What is the current state of the Multilingual Web of Data?

The Semantic Web is growing at a fast pace, recently boosted by the creation of the Linked Data initiative and principles. Methods, standards, techniques and the state of technology are becoming more mature and therefore are easing the task of publication and consumption of semantic information on the Web.

Transforming meteorological data into linked data

This paper describes the process followed in order to make some of the public meterological data from the Agencia Estatal de Meteorología (AEMET, Spanish Meteorological Office) available as Linked Data. The method followed has been already used to publish geographical, statistical, and leisure data. The data selected for publication are generated every ten minutes by the 250 automatic stations that belong to AEMET and that are deployed across Spain. These data are available as spreadsheets in the AEMET data catalog, and contain more than twenty types of measurements per station. Spreadsheets are retrieved from the website, processed with Python scripts, transformed to RDF according to an ontology network about meteorology that reuses the W3C SSN Ontology, published in a triple store and visualized in maps with Map4rdf.

Short paper: From streaming data to linked data. A case study with bike sharing systems

Current methods and tools that support Linked Data publication have mainly focused so far on static data, without considering the growing amount of streaming data available on the Web. In this paper we describe a case study that involves the publication of static and streaming Linked Data for bike sharing systems and related entities. We describe some of the challenges that we have faced, the solutions that we have explored, the lessons that we have learned, and the opportunities that lie in the future for exploiting Linked Stream Data.

Guidelines for multilingual linked data

In this article, we argue that there is a growing number of linked datasets in different natural languages, and that there is a need for guidelines and mechanisms to ensure the quality and organic growth of this emerging multilingual data network. However, we have little knowledge regarding the actual state of this data network, its current practices, and the open challenges that it poses. Questions regarding the distribution of natural languages, the links that are established across data in different languages, or how linguistic features are represented, remain mostly unanswered. Addressing these and other language-related issues can help to identify existing problems, propose new mechanisms and guidelines or adapt the ones in use for publishing linked data including language-related features, and, ultimately, provide metrics to evaluate quality aspects. In this article we review, discuss, and extend current guidelines for publishing linked data by focusing on those methods, techniques and tools that can help RDF publishers to cope with language barriers. Whenever possible, we will illustrate and discuss each of these guidelines, methods, and tools on the basis of practical examples that we have encountered in the publication of the datos.bne.es dataset.

3LD: towards high quality, industry-ready linguistic Linked Licensed Data

The application of Linked Data technology to the publication of linguistic data promises to facilitate interoperability of these data and has lead to the emergence of the so called Linguistic Linked Data Cloud (LLD) in which linguistic data is published following the Linked Data principles. Three essential issues need to be addressed for such data to be easily exploitable by language technologies: i) appropriate machine-readable licensing information is needed for each dataset, ii) minimum quality standards for Linguistic Linked Data need to be defined, and iii) appropriate vocabularies for publishing Linguistic Linked Data resources are needed. We propose the notion of Licensed Linguistic Linked Data (3LD) in which different licensing models might co-exist, from totally open to more restrictive licenses through to completely closed datasets.

Linked Data Rights 2.0: extension of ODRL for Licensing Linked Data

Linked Data assets (RDF triples, graphs, datasets, mappings...) can be object of protection by the intellectual property law, the database law or its access or publication be restricted by other legal reasons (personal data pro- tection, security reasons, etc.). Publishing a rights expression along with the digital asset, allows the rightsholder waiving some or all of the IP and database rights (leaving the work in the public domain), permitting some operations if certain conditions are satisfied (like giving attribution to the author) or simply reminding the audience that some rights are reserved.

Use of phosphorous mapping and sea-level change data in assessing coastal activity zones and establishing site chronology : A case study from the Icelandic multi-period site of Vatnsfjörður

This paper forms part of Lukasz Mikolajczyk's PhD dissertation, which is supervised by Karen Milek

Vertical crustal motion along the Mediterranean and Black Sea coast derived from ocean altimetry and tide gauge data

Tide gauge (TG) data along the northern Mediterranean and Black Sea coasts are compared to the sea-surface height (SSH) anomaly obtained from ocean altimetry (TOPEX/Poseidon and ERS-1/2) for a period of nine years (1993–2001). The TG measures the SSH relative to the ground whereas the altimetry does so with respect to the geocentric reference frame; therefore their difference would be in principle a vertical ground motion of the TG sites, though there are different error sources for this estimate as is discussed in the paper. In this study we estimate such vertical ground motion, for each TG site, from the slope of the SSH time series of the (non-seasonal) difference between the TG record and the altimetry measurement at a point closest to the TG. Where possible, these estimates are further compared with those derived from nearby continuous Global Positioning System (GPS) data series. These results on vertical ground motion along the Mediterranean and Black Sea coasts provide useful source data for studying, contrasting, and constraining tectonic models of the region. For example, in the eastern coast of the Adriatic Sea and in the western coast of Greece, a general subsidence is observed which may be related to the Adriatic lithosphere subducting beneath the Eurasian plate along the Dinarides fault.

