Guidelines for Linked Data generation and publication: an example in building energy consumption

Linked Data is the key paradigm of the Semantic Web, a new generation of the World Wide Web that promises to bring meaning (semantics) to data. A large number of both public and private organizations have published their data following the Linked Data principles, or have done so with data from other organizations. To this extent, since the generation and publication of Linked Data are intensive engineering processes that require high attention in order to achieve high quality, and since experience has shown that existing general guidelines are not always sufficient to be applied to every domain, this paper presents a set of guidelines for generating and publishing Linked Data in the context of energy consumption in buildings (one aspect of Building Information Models). These guidelines offer a comprehensive description of the tasks to perform, including a list of steps, tools that help in achieving the task, various alternatives for performing the task, and best practices and recommendations. Furthermore, this paper presents a complete example on the generation and publication of Linked Data about energy consumption in buildings, following the presented guidelines, in which the energy consumption data of council sites (e.g., buildings and lights) belonging to the Leeds City Council jurisdiction have been generated and published as Linked Data.

Singular value decomposition for genome-wide expression data processing and modeling

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

Data assimilation and its applications

In data assimilation, one prepares the grid data as the best possible estimate of the true initial state of a considered system by merging various measurements irregularly distributed in space and time, with a prior knowledge of the state given by a numerical model. Because it may improve forecasting or modeling and increase physical understanding of considered systems, data assimilation now plays a very important role in studies of atmospheric and oceanic problems. Here, three examples are presented to illustrate the use of new types of observations and the ability of improving forecasting or modeling.

Integrating the development of data mining and data warehouses via model-driven engineering

Data mining is one of the most important analysis techniques to automatically extract knowledge from large amount of data. Nowadays, data mining is based on low-level specifications of the employed techniques typically bounded to a specific analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Bearing in mind this situation, we propose a model-driven approach which is based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (that is deployed via data-warehousing technology) and the analysis models for data mining (tailored to a specific platform). Thus, analysts can concentrate on understanding the analysis problem via conceptual data-mining models instead of wasting efforts on low-level programming tasks related to the underlying-platform technical details. These time consuming tasks are now entrusted to the model-transformations scaffolding. The feasibility of our approach is shown by means of a hypothetical data-mining scenario where a time series analysis is required.

Advanced interpretation of subsidence in Murcia (SE Spain) using A-DInSAR data – modelling and validation

Subsidence is a natural hazard that affects wide areas in the world causing important economic costs annually. This phenomenon has occurred in the metropolitan area of Murcia City (SE Spain) as a result of groundwater overexploitation. In this work aquifer system subsidence is investigated using an advanced differential SAR interferometry remote sensing technique (A-DInSAR) called Stable Point Network (SPN). The SPN derived displacement results, mainly the velocity displacement maps and the time series of the displacement, reveal that in the period 2004–2008 the rate of subsidence in Murcia metropolitan area doubled with respect to the previous period from 1995 to 2005. The acceleration of the deformation phenomenon is explained by the drought period started in 2006. The comparison of the temporal evolution of the displacements measured with the extensometers and the SPN technique shows an average absolute error of 3.9±3.8 mm. Finally, results from a finite element model developed to simulate the recorded time history subsidence from known water table height changes compares well with the SPN displacement time series estimations. This result demonstrates the potential of A-DInSAR techniques to validate subsidence prediction models as an alternative to using instrumental ground based techniques for validation.

Data normalization and integration in robotic systems using web services technologies

The robotics is one of the most active areas. We also need to join a large number of disciplines to create robots. With these premises, one problem is the management of information from multiple heterogeneous sources. Each component, hardware or software, produces data with different nature: temporal frequencies, processing needs, size, type, etc. Nowadays, technologies and software engineering paradigms such as service-oriented architectures are applied to solve this problem in other areas. This paper proposes the use of these technologies to implement a robotic control system based on services. This type of system will allow integration and collaborative work of different elements that make up a robotic system.

