Open business intelligence: on the importance of data quality awareness in user-friendly data mining

Citizens demand more and more data for making decisions in their daily life. Therefore, mechanisms that allow citizens to understand and analyze linked open data (LOD) in a user-friendly manner are highly required. To this aim, the concept of Open Business Intelligence (OpenBI) is introduced in this position paper. OpenBI facilitates non-expert users to (i) analyze and visualize LOD, thus generating actionable information by means of reporting, OLAP analysis, dashboards or data mining; and to (ii) share the new acquired information as LOD to be reused by anyone. One of the most challenging issues of OpenBI is related to data mining, since non-experts (as citizens) need guidance during preprocessing and application of mining algorithms due to the complexity of the mining process and the low quality of the data sources. This is even worst when dealing with LOD, not only because of the different kind of links among data, but also because of its high dimensionality. As a consequence, in this position paper we advocate that data mining for OpenBI requires data quality-aware mechanisms for guiding non-expert users in obtaining and sharing the most reliable knowledge from the available LOD.

Direct Nucleophilic Substitution of Free Allylic Alcohols in Water Catalyzed by FeCl3⋅6 H2O: Which is the Real Catalyst?

The allylic substitution reaction, and particularly the direct allylic amination reaction, of free allylic alcohols in water catalyzed by FeCl3⋅6 H2O is described. This novel environmentally-friendly methodology allows the use of a wide variety of nitrogenated nucleophiles such as sulfonamides, carbamates, benzamides, anilines, benzotriazoles, and azides, generally giving good yields of the corresponding substitution products. The synthetic applicability of the process is also demonstrated because the reaction can be performed on gram-scale. Additionally, carbon nucleophiles such as silylated nucleophiles, aromatic compounds, and malonates also proved to be suitable for this transformation. Finally, the nature of the catalytic species present in aqueous media is unveiled, pointing towards the formation of hexaaquo iron(III) complexes.

Microwave-assisted palladium-catalyzed highly regio- and stereoselective head to head dimerization of terminal aryl alkynes in water

A highly regio- and stereoselective oxime palladacycle/imidazolinium-catalyzed head to head dimerization of terminal aryl alkynes in water is presented. The reaction, which is carried out at 130 °C under microwave irradiation in the presence of 1,3-bis-(2,6-diisopropylphenyl)imidazolinium chloride as ligand, triethylamine as base, and TBAB as surfactant, allows the synthesis of (E)-1,4-enynes as single stereoisomers in good isolated yields.

A data driven study of relationships between relief and farmland abandonment in a Mediterranean region

The environmental, cultural and socio-economic causes and consequences of farmland abandonment are issues of increasing concern for researchers and policy makers. In previous studies, we proposed a new methodology for selecting the driving factors in farmland abandonment processes. Using Data Mining and GIS, it is possible to select those variables which are more significantly related to abandonment. The aim of this study is to investigate the application of the above mentioned methodology for finding relationships between relief and farmland abandonment in a Mediterranean region (SE Spain).We have taken into account up to 28 different variables in a single analysis, some of them commonly considered in land use change studies (slope, altitude, TWI, etc), but also other novel variables have been evaluated (sky view factor, terrain view factor, etc). The variable selection process provides results in line with the previous knowledge of the study area, describing some processes that are region specific (e.g. abandonment versus intensification of the agricultural activities). The European INSPIRE Directive (2007/2/EC) establishes that the digital elevation models for land surfaces should be available in all member countries, this means that the research described in this work can be extrapolated to any European country to determine whether these variables (slope, altitude, etc) are important in the process of abandonment.

Towards a model-driven engineering approach of data mining

Nowadays, data mining is based on low-level specications of the employed techniques typically bounded to a specic analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Here, we propose a model-driven approach 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 (via data-warehousing technology) and the analysis models for data mining (tailored to a specic platform). Thus, analysts can concentrate on the analysis problem via conceptual data-mining models instead of low-level programming tasks related to the underlying-platform technical details. These tasks are now entrusted to the model-transformations scaffolding.

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.

