Finding the Needle in a Haystack: Who are the Most Central Authors Within a Domain?

The speed at which new scientific papers are published has increased dramatically, while the process of tracking the most recent publications having a high impact has become more and more cumbersome. In order to support learners and researchers in retrieving relevant articles and identifying the most central researchers within a domain, we propose a novel 2-mode multilayered graph derived from Cohesion Network Analysis (CNA). The resulting extended CNA graph integrates both authors and papers, as well as three principal link types: coauthorship, co-citation, and semantic similarity among the contents of the papers. Our rankings do not rely on the number of published documents, but on their global impact based on links between authors, citations, and semantic relatedness to similar articles. As a preliminary validation, we have built a network based on the 2013 LAK dataset in order to reveal the most central authors within the emerging Learning Analytics domain.

The RAGE Software Asset Model and Metadata Model

Software assets are key output of the RAGE project and they can be used by applied game developers to enhance the pedagogical and educational value of their games. These software assets cover a broad spectrum of functionalities – from player analytics including emotion detection to intelligent adaptation and social gamification. In order to facilitate integration and interoperability, all of these assets adhere to a common model, which describes their properties through a set of metadata. In this paper the RAGE asset model and asset metadata model is presented, capturing the detail of assets and their potential usage within three distinct dimensions – technological, gaming and pedagogical. The paper highlights key issues and challenges in constructing the RAGE asset and asset metadata model and details the process and design of a flexible metadata editor that facilitates both adaptation and improvement of the asset metadata model.

Software Components for Serious Game Development

The large upfront investments required for game development pose a severe barrier for the wider uptake of serious games in education and training. Also, there is a lack of well-established methods and tools that support game developers at preserving and enhancing the games’ pedagogical effectiveness. The RAGE project, which is a Horizon 2020 funded research project on serious games, addresses these issues by making available reusable software components that aim to support the pedagogical qualities of serious games. In order to easily deploy and integrate these game components in a multitude of game engines, platforms and programming languages, RAGE has developed and validated a hybrid component-based software architecture that preserves component portability and interoperability. While a first set of software components is being developed, this paper presents selected examples to explain the overall system’s concept and its practical benefits. First, the Emotion Detection component uses the learners’ webcams for capturing their emotional states from facial expressions. Second, the Performance Statistics component is an add-on for learning analytics data processing, which allows instructors to track and inspect learners’ progress without bothering about the required statistics computations. Third, a set of language processing components accommodate the analysis of textual inputs of learners, facilitating comprehension assessment and prediction. Fourth, the Shared Data Storage component provides a technical solution for data storage - e.g. for player data or game world data - across multiple software components. The presented components are exemplary for the anticipated RAGE library, which will include up to forty reusable software components for serious gaming, addressing diverse pedagogical dimensions.

A Scalable General Purpose System for Large-Scale Graph Processing

Graph analytics is an important and computationally demanding class of data analytics. It is essential to balance scalability, ease-of-use and high performance in large scale graph analytics. As such, it is necessary to hide the complexity of parallelism, data distribution and memory locality behind an abstract interface. The aim of this work is to build a scalable graph analytics framework that does not demand significant parallel programming experience based on NUMA-awareness.
The realization of such a system faces two key problems:
(i)~how to develop a scale-free parallel programming framework that scales efficiently across NUMA domains; (ii)~how to efficiently apply graph partitioning in order to create separate and largely independent work items that can be distributed among threads.

Emergence and Innovation in Digital Learning: Foundations and Applications

Educational systems worldwide are facing an enormous shift as a result of sociocultural, political, economic, and technological changes. The technologies and practices that have developed over the last decade have been heralded as opportunities to transform both online and traditional education systems. While proponents of these new ideas often postulate that they have the potential to address the educational problems facing both students and institutions and that they could provide an opportunity to rethink the ways that education is organized and enacted, there is little evidence of emerging technologies and practices in use in online education. Because researchers and practitioners interested in these possibilities often reside in various disciplines and academic departments the sharing and dissemination of their work across often rigid boundaries is a formidable task. Contributors to Emergence and Innovation in Digital Learning include individuals who are shaping the future of online learning with their innovative applications and investigations on the impact of issues such as openness, analytics, MOOCs, and social media. Building on work first published in Emerging Technologies in Distance Education, the contributors to this collection harness the dispersed knowledge in online education to provide a one-stop locale for work on emergent approaches in the field. Their conclusions will influence the adoption and success of these approaches to education and will enable researchers and practitioners to conceptualize, critique, and enhance their understanding of the foundations and applications of new technologies.

