Suchergebnisse

The Swedish government has decided that all research results in the form of research data and scientific publications financed with public funds should be openly accessible as far as possible. The question is whether the responsible actors and if the universities are ready to implement the change. The significance of open access has amplified in Sweden. Earlier research has brought to light that the collection and preservation of research data are often surrounded by ambiguous rules and lack a comprehensive structure. For example, archiving is not given enough consideration in connection to research projects and researchers often tend to save their material on platforms that are not persistent over time. This article is based upon a qualitative research approach where 15 semi-structured interviews have been used as primarily data sources to investigate the implementation of open access of research data and scientific publications. The article investigated how Swedish universities and public authorities were working with archiving and implementation of open research data and their opinions on open access. The results displayed a lack of coordination, resources and infrastructure but also that common agreed nomenclature were missing. The management of research data was not part of an overall recordkeeping strategy. One explanation could be differences in the information culture among researchers and archivists. Social sciences theory has been combined with archival theory in order to explain the reasons to this. These have been put in relation to the principles of the open data directive. ; This article is licensed under a Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/

Presented at the National data integrity conference: data sharing: the how, why, when and when not to share held on June 2-3, 2016 at University of Colorado, Denver, Colorado. The National Data Integrity Conference is a gathering of people sharing new challenges and solutions regarding research data and integrity. This conference aims to provide attendees with both an understanding of data integrity issues and impart practical tools and skills to deal with them. Topics addressed will include data privacy, openness, policy, education and the impacts of sharing data, how to do it, when to do it, and when not to. Speakers and audience members come from diverse fields such as: Academic Research; Information Technology; Quality Assurance; Regulatory Compliance; Private Industry; Grant Funding; Government. ; Dr. Wirz earned her Ph.D. from Oregon Health & Science University in Biochemistry & Molecular Biology and has a B.S. from Oregon State University in Biochemistry & Biophysics. Her research career has spanned 15 years and has covered diverse topics such as transcriptional regulation, macromolecular structure determination, collagen biophysics and DNA repair. Her professional interests include information, data, and knowledge management, as well as the flow of scientific information. She lectures on a variety of topics including professional skills development, data management, scholarly publication ethics, research impact and semantic technologies, and research communication. Jackie is a strong proponent of science outreach and has developed programs and grants designed to promote scientific, data and information literacy. Jackie believes in evolution, salted caramel buttercream and Jane Eyre. ; PowerPoint presentation given on June 2, 2016.

Presented at the National data integrity conference: data sharing: the how, why, when and when not to share held on June 2-3, 2016 at University of Colorado, Denver, Colorado. The National Data Integrity Conference is a gathering of people sharing new challenges and solutions regarding research data and integrity. This conference aims to provide attendees with both an understanding of data integrity issues and impart practical tools and skills to deal with them. Topics addressed will include data privacy, openness, policy, education and the impacts of sharing data, how to do it, when to do it, and when not to. Speakers and audience members come from diverse fields such as: Academic Research; Information Technology; Quality Assurance; Regulatory Compliance; Private Industry; Grant Funding; Government. ; Dr. Wirz earned her Ph.D. from Oregon Health & Science University in Biochemistry & Molecular Biology and has a B.S. from Oregon State University in Biochemistry & Biophysics. Her research career has spanned 15 years and has covered diverse topics such as transcriptional regulation, macromolecular structure determination, collagen biophysics and DNA repair. Her professional interests include information, data, and knowledge management, as well as the flow of scientific information. She lectures on a variety of topics including professional skills development, data management, scholarly publication ethics, research impact and semantic technologies, and research communication. Jackie is a strong proponent of science outreach and has developed programs and grants designed to promote scientific, data and information literacy. Jackie believes in evolution, salted caramel buttercream and Jane Eyre. ; PowerPoint presentation given on June 2, 2016.

Part 1. The context of sport management research -- Part 2. Planning the sport management research process -- Part 3. Foundations of sport management research -- Part 4. Analysing the sport management data -- Part 5. Paradigms used in sport management research -- Part 6. Digital tools for qualitative research -- Part 7. Writing the sport management research report.

