Harnessing data flow and modelling potentials for sustainable development

Tackling some of the global challenges relating to health, poverty, business and the environment is known to be heavily dependent on the flow and utilisation of data. However, while enhancements in data generation, storage, modelling, dissemination and the related integration of global economies and societies are fast transforming the way we live and interact, the resulting dynamic, globalised and information society remains digitally divided. On the African continent, in particular, the division has resulted into a gap between knowledge generation and its transformation into tangible products and services which Kirsop and Chan (2005) attribute to a broken information flow. This paper proposes some fundamental approaches for a sustainable transformation of data into knowledge for the purpose of improving the peoples' quality of life. Its main strategy is based on a generic data sharing model providing access to data utilising and generating entities in a multi disciplinary environment. It highlights the great potentials in using unsupervised and supervised modelling in tackling the typically predictive-in-nature challenges we face. Using both simulated and real data, the paper demonstrates how some of the key parameters may be generated and embedded in models to enhance their predictive power and reliability. Its main outcomes include a proposed implementation framework setting the scene for the creation of decision support systems capable of addressing the key issues in society. It is expected that a sustainable data flow will forge synergies between the private sector, academic and research institutions within and between countries. It is also expected that the paper's findings will help in the design and development of knowledge extraction from data in the wake of cloud computing and, hence, contribute towards the improvement in the peoples' overall quality of life. To void running high implementation costs, selected open source tools are recommended for developing and sustaining the system. Key words: Cloud Computing, Data Mining, Digital Divide, Globalisation, Grid Computing, Information Society, KTP, Predictive Modelling and STI

Ocean reanalyses: recent advances and unsolved challenges

Ocean reanalyses combine ocean models, atmospheric forcing fluxes, and observations using data assimilation to give a four-dimensional description of the ocean. Metrics assessing their reliability have improved over time, allowing reanalyses to become an important tool in climate services that provide a more complete picture of the changing ocean to end users. Besides climate monitoring and research, ocean reanalyses are used to initialize sub-seasonal to multi-annual predictions, to support observational network monitoring, and to evaluate climate model simulations. These applications demand robust uncertainty estimates and fit-for-purpose assessments, achievable through sustained advances in data assimilation and coordinated inter-comparison activities. Ocean reanalyses face specific challenges: (i) dealing with intermittent or discontinued observing networks, (ii) reproducing inter-annual variability and trends of integrated diagnostics for climate monitoring, (iii) accounting for drift and bias due, e.g., to air-sea flux or ocean mixing errors, and (iv) optimizing initialization and improving performances during periods and in regions with sparse data. Other challenges such as multi-scale data assimilation to reconcile mesoscale and large-scale variability and flow-dependent error characterization for rapidly evolving processes, are amplified in long-term reanalyses. The demand to extend reanalyses backward in time requires tackling all these challenges, especially in the emerging context of earth system reanalyses and coupled data assimilation. This mini-review aims at documenting recent advances from the ocean reanalysis community, discussing unsolved challenges that require sustained activities for maximizing the utility of ocean observations, supporting data rescue and advancing specific research and development requirements for reanalyses

Fake News Detection in Social Networks via Crowd Signals

Our work considers leveraging crowd signals for detecting fake news and is motivated by tools recently introduced by Facebook that enable users to flag fake news. By aggregating users' flags, our goal is to select a small subset of news every day, send them to an expert (e.g., via a third-party fact-checking organization), and stop the spread of news identified as fake by an expert. The main objective of our work is to minimize the spread of misinformation by stopping the propagation of fake news in the network. It is especially challenging to achieve this objective as it requires detecting fake news with high-confidence as quickly as possible. We show that in order to leverage users' flags efficiently, it is crucial to learn about users' flagging accuracy. We develop a novel algorithm, DETECTIVE, that performs Bayesian inference for detecting fake news and jointly learns about users' flagging accuracy over time. Our algorithm employs posterior sampling to actively trade off exploitation (selecting news that maximize the objective value at a given epoch) and exploration (selecting news that maximize the value of information towards learning about users' flagging accuracy). We demonstrate the effectiveness of our approach via extensive experiments and show the power of leveraging community signals for fake news detection

Production of Innovations within Farmer–Researcher Associations Applying Transdisciplinary Research Principles

Small-scale farmers in sub-Saharan West Africa depend heavily on local resources and local knowledge. Science-based knowledge is likely to aid decision-making in complex situations. In this presentation, we highlight a FiBL-coordinated research partnership between three national producer organisations and national agriculture research bodies in Mali, Burkina Faso, and Benin. The partnership seeks to compare conventional, GMObased, and organic cotton systems as regards food security and climate change

The value of rude health.