Gestengestützte Schema- und Datenexploration

Der Zugang zu Datenbanken über die universelle Abfragesprache SQL stellt für Nicht-Spezialisten eine große Herausforderung dar. Als eine benutzerfreundliche Alternative wurden daher seit den 1970er-Jahren unterschiedliche visuelle Abfragesprachen (Visual Query Languages, kurz VQLs) für klassische PCs erforscht. Ziel der vorliegenden Arbeit ist es, eine generische VQL zu entwickeln und zu erproben, die eine gestenbasierte Exploration von Datenbanken auf Schema- und Instanzdatenebene für mobile Endgeräte, insbesondere Tablets, ermöglicht. Dafür werden verschiedene Darstellungsformen, Abfragestrategien und visuelle Hints für Fremdschlüsselbeziehungen untersucht, die den Benutzer bei der Navigation durch die Daten unterstützen. Im Rahmen einer Anforderungsanalyse erwies sich die Visualisierung der Daten und Beziehungen mittels einer platzsparenden geschachtelten NF2-Darstellung als besonders vorteilhaft. Zur Steuerung der Datenbankexploration wird eine geeignete Gestensprache, bestehend aus Stroke-, Multitouch- und Mid-Air-Gesten, vorgestellt. Das Gesamtkonzept aus Darstellung und Gestensteuerung wurde anhand des im Rahmen dieser Arbeit entwickelten GBXT-Prototyps auf seine reale Umsetzbarkeit hin, als plattformunabhängige Single-Page-Application für verschiedene mobile Endgeräte mittels JavaScript und HTML5/CSS3 untersucht.

Data Science Seminar: Generic Big Data Processing for Advancing Situation Awareness and Decision-Support

The generation of heterogeneous big data sources with ever increasing volumes, velocities and veracities over the he last few years has inspired the data science and research community to address the challenge of extracting knowledge form big data. Such a wealth of generated data across the board can be intelligently exploited to advance our knowledge about our environment, public health, critical infrastructure and security. In recent years we have developed generic approaches to process such big data at multiple levels for advancing decision-support. It specifically concerns data processing with semantic harmonisation, low level fusion, analytics, knowledge modelling with high level fusion and reasoning. Such approaches will be introduced and presented in context of the TRIDEC project results on critical oil and gas industry drilling operations and also the ongoing large eVacuate project on critical crowd behaviour detection in confined spaces.

Open Space – Estratégia e Concretização: o caso EDP Porto

Este estudo centra-se numa investigação sobre o conceito de trabalho em open space na nova sede no Porto da empresa Energias de Portugal - SA, tendo em conta a estratégia implementada e os resultados conseguidos. Para isso, dissecámos as premissas apresentadas aos trabalhadores na cerimónia de inauguração do novo espaço - “O Open Space opera como plataforma de comunicação e de partilha de informação” e “O Open Space responde às necessidades dos trabalhadores, criando ambientes de trabalho modernos e funcionais”. A fim de avaliarmos o campo empírico, construímos e enviámos em formato eletrónico para o e-mail de todos os trabalhadores da amostra um instrumento de medida que denominámos de open space (OS). As ilações retiradas estão baseadas nos resultados analisados e discutidos após processamento em SPSS - predictive analytics software and solutions e em reports gráficos. O open space da EDP Porto é um local moderno e funcional, privilegiado em relação à fluidez e partilha de informação, capaz de manifestar estratégias de negócio e de salientar aspetos da marca e da cultura da Empresa. A formação/informação sobre comportamentos e regras básicas a seguir na partilha de um mesmo espaço, as razões de negócio que levam a organização a mudar o espaço de trabalho, a par das vantagens que ambas as partes podem tirar do novo conceito, influencia positivamente ou negativamente a perceção da mudança e o estado emocional dos trabalhadores. O ruído, a temperatura ambiente, a concentração ou a privacidade, são alguns dos fatores que poderão variar com o layout e funcionam como condicionantes de uma maior ou menor satisfação ambiental. No entanto, existem sempre questões que permanecem pendentes e foi nesse contexto que deixámos algumas propostas para novas investigações num trabalho científico que nunca se esgota. / This study focuses on researching the concept of working in an open space in the new Oporto’s headquarters of the company Energias de Portugal - SA, given the strategy implemented and the results achieved. For this, we dissected the assumptions presented to workers at the inauguration ceremony of the new space - "The Open Space operates as a platform for communication and information sharing" and "The Open Space responds to the needs of workers, creating modern and functional workplaces". In order to evaluate the empirical side, we built and sent, in electronic format, an e-mail to all the workers of the sample with a measurement tool that we called the open space (OS). The conclusions are based on the results analyzed and discussed after being processed in SPSS - predictive analytics software and solutions and graphs in reports. The open space of the EDP Oporto is a modern and functional place, privileged in relation to fluidity and information sharing, capable of manifesting business strategies and highlight aspects of the brand and culture of the Company. The training/information on behaviors and basic rules to follow when sharing the same space, the business reasons that lead the organization to change the workspace, along with the advantages that both parties can benefit from the new concept, influence positively or negatively the perception of change and the emotional state of workers. Noise, temperature, concentration or privacy, are some of the factors that may vary with the layout and function as constraints in a greater or lesser environmental satisfaction. However, there are always issues that remain outstanding and it was in this context that we made some proposals for further research in a scientific paper that never runs out.