Regional subsidence modelling in Murcia city (SE Spain) using 1-D vertical finite element analysis and 2-D interpolation of ground surface displacements

Subsidence is a hazard that may have natural or anthropogenic origin causing important economic losses. The area of Murcia city (SE Spain) has been affected by subsidence due to groundwater overexploitation since the year 1992. The main observed historical piezometric level declines occurred in the periods 1982–1984, 1992–1995 and 2004–2008 and showed a close correlation with the temporal evolution of ground displacements. Since 2008, the pressure recovery in the aquifer has led to an uplift of the ground surface that has been detected by the extensometers. In the present work an elastic hydro-mechanical finite element code has been used to compute the subsidence time series for 24 geotechnical boreholes, prescribing the measured groundwater table evolution. The achieved results have been compared with the displacements estimated through an advanced DInSAR technique and measured by the extensometers. These spatio-temporal comparisons have showed that, in spite of the limited geomechanical data available, the model has turned out to satisfactorily reproduce the subsidence phenomenon affecting Murcia City. The model will allow the prediction of future induced deformations and the consequences of any piezometric level variation in the study area.

A hydrological–economic model for sustainable groundwater use in sparse-data drylands: Application to the Amtoudi Oasis in southern Morocco, northern Sahara

A hydrological–economic model is introduced to describe the dynamics of groundwater-dependent economics (agriculture and tourism) for sustainable use in sparse-data drylands. The Amtoudi Oasis, a remote area in southern Morocco, in the northern Sahara attractive for tourism and with evidence of groundwater degradation, was chosen to show the model operation. Governing system variables were identified and put into action through System Dynamics (SD) modeling causal diagrams to program basic formulations into a model having two modules coupled by the nexus ‘pumping’: (1) the hydrological module represents the net groundwater balance (G) dynamics; and (2) the economic module reproduces the variation in the consumers of water, both the population and tourists. The model was operated under similar influx of tourists and different scenarios of water availability, such as the wet 2009–2010 and the average 2010–2011 hydrological years. The rise in international tourism is identified as the main driving force reducing emigration and introducing new social habits in the population, in particular concerning water consumption. Urban water allotment (PU) was doubled for less than a 100-inhabitant net increase in recent decades. The water allocation for agriculture (PI), the largest consumer of water, had remained constant for decades. Despite that the 2-year monitoring period is not long enough to draw long-term conclusions, groundwater imbalance was reflected by net aquifer recharge (R) less than PI + PU (G < 0) in the average year 2010–2011, with net lateral inflow from adjacent Cambrian formations being the largest recharge component. R is expected to be much less than PI + PU in recurrent dry spells. Some low-technology actions are tentatively proposed to mitigate groundwater degradation, such as: wastewater capture, treatment, and reuse for irrigation; storm-water harvesting for irrigation; and active maintenance of the irrigation system to improve its efficiency.

Synthesis of denim waste-based adsorbents and their application in water defluoridation

This study evaluates the application of denim fiber scraps as a precursor for the synthesis of adsorbents for water treatment via pyrolysis and their application in water defluoridation. The best pyrolysis conditions for the synthesis of this novel adsorbent have been identified and a metal doping route with different salts of Al3 +, La3 + and Fe3 + was proposed to improve its fluoride adsorption behavior. Different spectroscopic and microscopic techniques (i.e., FTIR, XPS, XRF, SEM) were used to characterize the precursor and adsorbents, and to analyze the surface interactions involved in the fluoride removal mechanism. Experimental results showed that these adsorbents were effective for fluoride adsorption showing uptakes up to 4.25 mg/g. The Si-O–metal–F interactions appear to be highly relevant for the fluoride removal. This study highlights the potential of denim textile waste as a raw material for the production of added-value products, thus minimizing their associated disposal cost. It also shows the performance of denim textile waste as a precursor of adsorbents for addressing relevant environmental concerns such as fluoride pollution.

Green synthesis of polypyrrole-supported metal catalysts: application to nitrate removal in water

Pt and Pt/Sn catalysts supported on polypyrrole (PPy) have been prepared using Ar plasma to reduce the metal precursors dispersed on the polymer. The PPy support was synthesized by chemical polymerization of pyrrole with FeCl3·6H2O, this leading to the conducting form of the polymer (conductimetric measurements). The Ar plasma treatment produced a partial reduction of platinum ions, anchored as platinum chloro-complexes to the PPy chain, into metallic platinum. A homogeneous distribution of Pt and Sn nanoparticles was observed by TEM. Activity of the PPy-supported catalysts was evaluated in the reduction of aqueous nitrate with H2 at room temperature. Nitrate concentration in water below the maximum acceptable level of 50 mg L−1 was achieved with all catalysts. However, considering not only efficiency in nitrate reduction, but also minimized concentrations of undesired nitrite and ammonium, the monometallic Pt catalyst seems to be the most promising one.