Incorporation of ontologies in data warehouse/business intelligence systems - A systematic literature review

Semantic Web (SW) techniques, such as ontologies, are used in Information Systems (IS) to cope with the growing need for sharing and reusing data and knowledge in various research areas. Despite the increasing emphasis on unstructured data analysis in IS, structured data and its analysis remain critical for organizational performance management. This systematic literature review aims at analyzing the incorporation and impact of ontologies in Data Warehouse/Business Intelligence (DW/BI) systems, contributing to the current literature by providing a classification of works based on the field of each case study, SW techniques used, and the authors’ motivations for using them, with a focus on DW/BI design, development and exploration tasks. A search strategy was developed, including the definition of keywords, inclusion and exclusion criteria, and the selection of search engines. Ontologies are mainly defined using the Ontology Web Language standard to support multiple DW/BI tasks, such as Dimensional Modeling, Requirement Analysis, Extract-Transform-Load, and BI Application Design. Reviewed authors present a variety of motivations for ontology-driven solutions in DW/BI, such as eliminating or solving data heterogeneity/semantics problems, increasing interoperability, facilitating integration, or providing semantic content for requirements and data analysis. Further, implications for practice and research agenda are indicated.info:eu-repo/semantics/publishedVersio

Adding value to sensor data of civil engineering structures: automatic outlier detection

This paper discusses the problem of outlier detection in datasets generated by sensors installed in large civil engineering structures. Since outlier detection can be implemented after the acquisition process, it is fully independent of particular acquisition processes as well as it scales to new or updated sensors. It shows a method of using machine learning techniques to implement an automatic outlier detection procedure, demonstrating and evaluating the results in a real environment, following the Design Science Research Methodology. The proposed approach makes use of Manual Acquisition System measurements and combine them with a clustering algorithm (DBSCAN) and baseline methods (Multiple Linear Regression and thresholds based on standard deviation) to create a method that is able to identify and remove most of the outliers in the datasets used for demonstration and evaluation. This automatic procedure improves data quality having a direct impact on the decision processes with regard to structural safety.info:eu-repo/semantics/acceptedVersio

Learning scorecard dashboards: visualizing student learning experience

This paper presents the design of dashboards for the Learning Scorecard, a platform designed for improving the student experience in a Higher Education course using gamification and Business Intelligence (BI) techniques. LS is a Learning Analytics application, that has been used in Data Warehouse and BI courses in a University setting since 2016. The LS platform has two independent views: student view and faculty (or course coordinator) view. In the LS faculty view, dashboards were designed according to the best practices of information visualization for decision support, whereas in the student view the visualization of the learning experience is immersed in gamification elements. This paper focuses only on student dashboards, which are driven by engagement and motivation of students to improve their collaboration and learning experience. A central design decision for the LS implementation, was the recognition that the way students want to track their progress and their learning experience in a course is fundamentally different that the way teachers need to monitor student progress. The presented learning dashboards use gamification mechanisms to enable the visualization of self-assessment results giving a clear indication of the learning progress of students in a course.info:eu-repo/semantics/acceptedVersio

Learning Scorecard dashboards: visualizing student learning experience

This paper presents the design of dashboards for the Learning Scorecard, a platform designed for improving the student experience in a Higher Education course using gamification and Business Intelligence (BI) techniques. LS is a Learning Analytics application, that has been used in Data Warehouse and BI courses in a University setting since 2016. The LS platform has two independent views: student view and faculty (or course coordinator) view. In the LS faculty view, dashboards were designed according to the best practices of information visualization for decision support, whereas in the student view the visualization of the learning experience is immersed in gamification elements. This paper focuses only on student dashboards, which are driven by engagement and motivation of students to improve their collaboration and learning experience. A central design decision for the LS implementation, was the recognition that the way students want to track their progress and their learning experience in a course is fundamentally different that the way teachers need to monitor student progress. The presented learning dashboards use gamification mechanisms to enable the visualization of self-assessment results giving a clear indication of the learning progress of students in a course.info:eu-repo/semantics/acceptedVersio

Lepidópteros tortricídeos em pomares de pomóideas e de prunóideas da Beira Interior