Introduction Health research using routinely collected National Health Service (NHS) data derived from electronic health records (EHRs) and health service information systems has been growing in both importance and quantity. Wide population coverage and detailed patient-level information allow this data to be applied to a variety of research questions. However, the sensitivity, complexity and scale of such data also hamper researchers from fully exploiting this potential.Objective Here, we establish the current challenges preventing researchers from making optimal use of the data sets at their disposal, on both the legislative and practical levels, and give recommendations as to how these challenges can be overcome.Method A number of projects has recently been launched in the UK to address poor research data management practices. Rapid Organisation of Healthcare Research Data (ROHRD) at Imperial College, London produced a useful prototype that provides local researchers with a one-stop index of available data sets together with relevant metadata.Findings Increased transparency of data sets' availability and their provenance leads to better utilisation and facilitates compliance with regulatory requirements.Discussion Research data resulting from NHS data is often not utilised fully, or is handled in a haphazard manner that prevents full auditability of the research. Furthermore, lack of informatics and data management skills in research teams act as a barrier to implementing more advanced practices, such as provenance capture and detailed, regularly updated, data management strategies. Only by a concerted effort at the levels of research organisations, funding bodies and publishers, can we achieve full transparency and reproducibility of the research.

We report on a case study which examines the social science community's capability and institutional support for data management. Fourteen researchers were invited for an in-depth qualitative survey between June 2014 and October 2015. We modify and adopt the Community Capability Model Framework (CCMF) profile tool to ask these scholars to self-assess their current data practices and whether their academic environment provides enough supportive infrastructure for data related activities. The exemplar disciplines in this report include anthropology, political sciences, and library and information science. Our findings deepen our understanding of social disciplines and identify capabilities that are well developed and those that are poorly developed. The participants reported that their institutions have made relatively slow progress on economic supports and data science training courses, but acknowledged that they are well informed and trained for participants' privacy protection. The result confirms a prior observation from previous literature that social scientists are concerned with ethical perspectives but lack technical training and support. The results also demonstrate intra- and inter-disciplinary commonalities and differences in researcher perceptions of data-intensive capability, and highlight potential opportunities for the development and delivery of new and impactful research data management support services to social sciences researchers and faculty.

SIMPLE SUMMARY: Locust outbreaks around the world regularly affect vast areas and millions of people. Mapping and monitoring locust habitats, as well as prediction of locust outbreaks is essential to minimize the damage on crops and pasture. In this context, remote sensing has become one of the most important data sources for effective locust management. This review paper summarizes remote sensing-based studies for locust management and research over the past four decades and reveals progress made and gaps for further research. We quantify which locust species, regions of interest, sensor data and variables were mainly used and which thematic foci were of interest. Our review shows that most studies were conducted for the desert locust, the migratory locust and Australian plague locust and corresponding areas of interest. Remote sensing studies for other destructive locust species are rather rare. Most studies utilized data from optical sensors to derive NDVI and land cover for mapping and monitoring the locust habitats. Furthermore, temperature, precipitation and soil moisture are derived from thermal infrared, passive and active radar sensors. Applications of the European Sentinel fleet, entire Landsat archive or very-high-spatial-resolution data are rare. Implementing new methods (e.g., data fusion) and additional data sources could provide new insights for locust research and management. ABSTRACT: Recently, locust outbreaks around the world have destroyed agricultural and natural vegetation and caused massive damage endangering food security. Unusual heavy rainfalls in habitats of the desert locust (Schistocerca gregaria) and lack of monitoring due to political conflicts or inaccessibility of those habitats lead to massive desert locust outbreaks and swarms migrating over the Arabian Peninsula, East Africa, India and Pakistan. At the same time, swarms of the Moroccan locust (Dociostaurus maroccanus) in some Central Asian countries and swarms of the Italian locust (Calliptamus italicus) in Russia and China ...