Online Personal Data Processing and EU Data Protection Reform. CEPS Task Force Report, April 2013

This report sheds light on the fundamental questions and underlying tensions between current policy objectives, compliance strategies and global trends in online personal data processing, assessing the existing and future framework in terms of effective regulation and public policy. Based on the discussions among the members of the CEPS Digital Forum and independent research carried out by the rapporteurs, policy conclusions are derived with the aim of making EU data protection policy more fit for purpose in today’s online technological context. This report constructively engages with the EU data protection framework, but does not provide a textual analysis of the EU data protection reform proposal as such.

Global compilation of chlorophyll fluorescence profiles from several data bases, and from published and unpublished individual sources

The present data set includes 268,127 vertical in situ fluorescence profiles obtained from several available online databases and from published and unpublished individual sources. Metadata about each profiles are given in the file provided here in further details. The majority of profiles comes from the National Oceanographic Data Center (NODC) and the fluorescence profiles acquired by Bio-Argo floats available on the Oceanographic Autonomous Observations (OAO) platform (63.7% and 12.5% respectively). Different modes of acquisition were used to collect the data presented in this study: (1) CTD profiles are acquired using a fluorometer mounted on a CTD-rosette; (2) OSD (Ocean Station Data) profiles are derived from water samples and are defined as low resolution profiles; (3) the UOR (Undulating Oceanographic Recorder) profiles are acquired by a equipped with a fluorometer and towed by a research vessel; (4) PA profiles are acquired by autonomous platforms (here profiling floats or elephant seals equipped with a fluorometer). Data acquired from gliders are not included in the compilation.

Stable oxygen isotope and Mg/Ca data of Globigerinoides ruber white, water stable oxygen isotope data, SST and MAT records of sediment core GeoB6211-2

During Termination 1, millennial-scale weakening events of the Atlantic meridional overturning circulation (AMOC) supposedly produced major changes in sea surface temperatures (SSTs) of the western South Atlantic, and in mean air temperatures (MATs) over southeastern South America. It has been suggested, for instance, that the Brazil Current (BC) would strengthen (weaken) and the North Brazil Current (NBC) would weaken (strengthen) during slowdown (speed-up) events of the AMOC. This anti-phase pattern was claimed to be a necessary response to the decreased North Atlantic heat piracy during periods of weak AMOC. However, the thermal evolution of the western South Atlantic and the adjacent continent is so far largely unknown. Here we address this issue, presenting high-temporal-resolution SST and MAT records from the BC and southeastern South America, respectively. We identify a warming in the western South Atlantic during Heinrich Stadial 1 (HS1), which is followed first by a drop and then by increasing temperatures during the Bølling-Allerød, in phase with an existing SST record from the NBC. Additionally, a similar SST evolution is shown by a southernmost eastern South Atlantic record, suggesting a South Atlantic-wide pattern in SST evolution during most of Termination 1. Over southeastern South America, our MAT record shows a two-step increase during Termination 1, synchronous with atmospheric CO2 rise (i.e., during the second half of HS1 and during the Younger Dryas), and lagging abrupt SST changes by several thousand years. This delay corroborates the notion that the long duration of HS1 was fundamental in driving the Earth out of the last glacial.

Surface sediment data, CaCO3 and TOC

Modern sedimentary total organic carbon (TOC) content as a proxy for surface water export production was mapped on the shelf and on the upper continental slope of the Benguela upwelling system using 137 core tops. Shelf maxima in TOC can be correlated with maxima in surface water productivity. On the slope, high TOC contents are observed offshore from sites of strong modern upwelling. Estimates of modern TOC mass accumulation rates (MAR) show that approximately 85% of the total is accumulating on the shelf. TOC MAR were calculated, mapped, and budgeted for the Holocene and for the Last Glacial Maximum (LGM) using 19 sediment cores from the continental slope. During the LGM, centers of deposition and production have migrated offshore with respect to their Holocene positions. TOC accumulation on the continental slope was approximately 84% higher during the LGM than during the Holocene, possibly reflecting enhanced productivity. The TOC distribution patterns and sediment echo sounding data suggest that undercurrents strongly influence the sedimentation off Namibia. Winnowing and focusing result in great lateral heterogeneity of sedimentation rates and sediment properties. Individual cores therefore do not necessarily reflect general changes in export production. These results highlight the need for detailed regional studies based on a large number of sediment cores for highly heterogeneous high-productivity areas in order to derive general statements on total fluxes.