce the ReScope widget, a Javascript widget that generates a tag cloud, which represents tags on the levels of global and recent usage. The first prototype of ReScope has been used to identify actual use cases for reflection support. In this paper we analyse these use cases and the related design criteria.

Distribución y uso de modelos 3D en la web: ¿estamos listos?

[EN] Digital technologies are now mature for producing high quality digital replicas of Cultural Heritage (CH) assets. The research results produced in the last decade ignitedan impressive evolution and consolidation of the technologies for acquiring high-quality digital three-dimensional (3D)models, encompassing both geometry and color. What remains still an open problem is how to deliver those data and related knowledge to our society. The web is nowadays the main channel for the dissemination of knowledge. Emerging commercial solutions for web-publishing of 3D data are consolidating and becoming a de-facto standard for many applications(e-commerce, industrial products, education, etc.).In this framework, CH is a very specific domain, requiring highly flexible solutions. Some recent experiences arepresented, aimed at providing a support to the archival of archaeological3Ddata, supporting web-based publishing of very high-resolution digitization results and finally enabling the documentation of complex restoration actions. All those examples have been recently implemented on the open-source 3D Heritage Online Presenter (3DHOP)platform, developed at CNR-ISTI[ES] Las tecnologías digitales estánahora maduraspara producir réplicas digitales de alta calidad de valores activos del patrimonio cultural (CH). Los resultados de la investigación producidos en la última década han mostrado una evolución impresionante y una consolidación de las tecnologías para la capturade modelos digitales tridimensionales (3D)de alta calidad, que abarcanla geometríay el color.Lo que queda aún por resolver estárelacionado con la forma de distribuirlos datos y el conocimiento relacionado conla sociedad. La web es hoy en día el principal canal utilizado para divulgarel conocimiento. Las soluciones comerciales nuevas relacionadas con la publicación en la red de datos en 3D se están consolidando y convirtiendo en un estándar de facto para muchas aplicaciones(comercio electrónico, productos industriales, educación, etc.). En este escenario, el patrimonio culturales un dominio muy específico, que requiere soluciones muyflexibles.Se presentan algunas experiencias recientes, destinadasa proporcionar un apoyo al archivo de los datos arqueológicos3D, la publicaciónwebde los resultados de digitalización de muy alta resoluciónque permitenfinalmente la documentación de trabajos de restauracióncomplejos. Todos estos ejemplos se han implementado recientemente en la plataforma 3D Heritage Online Presenter(3DHOP)de código abierto, desarrolladaen el CNR-ISTI.The research leading to these results has received funding from the EU 7th Framework Programme (FP7/2007-2013) under grant agreement no. 654119 (EC "PARTHENOS" project) and EU H2020 Programme (“EMOTIVE: EMOTIve Virtual cultural Experiences through personalized storytelling”, H2020-SC6-CULT-COOP-08-2016) under grant agreement no. 727188.Scopigno, R.; Callieri, M.; Dellepiane, M.; Ponchio, F.; Potenziani, M. (2017). Delivering and using 3D models on the web: are we ready?. Virtual Archaeology Review. 8(17):1-9. https://doi.org/10.4995/var.2017.6405SWORD1981

Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis

Collaborative tagging is a simple and effective method for organizing and sharing web resources using human created metadata. It has arisen out of the need for an efficient method of personal organization, as the number of digital resources in everyday lives increases. While tagging has become a proven organization scheme through its popularity and widespread use on the Web, little is known about its implications and how it may effectively be applied in different situations. This is due to the fact that tagging has evolved through several iterations of use on social software websites, rather than through a scientific or an engineering design process. The research presented in this thesis, through investigations in the domain of e-learning, seeks to understand more about the scientific nature of collaborative tagging through a number of human subject studies. While broad in scope, touching on issues in human computer interaction, knowledge representation, Web system architecture, e-learning, metadata, and information visualization, this thesis focuses on how collaborative tagging can supplement the growing metadata requirements of e-learning. I conclude by looking at how the findings may be used in future research, through using information based in the emergent social networks of social software, to automatically adapt to the needs of individual users

Casual Information Visualization on Exploring Spatiotemporal Data

The goal of this thesis is to study how the diverse data on the Web which are familiar to everyone can be visualized, and with a special consideration on their spatial and temporal information. We introduce novel approaches and visualization techniques dealing with different types of data contents: interactively browsing large amount of tags linking with geospace and time, navigating and locating spatiotemporal photos or videos in collections, and especially, providing visual supports for the exploration of diverse Web contents on arbitrary webpages in terms of augmented Web browsing

Deep Learning of Semantic Image Labels on HDR Imagery in a Maritime Environment

Situational awareness in the maritime environment can be extremely challenging. The maritime environment is highly dynamic and largely undefined, requiring the perception of many potential hazards in the shared maritime environment. One particular challenge is the effect of direct-sunlight exposure and specular reflection causing degradation of camera reliability. It is for this reason then, in this work, the use of High-Dynamic Range imagery for deep learning of semantic image labels is studied in a littoral environment. This study theorizes that the use HDR imagery may be extremely beneficial for the purpose of situational awareness in maritime environments due to the inherent advantages of the technology. This study creates labels for a multi-class semantic segmentation process, and performs well on water and horizon identification in the littoral zone. Additionally, this work contributes proof that water can be reasonably identified using HDR imagery with semantic networks, which is useful for determining the navigable regions for a vessel. This result is a basis on which to build further semantic segmentation work upon in this environment, and could be further improved upon in future works with the introduction of additional data for multi-class segmentation problems