New data on the Vrancea Nappe (Moldavidian Basin, Outer Carpathian Domain, Romania): paleogeographic and geodynamic reconstructions

A study has been performed on the Cretaceous to Early Miocene succession of the Vrancea Nappe (Outer Carpathians, Romania), based on field reconstruction of the stratigraphic record, mineralogical-petrographic and geochemical analyses. Extra-basinal clastic supply and intra-basinal autochthonous deposits have been differentiated, appearing laterally inter-fingered and/or interbedded. The main clastic petrofacies consist of calcarenites, sub-litharenites, quartzarenites, sub-arkoses, and polygenic conglomerates derived from extra-basinal margins. An alternate internal and external provenance of the different supplies is the result of the paleogeographic re-organization of the basin/margins system due to tectonic activation and exhumation of rising areas. The intra-basinal deposits consist of black shales and siliceous sediments (silexites and cherty beds), evidencing major environmental changes in the Moldavidian Basin. Organic-matter-rich black shales were deposited during anoxic episodes related to sediment starvation and high nutrient influx due to paleogeographic isolation of the basin caused by plate drifting. The black shales display relatively high contents in sub-mature to mature, Type II lipidic organic matter (good oil and gas-prone source rocks) constituting a potentially active petroleum system. The intra-basinal siliceous sediments are related to oxic pelagic or hemipelagic environments under tectonic quiescence conditions although its increase in the Oligocene part of the succession can be correlated with volcanic supplies. The integration of all the data in the “progressive reorientation of convergence direction” Carpathian model, and their consideration in the framework of a foreland basin, led to propose some constrains on the paleogeographic-geodynamic evolutionary model of the Moldavidian Basin from the Late Cretaceous to the Burdigalian.

A robust and fast method for 6DoF motion estimation from generalized 3D data

Nowadays, there is an increasing number of robotic applications that need to act in real three-dimensional (3D) scenarios. In this paper we present a new mobile robotics orientated 3D registration method that improves previous Iterative Closest Points based solutions both in speed and accuracy. As an initial step, we perform a low cost computational method to obtain descriptions for 3D scenes planar surfaces. Then, from these descriptions we apply a force system in order to compute accurately and efficiently a six degrees of freedom egomotion. We describe the basis of our approach and demonstrate its validity with several experiments using different kinds of 3D sensors and different 3D real environments.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

On the decorrelation filtering of RL05 GRACE data for global applications

In autumn 2012, the new release 05 (RL05) of monthly geopotencial spherical harmonics Stokes coefficients (SC) from GRACE (Gravity Recovery and Climate Experiment) mission was published. This release reduces the noise in high degree and order SC, but they still need to be filtered. One of the most common filtering processing is the combination of decorrelation and Gaussian filters. Both of them are parameters dependent and must be tuned by the users. Previous studies have analyzed the parameters choice for the RL05 GRACE data for oceanic applications, and for RL04 data for global application. This study updates the latter for RL05 data extending the statistics analysis. The choice of the parameters of the decorrelation filter has been optimized to: (1) balance the noise reduction and the geophysical signal attenuation produced by the filtering process; (2) minimize the differences between GRACE and model-based data; (3) maximize the ratio of variability between continents and oceans. The Gaussian filter has been optimized following the latter criteria. Besides, an anisotropic filter, the fan filter, has been analyzed as an alternative to the Gauss filter, producing better statistics.

The Use of the Relative Interior in Integration with Nonconvex Data

Introducing an appropriate inclusion between approximate minima associated with two nonconvex functions, we derive explicit relations between the closed convex hulls of these functions. The formula we obtain goes beyond the so-called epi-pointed property of functions which is usually concerned with such a topic.

When and how to support renewables? Letting the data speak. Bruegel Working Paper 2014/01, February 2014

Low-carbon energy technologies are pivotal for decarbonising our economies up to 2050 while ensuring secure and affordable energy. Consequently, innovation that reduces the cost of low-carbon energy would play an important role in reducing transition costs. We assess the two most prominent innovation policy instruments (i) public research, development and demonstration (RD&D) subsidies and (ii) public deployment policies. Our results indicate that both deployment and RD&D coincide with increasing knowledge generation and the improved competitiveness of renewable energy technologies. We find that both support schemes together have a greater effect that they would individually, that RD&D support is unsurprisingly more effective in driving patents and that timing matters. Current wind deployment based on past wind RD&D spending coincides best with wind patenting. If we look into competitiveness we find a similar picture, with the greatest effect coming from deployment. Finally, we find significant cross-border effects, especially for winddeployment. Increased deployment in one country coincides with increased patenting in nearby countries. Based on our findings we argue that both deployment and RD&D support are needed to create innovation in renewable energy technologies. However, we worry that current support is unbalanced. Public spending on deployment has been two orders of magnitude larger (in 2010 about €48 billion in the five largest EU countries in 2010) than spending on RD&D support (about €315 million). Consequently, basing the policy mix more on empirical evidence could increase the efficiency of innovation policy targeted towards renewable energy technologies.

Mapping competitiveness with European data. Bruegel Blueprint 23, 6 March 2015

Europe needs improved competitiveness to escape the current economic malaise, so it might seem surprising that there is no common European definition of competitiveness, and no consensus on how to consistently measure it. To help address this situation, this Blueprint provides an inventory and an assessment of the data related to the measurement of competitiveness in Europe. It is intended as a handbook for researchers interested in measuring competiveness, and for policymakers interested in new and better measures of competitiveness. MAPCOMPETE has been designed to provide an assessment of data opportunities and requirements for the comparative analysis of competitiveness in European countries at the macro and the micro level.