Designing Traceability into Big Data Systems

Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems need to be designed from the outset to support usage of such Items across the spectrum of business use rather than from any specific application view. The design philosophy advocated in this paper is to drive the design process using a so-called description-driven approach which enriches models with meta-data and description and focuses the design process on Item re-use, thereby promoting traceability. Details are given of the description-driven design of big data systems at CERN, in health informatics and in business process management. Evidence is presented that the approach leads to design simplicity and consequent ease of management thanks to loose typing and the adoption of a unified approach to Item management and usage.Comment: 10 pages; 6 figures in Proceedings of the 5th Annual International Conference on ICT: Big Data, Cloud and Security (ICT-BDCS 2015), Singapore July 2015. arXiv admin note: text overlap with arXiv:1402.5764, arXiv:1402.575

Evaluating complex digital resources

Squires (1999) discussed the gap between HCI (Human Computer Interaction) and the educational computing communities in their very different approaches to evaluating educational software. This paper revisits that issue in the context of evaluating digital resources, focusing on two approaches to evaluation: an HCI and an educational perspective. Squires and Preece's HCI evaluation model is a predictive model ‐ it helps teachers decide whether or not to use educational software ‐ whilst our own concern is in evaluating the use of learning technologies. It is suggested that in part the different approaches of the two communities relate to the different focus that each takes: in HCI the focus is typically on development and hence usability, whilst in education the concern is with the learner and teacher use

A Framework for Designing 3d Virtual Environments

The process of design and development of virtual environments can be supported by tools and frameworks, to save time in technical aspects and focusing on the content. In this paper we present an academic framework which provides several levels of abstraction to ease this work. It includes state-of-the-art components we devised or integrated adopting open-source solutions in order to face specific problems. Its architecture is modular and customizable, the code is open-source.\u

Materializing design fictions for metaverse services

As the state-of-the-art stands, our knowledge of designing Metaverse platforms is limited. In this paper we propose that design fictions are the first form of prototyping and explore how ‘materializing’ a design fiction can help cement or refute assumptions that drive the development of a software-based system toward a first Minimum Viable Product. Our context is a platform for trading music memorabilia in the Metaverse, integrating content sitting across archives, record labels, publishers, and private collections in an immersive and accessible manner. The design fiction provided both a means of exploring the businessassumptions of our industry partner and co-creating an experience of value to its intended audience. As key outcomes, the approach was of value in shapingbusiness assumptions, developing an enhanced understanding of the audience and allowing them to cocreate, shaping technology needs and identifying partners necessary for the development

Incorporating Online Instruction in Academic Libraries: Getting Ahead of the Curve

A sea change in higher education is shaping the way many libraries deliver instruction to their students and faculty. Years of technological innovation and changes in the way that people discover and use information has made online instruction an essential part of a library\u27s teaching and learning program. In order to evaluate our library\u27s online instruction program and to determine its future goals, we analyzed the technology, pedagogical models, organizational structures, administrative supports, and partnerships we would need in order to succeed. Our findings may be useful for libraries reassessing their own online instruction programs

Big Data in the Oil and Gas Industry: A Promising Courtship

The energy industry remains one of the highest money-producing and investment industries in the world. The United States’ own economic stability depends greatly on the stability of oil and gas prices. Various factors affect the amount of money that will continue to be invested in producing oil. A main disadvantage to the oil and gas industry is its lack of technological adaptation. This weakens the industry because the surest measures are not currently being taken to produce oil in optimally efficient, safe, and cost-effective ways. Big data has gained global recognition as an opportunity to gather large volumes of information in real-time and translate data sets into actionable insights. In a low commodity price environment, saving time, reducing costs, and improving safety are crucial outcomes that can be realized using machine learning in oil and gas operations. Big data provides the opportunity to use unsupervised learning. For example, with this approach, engineers can predict oil wells’ optimal barrels of production given the completion data in a specific area. However, a caveat to utilizing big data in the oil and gas industry is that there simply is neither enough physical data nor data velocity in the industry to be properly referred to as “big data.” Big data, as it develops, will nonetheless significantly change the energy business in the future, as it already has in various other industries.Petroleum and Geosystems Engineerin