Executive summary: The report demonstrates that health and wellbeing policies at Royal Mail Group have had a number of significant and material effects:  Royal Mail Group has successfully tackled the issue of absenteeism (CHAPTER ONE): Royal Mail achieved significant reductions in absence – from 7% to 5% – between January 2004 and May 2007, equivalent to an extra 3,600 employees in work Parcelforce Worldwide reduced absence from 7% to 4.5% between January 2004 and May 2007 equivalent to an extra 104 employees in work There is a strong link between both organisations’ range of health and wellbeing and absence policies and reductions in absence (based on available data and interviews) Reducing absence has enabled both Royal Mail Group and its Parcelforce Worldwide business unit to make significant cost savings (CHAPTER TWO): LSE estimates of the annual staff cost of 1% short-term absence across Royal Mail would be on an annual basis: £34.8 millioniv excluding the cost of replacement labour such as overtime and agency staff / £75.9 million including such costs LSE’s estimates suggest that reducing absence by 2% between 2004 and 2007 would have contributed to a total saving across Royal Mail Group over the three years of as much as £227 millionv in terms of direct costs These estimates are based on the accounting cost of a day’s absence in terms of pay and benefit costs, and use of replacement labour either through agency staff or overtime Reducing absence will have saved at least £1.79 millionvi in direct costs annually for each percentage point reduction in absence in Parcelforce Worldwide Since being introduced in 2004, it is estimated that the policies which led to this 2.5% reduction in absence could have contributed to a total saving over the three years of as much as £6.7vii million in direct costs for Parcelforce Worldwide Controlling absence specifically enables managers at Parcelforce Worldwide to hit their targets more easily (CHAPTER THREE): It removes unpredictability in meeting profitability targets that managers are set, enabling them to keep unit costs down as well as hit targets for items delivered per day and grow depot net income more easily Across, all depots, reducing absence by 1% is worth £1,317,000 to Parcelforce Worldwide annually in terms of meeting net income targetsviii Reducing absence by 1% takes an average depot £2,300 closer to its daily net income target Tackling absenteeism reduces dependency on replacement labour, including agency staff. The evidence from Parcelforce Worldwide suggests that doing so safeguards performance indicators such as Quality of Service (QoS) and improves net income through bringing costs down (CHAPTER FOUR): The experience across Parcelforce Worldwide shows that reducing dependence on replacement labour such as agency staff prevents key performance indicators from slipping and strengthens a depot’s bottom line. Reducing absence by 1% adds more than £319,000ix annually to net income through reduced dependence on replacement labour This is primarily as a result of: i. Cost savings (replacement labour is expensive) ii. Improved efficiency – analysis suggests agency staff are half as efficient. This is supported by evidence drawn from interviews with managers LSE estimates that that the 2.5% reduction in absence achieved by Parcelforce Worldwide between January 2004 and May 2007 would have contributed at least £1.2 millionx to improved net income across the group Reducing absence has a positive effect on Quality of Service (QoS) – a key performance indicator both for Parcelforce Worldwide and for Royal Mail – by around a factor of 12 to one. 7 Improvements in QoS enable Parcelforce Worldwide to capture additional business and improve net income (roughly equivalent to profitability) (CHAPTER FIVE):  Reducing absence by 2.5% between January 2004 and May 2007 would have contributed to a 0.2% point increase in QoS all things being equal. i. This figure is derived from estimates relating to the individual depots. It is difficult to draw concrete conclusions about the aggregate movement in QoS across all depots Improvements in QoS enable depots to bring in more business through building a reputation for reliability with customers A 2.5% reduction in absence contributes to an improvement in net income of £448,000 annually through improvements in QoS This improvement in net income reflects: i. Greater cost savings through reduced absence ii. Greater efficiency Analysis by LSE suggests that between Jan 2004 and May 2007, improvements in QoS would have contributed at least £672,000 to Parcelforce Worldwide’s annual net income LSE has extrapolated from the example of Royal Mail Group to illustrate the wider benefits to the economy of tackling the issue of health and wellbeing (CHAPTER SIX) Royal Mail’s success in addressing the health and wellbeing of its employees provides an effective blueprint on tackling absence for the 13 worst performing sectors in the UK in terms of absence rates By concentrating on raising attendance in the poorest performing sites and depots and moving them towards average rates of absence, Royal Mail Group has demonstrated a highly effective method for improving the group-wide average absence rate Following the example of Royal Mail Group in addressing the ‘long tail’ of absence and investing in such policies among the 13 sectors in the economy with the highest absence rates would be worth £1.45 billion to the UK economy.

