CERN openlab Whitepaper on Future IT Challenges in Scientific Research

This whitepaper describes the major IT challenges in scientific research at CERN and several other European and international research laboratories and projects. Each challenge is exemplified through a set of concrete use cases drawn from the requirements of large-scale scientific programs. The paper is based on contributions from many researchers and IT experts of the participating laboratories and also input from the existing CERN openlab industrial sponsors. The views expressed in this document are those of the individual contributors and do not necessarily reflect the view of their organisations and/or affiliates

BCAS: A Web-enabled and GIS-based Decision Support System for the Diagnosis and Treatment of Breast Cancer

For decades, geographical variations in cancer rates have been observed but the precise determinants of such geographic differences in breast cancer development are unclear. Various statistical models have been proposed. Applications of these models, however, require that the data be assembled from a variety of sources, converted into the statistical models’ parameters and delivered effectively to researchers and policy makers. A web-enabled and GIS-based system can be developed to provide the needed functionality. This article overviews the conceptual web-enabled and GIS-based system (BCAS), illustrates the system’s use in diagnosing and treating breast cancer and examines the potential benefits and implications for breast cancer research and practice

Developing a business intelligence initiative in higher education

ACM Classification: H.4.2 Types of Systems – Decision SupportIn nowadays, Business Intelligence (BI) is one of the most important areas for managers and their organizations, whose investments on this type of projects are increasing. The decision-making process has become crucial to be more competitive, and higher education institutions (HEIs) are not an exception. For the last years, HEIs from all over the world have started to apply BI to their educational and decision-making challenges. In 2013, the BI Task Force from EUNIS (European University Information Systems) surveyed several HEIs to understand the maturity of their BI systems. The results revealed inconsistencies, raising the doubt about the comprehension of BI concepts. Considering this survey and its basis on maturity models, this dissertation analyses the existing models regarding higher education. Understanding the difficulties in answering the EUNIS survey from a perspective of two Portuguese universities is also a goal. It was created a feedback survey, whose results revealed it was a positive experience, although the lack of clarification of BI concepts was underlined. Thinking about other universities starting their BI journey, it was developed a kit proposal that clarifies concepts and best practices for this sector. It was validated by the two universities mentioned above, which will be starting their initiative in January 2015. This validation was made through an interview, and the feedback was encouraging. Having a guidance to be methodical in this phase was highlighted, as well as the presentation of real success cases that allow to understand what other institutions do on their daily basis.Atualmente, Business Intelligence (BI) é uma das mais importantes áreas para gestores e empresas, cujo investimento tem vindo a aumentar substancialmente. A tomada de decisão tem-se tornado fundamental para o aumento da competitividade e as instituições do ensino superior não são exceção. Nos últimos anos, instituições de todo o mundo têm começado a aplicar BI nos seus desafios. Em 2013, a BI Task Force da EUNIS (European University Information Systems) decidiu realizar um inquérito a instituições de ensino superior para conhecer a maturidade dos seus sistemas de BI. Os resultados revelaram incoerências, criando a dúvida sobre a correta compreensão dos conceitos. Tendo em conta este inquérito e a sua base em modelos de maturidade de BI, é realizada uma revisão bibliográfica dos modelos existentes direcionados para o ensino superior. Compreender as dificuldades em responder ao inquérito da EUNIS, na perspetiva de duas universidades, também é um objetivo deste estudo. Foi criado um questionário de feedback, cujos resultados revelaram ter sido uma experiência positiva, embora a falta de clarificação dos conceitos fosse sublinhada. Considerando instituições a iniciar a sua aventura em BI, foi criado um guião que clarifica conceitos e boas práticas para o sector. Foi validado pelas universidades mencionadas, que vão começar as suas iniciativas no próximo ano. Essa validação, feita com entrevistas, revelou que um guião que ajude as universidades a serem metódicas nesta fase é essencial, bem como a apresentação de casos reais de sucesso que permitem dar a conhecer o que é feito no dia-a-dia do sector

Degree of Scaffolding: Learning Objective Metadata: A Prototype Leaning System Design for Integrating GIS into a Civil Engineering Curriculum

Digital media and networking offer great potential as tools for enhancing classroom learning environments, both local and distant. One concept and related technological tool that can facilitate the effective application and distribution of digital educational resources is learning objects in combination with the SCORM (sharable content objects reference model) compliance framework. Progressive scaffolding is a learning design approach for educational systems that provides flexible guidance to students. We are in the process of utilizing this approach within a SCORM framework in the form of a multi-level instructional design. The associated metadata required by SCORM will describe the degree of scaffolding. This paper will discuss progressive scaffolding as it relates to SCORM compliant learning objects, within the context of the design of an application for integrating Geographic Information Systems (GIS) into the civil engineering curriculum at the University of Missouri - Rolla

