16 research outputs found

    Understanding the Brain through Neuroinformatics

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    Brain in the Shell. Assessing the Stakes and the Transformative Potential of the Human Brain Project

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    The “Human Brain Project” (HBP) is a large-scale European neuroscience and information communication technology (ICT) project that has been a matter of heated controversy since its inception. With its aim to simulate the entire human brain with the help of supercomputing technologies, the HBP plans to fundamentally change neuroscientific research practice, medical diagnosis, and eventually the use of computers itself. Its controversial nature and its potential impacts render the HBP a subject of crucial importance for critical studies of science and society. In this paper, we provide a critical exploratory analysis of the potential mid- to long-term impacts the HBP and its ICT infrastructure could be expected to have, provided its agenda will indeed be implemented and executed to a substantive degree. We analyse how the HBP aspires to change current neuroscientific practice, what impact its novel infrastructures could have on research culture, medical practice and the use of ICT, and how, given a certain degree of successful execution of the project’s aims, potential clinical and methodological applications could even transform society beyond scientific practice. Furthermore, we sketch the possibility that research such as that projected by the HBP may eventually transform our everyday world, even beyond the scope of the HBP’s explicit agenda, and beyond the isolated ‘application’ of some novel technological device. Finally, we point towards trajectories for further philosophical, historical and sociological research on the HBP that our exploratory analysis might help to inspire. Our analysis will yield important insights regardless of the actual success of the HBP. What we drive at, for the most part, is the broader dynamics of scientific and technological development of which the HBP agenda is merely one particularly striking exemplification

    The evaluation of the XooNIps content management system for research data database.

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    Neurotieteiden alalla on tarvetta tietokannoille tutkimustiedon monimuotoisuuden ja sen hallinnan vaikeuden vuoksi. Aivoja tutkivaa tietoa on haastavaa yhdistää ymmärrettäväksi kokonaisuudeksi, mikä on luonut tarpeen tietokantojen käytölle tutkimuksissa. Tietoa ei ole pystytty tallentamaan organisoidusti yhteen paikkaan. Tässä työssä tutkimusryhmän tiedon hallintaan valittiin japanilaisten neuroinformaatikkojen kehittämä XooNIps-sisällönhallintasovellus. XooNIps:n soveltuvuutta tutkimusryhmän käyttöön arvioitiin ryhmältä kerättyjä vaatimuksia vasten. Arviointi sisälsi sovelluksen käyttökokeilujen lisäksi XooNIps:n tietokannan takaisinmallinnuksen käsitteelliseksi malliksi ja sen vertailun kerättyjen vaatimusten mukaan laadittuun uuteen malliin. Vertailun tuloksena löydettiin yhtäläisyyksiä mallien välillä mutta myös eroja, joita uudelleen suunnitellulla mallilla pyrittiin löytämään. Uudelleen suunniteltu malli ottaa paremmin huomioon tietotyyppien metatietojen tallennuksen. Lisäksi tiettyjen tiedostotyyppien vaatimien otsikkotiedostojen tallennus onnistuu uudella mallilla. Vertailussa tuli esiin myös, että uudelleen suunnitellussa mallissa ei huomioida mahdollista kehittämiskohtaa hakemistopohjaisen tiedon tallennukseen, joka molemmissa malleissa on melko samankaltainen. Vertailulla onnistuttiin todentamaan, että uudelleen suunniteltu malli paransi alkuperäistä mallia. Vertailussa tuli kuitenkin myös ilmi, että uudelleen suunnitellussa mallissakin on kehitystarvetta. /Kir1

    A Step Change for Earth System Research: Future Earth – Research for Global Sustainability

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    More integration between scientific disciplines and between the scientific, development and policy communities have been called for by nations and organisations around the world to address the mounting challenge of a transition to sustainability in general and sustainable development in par-ticular

    LayerBoom Strategy

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    The purpose of this MBA project is to analyze the market situation for one cloud computing company, LayerBoom, as it struggles with questions of expansion. Particular focus is paid to the current market situation within the cloud computing industry as well as the corporate structure of LayerBoom

    Proposed taxonomy and framework to support the decision-making of investments in Big Science