Comunicação apresentada no 6.º Encontro Nacional de Protecção Integrada que decorreu em Castelo Branco, na Escola Superior Agrária do Instituto Poliécnico de Castelo Branco, de 14 a 16 de Maio de 2003, no âmbito do painel sobre Prunóideas.Neste trabalho são apresentados resultados de uma prospecção relativa às espécies de tortricídeos fitófagos de pomares de pomóideas e de prunóideas, na Beira Interior. O trabalho reporta-se a dados obtidos no ano de 2002, tendo sido utilizadas armadilhas sexuais para as capturas de adultos e observação visual para a detecção de larvas. As espécies monitorizadas foram: Adoxophyes orana, Cacoecimorpha pronubana, Pandemis heparana, Pandemis ribeana (=cerasana) e Cydia molesta. Das cinco espécies monitorizadas apenas houve capturas de Cacoecimorpha pronubana e de Pandemis heparana. Relativamente a estas duas espécies são apresentadas curvas de voo. Embora tenham sido detectados frutos com a sintomatologia característica do ataque destas espécies, não foram encontradas larvas, sugerindo populações economicamente insignificantes no ano de 2002

Gamificação do learning scorecard: aplicação da framework MDA

A aplicação de técnicas de gamificação no ensino superior é um desafio; em diferentes momentos facilmente se perde o foco e deixamos de conseguir explicar as ligações entre as motivações dos jogadores e os elementos que constituem o jogo. Este estudo focou-se na aplicação da framework MDA (Mechanics, Dynamics and Aesthetics) numa plataforma designada de Learning Scorecard (LS), utilizada por dezenas de alunos no ISCTE - Instituto Universitário de Lisboa. O LS é uma plataforma de Learning Analytics, que tem sido usada em Unidades Curriculares de Data Warehouse e Business Intelligence desde 2016. O LS possui duas visões independentes: a vista de aluno e a vista de docente. Neste trabalho apenas reportamos a aplicação dos diferentes passos da framework MDA no LS na vista de aluno. Esta vista procura melhorar a experiência de aprendizagem dos alunos conseguindo melhorar o seu compromisso e motivação através do uso da gamificação.info:eu-repo/semantics/publishedVersio

Lepidópteros tortricídeos em pomares de pomóideas e prunóideas da Beira Interior

A survey for lepidoptera tortricid feeding on pome and stone fruit orchards was carried out, in 2002, in Beira Interior, Portugal. Adults were captured using sexual pheromones traps and visual observation techniques were used in larvae detection. The species monitorised were: Adoxophyes orana, Cacoecimorpha pronubana, Pandemis heparana, Pandemis ribeana(=cerasana), and Cydia molesta. Among the five species monitorised only Cacoecimorpha pronubana and Pandemis heparana were captured. Flight curves of these two species are shown in this paper. Although there were detected fruits and leaves with characteristic symptoms of attack of these species, larvae were not found, suggesting populations not economically significant

S100B as a potential biomarker and therapeutic target in multiple sclerosis

Multiple sclerosis (MS) pathology is characterized by neuroinflammation and demyelination. Recently, the inflammatory molecule S100B was identified in cerebrospinal fluid (CSF) and serum of MS patients. Although seen as an astrogliosis marker, lower/physiological levels of S100B are involved in oligodendrocyte differentiation/maturation. Nevertheless, increased S100B levels released upon injury may induce glial reactivity and oligodendrocyte demise, exacerbating tissue damage during an MS episode or delaying the following remyelination. Here, we aimed to unravel the functional role of S100B in the pathogenesis of MS. Elevated S100B levels were detected in the CSF of relapsing-remitting MS patients at diagnosis. Active demyelinating MS lesions showed increased expression of S100B and its receptor, the receptor for advanced glycation end products (RAGE), in the lesion area, while chronic active lesions displayed increased S100B in demyelinated areas with lower expression of RAGE in the rim. Interestingly, reactive astrocytes were identified as the predominant cellular source of S100B, whereas RAGE was expressed by activated microglia/macrophages. Using an ex vivo demyelinating model, cerebral organotypic slice cultures treated with lysophosphatidylcholine (LPC), we observed a marked elevation of S100B upon demyelination, which co-localized mostly with astrocytes. Inhibition of S100B action using a directed antibody reduced LPC-induced demyelination, prevented astrocyte reactivity and abrogated the expression of inflammatory and inflammasome-related molecules. Overall, high S100B expression in MS patient samples suggests its usefulness as a diagnostic biomarker for MS, while the beneficial outcome of its inhibition in our demyelinating model indicates S100B as an emerging therapeutic target in MS.This work was supported by Medal of Honor L’Oréal for Women in Science (FCT, UNESCO, L’Óreal) and innovation grant (Ordem dos Farmacêuticos) to AF, a post-doctoral grant from Fundação para a Ciência e Tecnologia (FCT-SFRH/BPD/96794/2013) and a DuPré Grant from the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) to AB, and by FCT-Pest- OE/SAU/UI4013 to iMed.ULisboa.info:eu-repo/semantics/publishedVersio