Recently, locust outbreaks around the world have destroyed agricultural and natural vegetation and caused massive damage endangering food security. Unusual heavy rainfalls in habitats of the desert locust (Schistocerca gregaria) and lack of monitoring due to political conflicts or inaccessibility of those habitats lead to massive desert locust outbreaks and swarms migrating over the Arabian Peninsula, East Africa, India and Pakistan. At the same time, swarms of the Moroccan locust (Dociostaurus maroccanus) in some Central Asian countries and swarms of the Italian locust (Calliptamus italicus) in Russia and China destroyed crops despite developed and ongoing monitoring and control measurements. These recent events underline that the risk and damage caused by locust pests is as present as ever and affects 100 million of human lives despite technical progress in locust monitoring, prediction and control approaches. Remote sensing has become one of the most important data sources in locust management. Since the 1980s, remote sensing data and applications have accompanied many locust management activities and contributed to an improved and more effective control of locust outbreaks and plagues. Recently, open-access remote sensing data archives as well as progress in cloud computing provide unprecedented opportunity for remote sensing-based locust management and research. Additionally, unmanned aerial vehicle (UAV) systems bring up new prospects for a more effective and faster locust control. Nevertheless, the full capacity of available remote sensing applications and possibilities have not been exploited yet. This review paper provides a comprehensive and quantitative overview of international research articles focusing on remote sensing application for locust management and research. We reviewed 110 articles published over the last four decades, and categorized them into different aspects and main research topics to summarize achievements and gaps for further research and application development. The results reveal a strong focus on three species-the desert locust, the migratory locust (Locusta migratoria), and the Australian plague locust (Chortoicetes terminifera)-and corresponding regions of interest. There is still a lack of international studies for other pest species such as the Italian locust, the Moroccan locust, the Central American locust (Schistocerca piceifrons), the South American locust (Schistocerca cancellata), the brown locust (Locustana pardalina) and the red locust (Nomadacris septemfasciata). In terms of applied sensors, most studies utilized Advanced Very-High-Resolution Radiometer (AVHRR), Satellite Pour l'Observation de la Terre VEGETATION (SPOT-VGT), Moderate-Resolution Imaging Spectroradiometer (MODIS) as well as Landsat data focusing mainly on vegetation monitoring or land cover mapping. Application of geomorphological metrics as well as radar-based soil moisture data is comparably rare despite previous acknowledgement of their importance for locust outbreaks. Despite great advance and usage of available remote sensing resources, we identify several gaps and potential for future research to further improve the understanding and capacities of the use of remote sensing in supporting locust outbreak- research and management.

This event was the third of the 'Failed it to Nailed it' online data seminar series. The event was hosted online through a zoom conference. The event ran for approximately 3 hours in an afternoon session. There were three talks given on different aspects of responsible data management including the ethical dimensions of research data management and different types of legislation with respect to personal and non personal data. These talks covered some of the key concepts that are central to responsible data management alongside some practical methods of carrying these out. The talks were followed by an interactive breakout discussion on the moral and ethical considerations surrounding different aspects of the data lifecycle. The discussions were facilitated by using a set of Moral IT cards developed by researchers at the University of Nottingham.

DISCLAIMER: The present Project Deliverable has been submitted to the European Commission for review. The information and views set out in this report are those of the author(s) and do not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. CoAct proposes a radically new participatory approach through "four wicked" social issues in which citizen groups act as co-researchers. The overall objective of CoAct is to develop and demonstrate the scientific relevance and social impact of Citizen Social Science, which is to date an underexplored area of citizen science. This deliverable constitutes the first draft of the CoAct Data Management Plan. The main obljective of this plan is make the Research Data FAIR, meaning Findable, Accessible, Interoperable and Reusable. The Data Management Plan is expected to be delivered in 3 phases: A draft version at Month 6, a revision at Month 18 and a final version at M36. The current document is the revised version.

The aim of WASTE4THINK ́s Data Management Plan is to provide an analysis of the main elements of the data management policy that are going to be used by the consortium. The results of the project waste4think It will produce an improvement in the management of public services which address the citizens and other stakeholders ́ needs. These services are expected to be based on the combination of Open Government Datasets with user-generated data though social networks and third party data to give place to added value datasets. The Waste4think project's partners are committed to offer as much information as possible generated by the project through Open Access. Such information includes: scientific publications issued by the project consortium, white papers published, open source code generated, anonymous interview results, or datasets used for gathering stakeholders ́ feedback. The present document constitutes the first version of WASTE4THINK`s Data Management Plan (DMP). The main objective of this DMP is to provide an analysis of the main elements of the data management policy that are going to be used by the consortium.