Emerging Implications of Open and Linked Data for Knowledge Sharing in Development

Movements towards open data involve the publication of datasets (from metadata on publications, to research, to operational project statistics) online in standard formats and without restrictions on reuse. A number of open datasets are published as linked data, creating a web of connected datasets. Governments, companies and non?governmental organisations (NGOs) across the world are increasingly exploring how the publication and use of open and linked data can have impacts on governance, economic growth and the delivery of services. This article outlines the historical, social and technical trajectories that have led to current interest in, and practices around, open data. Drawing on three example cases of working with open and linked data it takes a critical look at issues that development sector knowledge intermediaries may need to engage with to ensure the socio?technical innovations of open and linked data work in the interests of greater diversity and better development practice

Sustainability as corporate culture of a brand for superior performance

This is the post-print version of the final paper published in the Journal of World Business. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2012 Elsevier B.V.Sustainability research highlights new challenges and opportunities for businesses. This paper reviews the literature to understand the ability of sustainable green initiatives when practiced as a corporate culture to individually create new opportunities for operations, management and marketing. According to current research, business opportunities exclusively available to different functions of a firm can drive its performance. The role of marketing in the achievement of superior performance by virtue of sustainability practices is also explained by the existing literature. Branding literature, however, fails to explain the influence of a brand on sustainability-driven opportunities available to a firm for superior performance. The objective of this study is to explore if a brand can strengthen the ability of sustainability-based green initiatives of managers to drive opportunities available to a firm for superior performance. A conceptual framework grounded in the triple bottom line theory is presented based on the assumption that brand as a stimulating factor can accelerate the conversion of opportunities available to a business into superior performance. Academic and managerial perspectives have been used to draw upon the implications of the model. Both practitioners and academic researchers will benefit from future research on this topic

Toward a theory of repeat purchase drivers for consumer services

The marketing discipline’s knowledge about the drivers of service customers’ repeat purchase behavior is highly fragmented. This research attempts to overcome that fragmented state of knowledge by making major advances toward a theory of repeat purchase drivers for consumer services. Drawing on means–end theory, the authors develop a hierarchical classification scheme that organizes repeat purchase drivers into an integrative and comprehensive framework. They then identify drivers on the basis of 188 face-to-face laddering interviews in two countries (USA and Germany) and assess the drivers’ importance and interrelations through a national probability sample survey of 618 service customers. In addition to presenting an exhaustive and coherent set of hierarchical repeat-purchase drivers, the authors provide theoretical explanations for how and why drivers relate to one another and to repeat purchase behavior. This research also tests the boundary conditions of the proposed framework by accounting for different service types. In addition to its theoretical contribution, the framework provides companies with specific information about how to manage long-term customer relationships successfully

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

Background: The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings: Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance: We propose a new neural model for MT pattern computation and motion disambiguation that i

A community resource for paired genomic and metabolomic data mining

Genomics and metabolomics are widely used to explore specialized metabolite diversity. The Paired Omics Data Platform is a community initiative to systematically document links between metabolome and (meta)genome data, aiding identification of natural product biosynthetic origins and metabolite structures.Peer reviewe

Enabling planetary science across light-years. Ariel Definition Study Report

Ariel, the Atmospheric Remote-sensing Infrared Exoplanet Large-survey, was adopted as the fourth medium-class mission in ESA's Cosmic Vision programme to be launched in 2029. During its 4-year mission, Ariel will study what exoplanets are made of, how they formed and how they evolve, by surveying a diverse sample of about 1000 extrasolar planets, simultaneously in visible and infrared wavelengths. It is the first mission dedicated to measuring the chemical composition and thermal structures of hundreds of transiting exoplanets, enabling planetary science far beyond the boundaries of the Solar System. The payload consists of an off-axis Cassegrain telescope (primary mirror 1100 mm x 730 mm ellipse) and two separate instruments (FGS and AIRS) covering simultaneously 0.5-7.8 micron spectral range. The satellite is best placed into an L2 orbit to maximise the thermal stability and the field of regard. The payload module is passively cooled via a series of V-Groove radiators; the detectors for the AIRS are the only items that require active cooling via an active Ne JT cooler. The Ariel payload is developed by a consortium of more than 50 institutes from 16 ESA countries, which include the UK, France, Italy, Belgium, Poland, Spain, Austria, Denmark, Ireland, Portugal, Czech Republic, Hungary, the Netherlands, Sweden, Norway, Estonia, and a NASA contribution