From Social Data Mining to Forecasting Socio-Economic Crisis

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

Gap Analysis Report

Julkaistu versi

ISER 2012 Working Paper No. 1

Large resource development projects take years to plan. During that planning time, the public frequently debates the potential benefits and risks of a project, but with incomplete information. In these debates, some people might assert that a project would have great benefits, while others might assert that it would certainly harm the environment. At the same time, the developer will be assessing different designs, before finally submitting one to the government permitting agencies for evaluation and public scrutiny. For large mines in Alaska, the government permitting process takes years, and often includes an ecological risk assessment. This assessment is a data-intensive, scientific evaluation of the project’s potential ecological risks, based on the specific details of the project. Recently, some organizations have tried to bring scientific rigor to the pre-design public discussions, especially for mining projects, through a pre-design risk ecological risk assessment. This is a scientific assessment of the environmental risks a project might pose, before the details of project design, risk-prevention, and risk-mitigation measures are known. It is important to know whether pre-design risk assessment is a viable method for drawing conclusions about risks of projects. If valid risk predictions can be made at that stage, then people or governments would not have to wait for either a design or for the detailed evaluation that is done during the permitting process. Such an approach could be used to short cut permitting. It could affect project financing; it could affect the schedule, priority, or even the resources that governments put toward evaluating a project. But perhaps most important: in an age where public perceptions are an important influence on a project’s viability and government permitting decisions, a realistic risk assessment can be used to focus public attention on the facts. But if the methodology is flawed and results in poor quality information and unsupportable conclusions, then a pre-design risk assessment could unjustifiably either inflame or calm the public, depending on what it predicts.Executive Summary / Section 1. Introduction / Section 2. Overview of Ecological Risk / Section 3. Ecological Risk Assessment Methodology / Section 4. Examples of Post-Design Ecological Risk Assessments / Section 5. Pre-Design Ecological Risk Assessment: Risks of Large Scale Mining in the Bristol Bay Watershed / Section 6. Conclusion / Bibliograph

Data Science and Ebola

Data Science---Today, everybody and everything produces data. People produce large amounts of data in social networks and in commercial transactions. Medical, corporate, and government databases continue to grow. Sensors continue to get cheaper and are increasingly connected, creating an Internet of Things, and generating even more data. In every discipline, large, diverse, and rich data sets are emerging, from astrophysics, to the life sciences, to the behavioral sciences, to finance and commerce, to the humanities and to the arts. In every discipline people want to organize, analyze, optimize and understand their data to answer questions and to deepen insights. The science that is transforming this ocean of data into a sea of knowledge is called data science. This lecture will discuss how data science has changed the way in which one of the most visible challenges to public health is handled, the 2014 Ebola outbreak in West Africa.Comment: Inaugural lecture Leiden Universit

Measuring impact of academic research in computer and information science on society

Academic research in computer & information science (CIS) has contributed immensely to all aspects of society. As academic research today is substantially supported by various government sources, recent political changes have created ambivalence amongst academics about the future of research funding. With uncertainty looming, it is important to develop a framework to extract and measure the information relating to impact of CIS research on society to justify public funding, and demonstrate the actual contribution and impact of CIS research outside academia. A new method combining discourse analysis and text mining of a collection of over 1000 pages of impact case study documents written in free-text format for the Research Excellence Framework (REF) 2014 was developed in order to identify the most commonly used categories or headings for reporting impact of CIS research by UK Universities (UKU). According to the research reported in REF2014, UKU acquired 83 patents in various areas of CIS, created 64 spin-offs, generated £857.5 million in different financial forms, created substantial employment, reached over 6 billion users worldwide and has helped save over £1 billion Pounds due to improved processes etc. to various sectors internationally, between 2008 and 2013

Independent Expert Scientific Panel – Report on Unconventional Oil and Gas

No abstract available