The National Transport Data Framework

Report by Professor Peter Landshoff (Cambridge University) and Professor John Polak (Imperial College London) on a project for the Department for Transport. emails: [email protected] [email protected] NTDF is designed to be a resource for data owners to deposit descriptions into a central catalogue, so that people can search for data and find data and understand their characteristics. The value of this is to individuals, to commercial organizations, and to public bodies. For example, services that provide better information to travellers will help to make their journey less stressful and persuade them to make more use of public transport. Transport operators need very diverse information to help them plan developments to their services: demographic, geographical, economic etc. And policy makers need a similar range of information to help them decide how to divide their budget and afterwards to evaluate how valuable it has been.This work was supported by the Department for Transport (DfT)

Cloud engineering is search based software engineering too

Many of the problems posed by the migration of computation to cloud platforms can be formulated and solved using techniques associated with Search Based Software Engineering (SBSE). Much of cloud software engineering involves problems of optimisation: performance, allocation, assignment and the dynamic balancing of resources to achieve pragmatic trade-offs between many competing technical and business objectives. SBSE is concerned with the application of computational search and optimisation to solve precisely these kinds of software engineering challenges. Interest in both cloud computing and SBSE has grown rapidly in the past five years, yet there has been little work on SBSE as a means of addressing cloud computing challenges. Like many computationally demanding activities, SBSE has the potential to benefit from the cloud; ‘SBSE in the cloud’. However, this paper focuses, instead, of the ways in which SBSE can benefit cloud computing. It thus develops the theme of ‘SBSE for the cloud’, formulating cloud computing challenges in ways that can be addressed using SBSE

Carbon Free Boston: Buildings Technical Report

Part of a series of reports that includes: Carbon Free Boston: Summary Report; Carbon Free Boston: Social Equity Report; Carbon Free Boston: Technical Summary; Carbon Free Boston: Transportation Technical Report; Carbon Free Boston: Waste Technical Report; Carbon Free Boston: Energy Technical Report; Carbon Free Boston: Offsets Technical Report; Available at http://sites.bu.edu/cfb/OVERVIEW: Boston is known for its historic iconic buildings, from the Paul Revere House in the North End, to City Hall in Government Center, to the Old South Meeting House in Downtown Crossing, to the African Meeting House on Beacon Hill, to 200 Clarendon (the Hancock Tower) in Back Bay, to Abbotsford in Roxbury. In total, there are over 86,000 buildings that comprise more than 647 million square feet of area. Most of these buildings will still be in use in 2050. Floorspace (square footage) is almost evenly split between residential and non-residential uses, but residential buildings account for nearly 80,000 (93 percent) of the 86,000 buildings. Boston’s buildings are used for a diverse range of activities that include homes, offices, hospitals, factories, laboratories, schools, public service, retail, hotels, restaurants, and convention space. Building type strongly influences energy use; for example, restaurants, hospitals, and laboratories have high energy demands compared to other commercial uses. Boston’s building stock is characterized by thousands of turn-of-the-20th century homes and a postWorld War II building boom that expanded both residential buildings and commercial space. Boston is in the midst of another boom in building construction that is transforming neighborhoods across the city. [TRUNCATED]Published versio

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

Acquisition and Declarative Analytical Processing of Spatio-Temporal Observation Data

A generic framework for spatio-temporal observation data acquisition and declarative analytical processing has been designed and implemented in this Thesis. The main contributions of this Thesis may be summarized as follows: 1) generalization of a data acquisition and dissemination server, with great applicability in many scientific and industrial domains, providing flexibility in the incorporation of different technologies for data acquisition, data persistence and data dissemination, 2) definition of a new hybrid logical-functional paradigm to formalize a novel data model for the integrated management of entity and sampled data, 3) definition of a novel spatio-temporal declarative data analysis language for the previous data model, 4) definition of a data warehouse data model supporting observation data semantics, including application of the above language to the declarative definition of observation processes executed during observation data load, and 5) column-oriented parallel and distributed implementation of the spatial analysis declarative language. The huge amount of data to be processed forces the exploitation of current multi-core hardware architectures and multi-node cluster infrastructures

Evolving a secure grid-enabled, distributed data warehouse : a standards-based perspective

As digital data-collection has increased in scale and number, it becomes an important type of resource serving a wide community of researchers. Cross-institutional data-sharing and collaboration introduce a suitable approach to facilitate those research institutions that are suffering the lack of data and related IT infrastructures. Grid computing has become a widely adopted approach to enable cross-institutional resource-sharing and collaboration. It integrates a distributed and heterogeneous collection of locally managed users and resources. This project proposes a distributed data warehouse system, which uses Grid technology to enable data-access and integration, and collaborative operations across multi-distributed institutions in the context of HV/AIDS research. This study is based on wider research into OGSA-based Grid services architecture, comprising a data-analysis system which utilizes a data warehouse, data marts, and near-line operational database that are hosted by distributed institutions. Within this framework, specific patterns for collaboration, interoperability, resource virtualization and security are included. The heterogeneous and dynamic nature of the Grid environment introduces a number of security challenges. This study also concerns a set of particular security aspects, including PKI-based authentication, single sign-on, dynamic delegation, and attribute-based authorization. These mechanisms, as supported by the Globus Toolkit’s Grid Security Infrastructure, are used to enable interoperability and establish trust relationship between various security mechanisms and policies within different institutions; manage credentials; and ensure secure interactions