Abstract
This paper presents the participation of FEUP, from University of Porto, in the TREC 2008 Blog Track. FEUP participated in two tasks, the baseline adhoc retrieval task and the blog finding distillation task. Our approach was focused on the use of the temporal information available in the TREC Blog06 collection. For the baseline adhoc retrieval task a simple temporal sort was evaluated. In the blog finding distillation task we tested three alternative scoring functions based on temporal evidence. All features were combined with a BM25 baseline run using a standard rank aggregation approach. We observed small, but statistically significant, improvements in several evaluation measures when temporal information is used.

Abstract
This paper describes the participation of FEUP, from the University of Porto, in the TREC 2009 Blog Track. FEUP participated in the faceted blog distillation task with work focused on the use of temporal features available in the new TREC Blogs08 collection. The approach presented in this paper uses the temporal information available in most individual posts to amplify (or reduce) each post's score. Blog scores, and subsequent ranks, are obtained by combining individual posts' scores. While preparing the runs, no endeavors were made to identify a priori any temporal differences between the three distinct facets.

Abstract
The importance of the spatial component of data items has been long recognized and gave rise to a successful line of research and development in Geographic Information Systems (GIS). In many application domains it is also essential to deal with the evolution of data along time and to integrate spatial, temporal and other aspects of the information domain in an expressive and operationally effective manner. Until recently, temporal solutions provided by spatial database systems were semi-temporal approaches lacking full temporal support. As a consequence, most spatial database systems manage snapshots of the present state of facts without fully exploiting historical temporal aspects. This paper provides preliminary results on a spatiotemporal database implementation. The proposed system builds on existing database technologies, TimeDB and Oracle Spatial, for temporal and spatial support, respectively. The justification for the choice of these technologies is given, based on the state of the art in spatial and temporal database research. The integration of the spatial and temporal components is achieved with the extension of the TimeDB implementation layer. A set of goals has been established in order to cover both the integration of the spatial support and the enforcement of the temporal requirements in the extended system. Issues and solutions are presented and illustrative examples show the use of the implemented functionalities.

Abstract
Spatiotemporal databases provide effective means to represent, manage and query information evolving over time. However, the visualization of record sets that result from spatiotemporal queries through traditional visualization techniques can be of difficult interpretation or may lack the ability to meaningfully display several instants at the same time. We propose a Temporal Focus + Context visualization model to overcome issues from such techniques resorting to concepts from Information Visualization. In this model, Focus + Context is applied to time rather than, as more typically, to attributes or space, and allows large amounts of data from distinct periods of time and from several record sets to be compressed onto one. Underlying the proposed visualization technique is the calculation of a temporal degree of interest (TDOI) for each record driven by specific analysis, exploration or presentation goals and based on the record valid time attribute, as well as on user-defined temporal visualization requirements. In the mapping stage of the visualization pipeline, the TDOI for a record is used to control graphical properties, such as transparency and color. More complex rendering properties, such as sketch drawing edges or other non-photorealistic enhancement techniques, can also be used to convey the temporal aspects of data, replacing the original graphical features of the record data. By enhancing or dimming the representation of a data item, according to the corresponding degree of interest, it is possible to meaningfully compress information about distinct temporal states of data onto the same visualization display. The model has been applied to several test scenarios and proved appropriate and useful for a wide range of domains that require the display, exploration and analysis of spatial information discretely evolving over time. Information Visualization (2008) 7, 265-274. doi: 10.1057/palgrave.ivs.9500188

Abstract

Abstract
To address metadata with researchers it is important to use models that include familiar domain concepts. In the Social Sciences, the DDI is a well-accepted source of such domain concepts. To create FAIR data and metadata, we need to establish a compact set of DDI elements that fit the requirements in projects and are likely to be adopted by researchers inexperienced with metadata creation. Over time, we have engaged in interviews and data description sessions with research groups in the Social Sciences, identifying a manageable DDI subset. A recent Clinical Psychology project, TOGETHER, dealing with risk assessment for hereditary cancer, considered the inclusion of a DDI subset for the production of metadata that are timely and interoperable with data publication initiatives in the same domain. Taking a DDI subset identified by the data curators, we make a preliminary assessment of its use as a realistic effort on the part of researchers, taking into consideration the metadata created in two data description sessions, the effort involved, and overall metadata quality. A follow-up questionnaire was used to assess the perspectives of researchers regarding data description.