Telescope Bibliographies: an Essential Component of Archival Data Management and Operations

Assessing the impact of astronomical facilities rests upon an evaluation of the scientific discoveries which their data have enabled. Telescope bibliographies, which link data products with the literature, provide a way to use bibliometrics as an impact measure for the underlying data. In this paper we argue that the creation and maintenance of telescope bibliographies should be considered an integral part of an observatory's operations. We review the existing tools, services, and workflows which support these curation activities, giving an estimate of the effort and expertise required to maintain an archive-based telescope bibliography.Comment: 10 pages, 3 figures, to appear in SPIE Astronomical Telescopes and Instrumentation, SPIE Conference Series 844

Building Business Intelligence & Analytics Capabilities - A Work System Perspective

Although enterprises believe that they can achieve a competitive advantage with big data and AI, their analytics initiatives’ success rate still lags behind expectations. Existing research reveals that value creation with business intelligence and analytics (BI&A) is a complex process with multiple stages between the initial investments in BI&A resources and ultimately obtaining value. While prior research mostly focused on value generation mechanisms, we still lack a thorough understanding of how enterprises actually build BI&A capabilities. We explain the process in our research using work system theory (WST). Based on case studies and focus groups, we identify four prevalent BI&A capabilities: reporting, data exploration, analytics experimentation, and analytics production. For each identified BI&A capability, we derive patterns for BI&A resource orchestration, using the WST lens. Our findings complement the BI&A value creation research stream by providing insights into capability building

Libraries and the management of research data

A discussion of the role of university libraries in the management of digital research data outputs. Reviews some of the recent history of progress in this area from a UK perspective, with reference to international developments

The Data Curation Profiles Toolkit: The Profile Template

The Data Curation Profile is composed of the following sections and sub-sections, each of which is defined below. The information used to populate the profile will largely come from the information gathered through the use of the Interview Worksheet and the Interviewer’s Manual. The following table provides a broad overview of how the interview modules correspond to the sections of the Data Curation Profile template

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

IBIS interview report.docx

The survey results provide an understanding of the prevalence of scientists behaviors and attitudes regarding their data. The results of the in-depth interviews allow us to gain insight into the details of how scientists “do” science and how they handle their data. This report outlines the interview process, our analysis and key findings