The MOOC Dashboard: Visualising MOOC data for everyone

Abstract Massive Open Online Courses (MOOCs) generate enormous amounts of data. The University of Southampton has run and is running dozens of MOOC instances. The vast amount of data resulting from our MOOCs can provide highly valuable information to all parties involved in the creation and delivery of these courses. However, analysing and visualising such data is a task that not all educators have the time or skills to undertake. The recently developed MOOC Dashboard is a tool aimed at bridging such a gap: it provides reports and visualisations based on the data generated by learners in MOOCs. Speakers Manuel Leon is currently a Lecturer in Online Teaching and Learning in the Institute for Learning Innovation and Development (ILIaD). Adriana Wilde is a Teaching Fellow in Electronics and Computer Science, with research interests in MOOCs and Learning Analytics. Darron Tang (4th Year BEng Computer Science) and Jasmine Cheng (BSc Mathematics & Actuarial Science and starting MSc Data Science shortly) have been working as interns over this Summer (2016) as have been developing the MOOC Dashboard.

Restoring function after neuromuscular trauma: novel paradigms for enhancing volitional control of neural activity in untethered environments and vHAB, a gamified therapy platform

Thesis (Ph.D.)--University of Washington, 2016-08

La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding

“La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding”. L’obiettivo di questa tesi è quello di illustrare cos’è la Business Intelligence e di mostrare i cambiamenti verificatisi in Ducati Motor Holding, in seguito alla sua adozione, in termini di realizzazione di report e dashboard per il monitoraggio delle vendite. L’elaborato inizia con una panoramica generale sulla storia e gli utilizzi della Business Intelligence nella quale vengono toccati i principali fondamenti teorici: Data Warehouse, data mining, analisi what-if, rappresentazione multidimensionale dei dati, costruzione del team di BI eccetera. Si proseguirà mediante un focus sui Big Data convogliando l’attenzione sul loro utilizzo e utilità nel settore dell’automotive (inteso nella sua accezione più generica e cioè non solo come mercato delle auto, ma anche delle moto), portando in questo modo ad un naturale collegamento con la realtà Ducati. Si apre così una breve overview sull’azienda descrivendone la storia, la struttura commerciale attraverso la quale vengono gestite le vendite e la gamma dei prodotti. Dal quarto capitolo si entra nel vivo dell’argomento: la Business Intelligence in Ducati. Si inizia descrivendo le fasi che hanno fino ad ora caratterizzato il progetto di Business Analytics (il cui obiettivo è per l'appunto introdurre la BI i azienda) per poi concentrarsi, a livello prima teorico e poi pratico, sul reporting sales e cioè sulla reportistica basata sul monitoraggio delle vendite.

NGL Project: Sub-project “Flipped Classroom” : Course “Organization Theory” (FÖ1039)

This paper is the final report from the NGL project implementing the flipped classroom approach into the undergraduate course "Organization Theory". The report describes the implementation and evaluates the outcomes of flipped classroom teaching/learning using the students' survey and statistics from YouTube analytics and the learning management platform Fronter.

Analytiikkajärjestelmän käyttöönottoprojekti, kustannukset ja kustannusten hallinta

Perinteisten kilpailuetujen katoaminen ja kilpailun kiristyminen haastavat yrityksiä etsimään keinoja kilpailukyvyn säilyttämiseksi. Tietotekniikan nopea kehitys ja liiketoiminnassa syntyvän datan määrän kasvu luovat yrityksille mahdollisuuden hyödyntää analytiikkaa päätöksenteon tukena ja liiketoiminnan tehostamisessa. Työ on kirjallisuuskatsaus ja sen tavoitteena on selvittää analytiikkajärjestelmän käyttöönottoprojektin vaiheet, käyttöönottoon liittyvät kustannukset ja miten kustannuksia voidaan hallita. Lisäksi esitetään tiivis katsaus analytiikan kehitykseen ja nykytilaan sekä tarkastellaan hankintamalleja, hankkeiden taloudellista arviointia ja käyttöönottoprojektin kriittisiä menestystekijöitä. Käyttöönottoprojekti on monivaiheinen ja se alkaa liiketoiminnan analysoinnista sekä järjestelmän suunnittelusta ulottuen aina sen toteutukseen ja jälkiarviointiin. Käyttöönottoon liittyy useita kustannuseriä, joita voidaan luokitella niiden ominaisuuksien perusteella. Projektin kustannusten hallinnan prosesseja ovat kustannusten hallinnan suunnittelu, kustannusten arviointi, budjetin määrittäminen ja kustannusten valvonta, jotka limittyvät käyttöönoton vaiheiden kanssa.

High-performance parallel systems for data-intensive computing

Thesis (Ph.D.)--University of Washington, 2016-08

Type-Aware Programming Models for Distributed Applications

Thesis (Ph.D.)--University of Washington, 2016-08