Methods for Ordinal Peer Grading

MOOCs have the potential to revolutionize higher education with their wide outreach and accessibility, but they require instructors to come up with scalable alternates to traditional student evaluation. Peer grading -- having students assess each other -- is a promising approach to tackling the problem of evaluation at scale, since the number of "graders" naturally scales with the number of students. However, students are not trained in grading, which means that one cannot expect the same level of grading skills as in traditional settings. Drawing on broad evidence that ordinal feedback is easier to provide and more reliable than cardinal feedback, it is therefore desirable to allow peer graders to make ordinal statements (e.g. "project X is better than project Y") and not require them to make cardinal statements (e.g. "project X is a B-"). Thus, in this paper we study the problem of automatically inferring student grades from ordinal peer feedback, as opposed to existing methods that require cardinal peer feedback. We formulate the ordinal peer grading problem as a type of rank aggregation problem, and explore several probabilistic models under which to estimate student grades and grader reliability. We study the applicability of these methods using peer grading data collected from a real class -- with instructor and TA grades as a baseline -- and demonstrate the efficacy of ordinal feedback techniques in comparison to existing cardinal peer grading methods. Finally, we compare these peer-grading techniques to traditional evaluation techniques.Comment: Submitted to KDD 201

Measurement with Persons: A European Network

The European ‘Measuring the Impossible’ Network MINET promotes new research activities in measurement dependent on human perception and/or interpretation. This includes the perceived attributes of products and services, such as quality or desirability, and societal parameters such as security and well-being. Work has aimed at consensus about four ‘generic’ metrological issues: (1) Measurement Concepts & Terminology; (2) Measurement Techniques: (3) Measurement Uncertainty; and (4) Decision-making & Impact Assessment, and how these can be applied specificallyto the ‘Measurement of Persons’ in terms of ‘Man as a Measurement Instrument’ and ‘Measuring Man.’ Some of the main achievements of MINET include a research repository with glossary; training course; book; series of workshops;think tanks and study visits, which have brought together a unique constellation of researchers from physics, metrology,physiology, psychophysics, psychology and sociology. Metrology (quality-assured measurement) in this area is relativelyunderdeveloped, despite great potential for innovation, and extends beyond traditional physiological metrology in thatit also deals with measurement with all human senses as well as mental and behavioral processes. This is particularlyrelevant in applications where humans are an important component of critical systems, where for instance health andsafety are at stake

Net solar generation potential from urban rooftops in Los Angeles

Rooftops provide accessible locations for solar energy installations. While rooftop solar arrays can offset in-building electricity needs, they may also stress electric grid operations. Here we present an analysis of net electricity generation potential from distributed rooftop solar in Los Angeles. We integrate spatial and temporal data for property-level electricity demands, rooftop solar generation potential, and grid capacity constraints to estimate the potential for solar to meet on-site demands and supply net exports to the electric grid. In the study area with 1.2 million parcels, rooftop solar could meet 7200 Gigawatt Hours (GWh) of on-site building demands (~29% of demand). Overall potential net generation is negative, meaning buildings use more electricity than they can produce. Yet, cumulative net export potential from solar to grid circuits is 16,400 GWh. Current policies that regulate solar array interconnection to the grid result in unutilized solar power output of 1700 MW. Lower-income and at-risk communities in LA have greater potential for exporting net solar generation to the grid. This potential should be recognized through investments and policy innovations. The method demonstrates the need for considering time-dependent calculations of net solar potential and offers a template for distributed renewable energy planning in cities