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    RÉSUMÉ: Au cours des sept dernières décennies, les projets de Mégascience (Big Science) ont adopté une dimension internationale, sont devenus plus complexes et plus coûteux, rendant ainsi plus difficile la prise de décision des gouvernements en matière d’investissement. Combinant des méthodes de recherche qualitatives et quantitatives, l’objectif principal de cette recherche est d’aider les gouvernements nationaux à améliorer leur capacité à prendre des décisions éclairées et structurées en matière d’investissement en Mégascience, avec la participation de la communauté scientifique et de l’industrie. Pour atteindre cet objectif, deux objectifs spécifiques sont poursuivis. Le premier vise à construire une taxonomie générale de la Mégascience qui offre une compréhension globale allant au-delà de la vision traditionnelle du terme, c’est-à-dire de gros projets d’infrastructure pour la physique de haute énergie. Cette taxonomie est construite sur la base de domaines de recherche qui, en combinaison avec des définitions pratiques et complètes, peut être utilisée pour présélectionner des projets qui, s’ils répondent à des exigences spécifiques, seront éligibles à recevoir des financements importants. Le deuxième objectif spécifique est la structuration du problème de l’investissement gouvernemental en Mégascience. À cet effet, une série de 50 entretiens avec des parties prenantes de haut niveau de la Mégascience trace un portrait détaillé de la complexité de la prise de décision de financement. Les résultats ont révélé qu’il existe une seule cause principale du problème de décision d’investissement en Mégascience qui est la nature même de la Mégascience, dont le but est d’explorer la frontière de la connaissance, plutôt que le montant astronomique du financement en lui-même. La structuration du problème a également révélé que pour résoudre le problème, il est nécessaire de promouvoir un processus décisionnel qui soit objectif, et donc fondé sur des critères qualitatifs et / ou quantitatifs. Au final, cette recherche propose un cadre systématique et personnalisable afin de faciliter la prise de décision en matière d’investissements dans le domaine de la Mégascience. Le système propose un index de la Mégascience (« BigSci Index »), compatible avec toutes les initiatives en Mégascience de façon à fournir un cadre transparent, éclairé et fondé sur des données probantes pour le processus décisionnel et la reddition de comptes. La communauté scientifique, les représentants de l’industrie et les analystes gouvernementaux sont des éléments centraux de cette cadre. Les résultats de cette recherche offrent une double perspective par l’intermédiaire d’une contribution à une meilleure compréhension du phénomène de la Mégascience et également par l’introduction d’une nouvelle approche du problème de la prise de décision dans le financement des projets. L’adoption du cadre proposé permettrait de garantir aux gouvernements une prise de décision éclairée dans les investissements en Mégascience tout en adoptant les meilleures pratiques dans un processus rationnel, structuré et objectif. Ces avantages comprennent également une utilisation plus efficace des fonds publics et une plus grande transparence dans la prise de décision. Cela se traduirait en effet par une augmentation des avantages sociaux, économiques, politiques et scientifiques des investissements dans des projets de Mégascience.----------ABSTRACT: Over the past 70 years, Big Science projects have adopted an international dimension, which has become more complex, costly, and challenging regarding governments’ decision-making in investments. Combining qualitative and quantitative research methods, this research’s primary goal is to support national governments to improve their capacity to make informed and structured decisions on Big Science investments, with the participation of the scientific community and the industry. To reach this goal, two specific objectives are pursued. The first specific objective is to build a taxonomy of Big Science that provides a comprehensive understanding of the term beyond the traditional view of BigSci as high-energy physics infrastructure projects. This taxonomy is built based on research fields that, along with a proposed workable and comprehensive definition of Big Science, may be used to pre-select candidate project proposals to receive significant investments if they meet specific requirements. The second specific objective is to structure the problem of government investments in Big Science. To that effect, a set of 50 interviews with high-level Big Science stakeholders provided an in-depth portrait of the complex situation of the funding decision. The results revealed a single prime cause of the Big Science investment decision problem, which is the inherent nature of Big Science of exploring the frontier of knowledge, rather than the exorbitant amount of funding it demands. The problem structuring also revealed that to solve the problem, it is necessary to promote a decision-making process that should be objective, i.e., grounded on qualitative and/or quantitative criteria. In the end, this research proposes a systematic and customizable framework for supporting the decision-making of Big Science investments. The framework introduces the BigSci Index, which addresses any Big Science initiative and provides measures to ensure transparent, informed, and evidence-based decision-making and accountability. The scientific community, industry representatives, and government analysts are central components of the framework. The results provide a two-fold perspective: they contribute to a new understanding of the phenomenon of Big Science and offer a new approach to its funding decision problem. Adopting the proposed framework for the government decision-making of Big Science investments would ensure that decisions are well informed, follow best practices, and involve a rational, structured, and objective process. The benefits also include more effective use of public funds and greater clarity and transparency in decision-making. These, in turn, would translate into increased social, economic, political, and scientific benefits from investments in Big Science projects

    Promoting access to public research data for scientific, economic, and social development

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    It is now commonplace to say that information and communications technologies are rapidly transforming the world of research. We are only beginning to recognize, however, that management of the scientific enterprise must adapt if we, as a society, are to take full advantage of the knowledge and understanding generated by researchers. One of the most important areas of information and communication technology (ICT)-driven change is the emergence of escience, briefly described as universal desktop access, via the Internet, to distributed resources, global collaboration, and the intellectual, analytical, and investigative output of the world’s scientific community.The vision of e-science is being realised in relation to the outputs of science, particularly journal articles and other forms of scholarly publication. This realisation extends less to research data, the raw material at the heart of the scientific process and the object of significant annual public investments.Ensuring research data are easily accessible, so that they can be used as often and as widely as possible, is a matter of sound stewardship of public resources. Moreover, as research becomes increasingly global, there is a growing need to systematically address data access and sharing issues beyond national jurisdictions. The goals of this report and its recommendations are to ensure that both researchers and the public receive optimum returns on the public investments in research, and to build on the value chain of investments in research and research data. To some extent, research data are shared today, often quite extensively within established networks, using both the latest technology and innovative management techniques. The Follow Up Group drew on the experiences of several of these networks to examine the roles and responsibilities of governments as they relate to data produced from publicly funded research. The objective was to seek good practices that can be used by national governments, international bodies, and scientists in other areas of research. In doing so, the Group developed an analytical framework for determining where further improvements can be made in the national and international organization, management, and regulation of research data.The findings and recommendations presented here are based on the central principle that publicly funded research data should be openly available to the maximum extent possible. Availability should be subject only to national security restrictions; protection of confidentiality and privacy; intellectual property rights; and time-limited exclusive use by principal investigators. Publicly funded research data are a public good, produced in the public interest. As such they should remain in the public realm. This does not preclude the subsequent commercialization of research results in patents and copyrights, or of the data themselves in databases, but it does mean that a copy of the data must be maintained and made openly accessible. Implicitly or explicitly, this principle is recognized by many of the world’s leading scientific institutions, organizations, andagencies. Expanding the adoption of this principle to national and international stages will enable researchers, empower citizens and convey tremendous scientific, economic, and social benefits. Evidence from the case studies and from other investigation undertaken for this report suggest that successful research data access and sharing arrangements, or regimes, share a number of key attributes and operating principles. These bring effective organization and management to the distribution and exchange of data. The key attributes include: openness; transparency of access and active dissemination; the assignment and assumption of formal responsibilities; interoperability; quality control; operational efficiency and flexibility; respect for private intellectual property and other ethical and legal matters; accountability; and professionalism. Whether they are discipline-specific or issue oriented, national or international, the regimes that adhere to these operating principles reap the greatest returns from the use of research data. There are five broad groups of issues that stand out in any examination of research data access and sharing regimes. The Follow Up Group used these as an analytical framework for examining the case studies that informed this report, and in doing so, came to several broad conclusions: • Technological issues: Broad access to research data, and their optimum exploitation, requires appropriately designed technological infrastructure, broad international agreement on interoperability, and effective data quality controls; • Institutional and managerial issues: While the core open access principle applies to all science communities, the diversity of the scientific enterprise suggests that a variety of institutional models and tailored data management approaches are most effective in meeting the needs of researchers; • Financial and budgetary issues: Scientific data infrastructure requires continued, and dedicated, budgetary planning and appropriate financial support. The use of research data cannot be maximized if access, management, and preservation costs are an add-on or after-thought in research projects; • Legal and policy issues: National laws and international agreements directly affect data access and sharing practices, despite the fact that they are often adopted without due consideration of the impact on the sharing of publicly funded research data; • Cultural and behavioural issues: Appropriate reward structures are a necessary component for promoting data access and sharing practices. These apply to both those who produce and those who manage research data.The case studies and other research conducted for this report suggest that concrete, beneficial actions can be taken by the different actors involved in making possible access to, and sharing of, publicly funded research data. This includes the OECD as an international organization with credibility and stature in the science policy area. The Follow Up Group recommends that the OECD consider the following: • Put the issues of data access and sharing on the agenda of the next Ministerial meeting; • In conjunction with relevant member country research organizations, o Conduct or coordinate a study to survey national laws and policies that affect data access and sharing practices; o Conduct or coordinate a study to compile model licensing agreements and templates for access to and sharing of publicly funded data; • With the rapid advances in scientific communications made possible by recent developments in ICTs, there are many aspects of research data access and sharing that have not been addressed sufficiently by this report, would benefit from further study, and will need further clarification. Accordingly, further possible actions areas include: o Governments from OECD expand their policy frameworks of research data access and sharing to include data produced from a mixture of public and private funds; o OECD consider examinations of research data access and sharing to include issues of interacting with developing countries; and o OECD promote further research, including a comprehensive economic analysis of existing data access regimes, at both the national and research project or program levels.National governments have a crucial role to play in promoting and supporting data accessibility since they provide the necessary resources, establish overall polices for data management, regulate matters such as the protection of confidentiality and privacy, and determine restrictions based on national security. Most importantly, national governments are responsible for major research support and funding organizations, and it is here that many of the managerial aspects ofdata sharing need to be addressed. Drawing on good practices worldwide, the Follow Up Group suggests that national governments should consider the following: • Adopt and effectively implement the principle that data produced from publicly funded research should be openly vailable to the maximum extent possible; • Encourage their research funding agencies and major data producing departments to work together to find ways to enhance access to statistical data, such as census materials and surveys; • Adopt free access or marginal cost pricing policies for the dissemination of researchuseful data produced by government departments and agencies; • Analyze, assess, and monitor policies, programs, and management practices related to data access and sharing polices within their national research and research funding organizations. The widespread national, international and cross-disciplinary sharing of research data is no longer a technological impossibility. Technology itself, however, will not fulfill the promise of escience.Information and communication technologies provide the physical infrastructure. It is up to national governments, international agencies, research institutions, and scientists themselves to ensure that the institutional, financial and economic, legal, and cultural and behavioural aspects of data sharing are taken into account

    Mecanismos de codificación y procesamiento de información en redes basadas en firmas neuronales

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    Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Tecnología Electrónica y de las Comunicaciones. Fecha de lectura: 21-02-202
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