A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is
This report contains a concise description of the online repository of the SYNCHROS project (Deliverable 1.2). Intended readers and users of this document are project team members who are involved in the project work, for instance as authors of deliverables, WP-leaders, authors of web-articles, bloggers or anyone who is in charge of external communication and dissemination. The document contains the following information: Description of overall structure and content of the repository. Technicaldoi:10.5281/zenodo.6389971 fatcat:s6vesoxvzrfrtmmbk6s3q2jlwu
more »... characteristics of the repository construction. Details on how to use the data management site. An overview of the public repository.
The lack of accessible and structured documentation creates major barriers for investigators interested in understanding, properly interpreting and analyzing cohort data and biological samples. Providing the scientific community with open information is essential to optimize usage of these resources. A cataloguing toolkit is proposed by Maelstrom Research to answer these needs and support the creation of comprehensive and user-friendly studyand network-specific web-based metadata catalogues.doi:10.1371/journal.pone.0200926 pmid:30040866 pmcid:PMC6057635 fatcat:vi5lurvp3fdd3cxi7muprtl5fq
Motivation: Improving the dissemination of information on existing epidemiological studies and facilitating the interoperability of study databases are essential to maximizing the use of resources and accelerating improvements in health. To address this, Maelstrom Research proposes Opal and Mica, two inter-operable open-source software packages providing out-of-the-box solutions for epidemiological data management, harmonization and dissemination. Implementation: Opal and Mica are twodoi:10.1093/ije/dyx180 pmid:29025122 pmcid:PMC5837212 fatcat:27c2vl43vnehfmoz5wt46fiq4m
Author Contributions Conceptualization: Yannick Marcon, Juan R. González. ...doi:10.1371/journal.pcbi.1008880 pmid:33784300 fatcat:thhhk5smhbhl5ns62w2ydzldya
Abstracts Background: Individual-level data pooling of large population-based studies across research centres in international research projects faces many hurdles. The BioSHaRE (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project aims to address these issues by building a collaborative group of investigators and developing tools for data harmonization, database integration and federated data analyses. Methods: Eight population-based studies in sixdoi:10.1186/1742-7622-10-12 pmid:24257327 pmcid:PMC4175511 fatcat:lliqcdc5gbbnldspb7fypguouu
more »... ropean countries were recruited to participate in the BioSHaRE project. Through workshops, teleconferences and electronic communications, participating investigators identified a set of 96 variables targeted for harmonization to answer research questions of interest. Using each study's questionnaires, standard operating procedures, and data dictionaries, harmonization potential was assessed. Whenever harmonization was deemed possible, processing algorithms were developed and implemented in an open-source software infrastructure to transform study-specific data into the target (i.e. harmonized) format. Harmonized datasets located on server in each research centres across Europe were interconnected through a federated database system to perform statistical analysis. Results: Retrospective harmonization led to the generation of common format variables for 73% of matches considered (96 targeted variables across 8 studies). Authenticated investigators can now perform complex statistical analyses of harmonized datasets stored on distributed servers without actually sharing individual-level data using the DataSHIELD method. Conclusion: New Internet-based networking technologies and database management systems are providing the means to support collaborative, multi-center research in an efficient and secure manner. The results from this pilot project show that, given a strong collaborative relationship between participating studies, it is possible to seamlessly co-analyse internationally harmonized research databases while allowing each study to retain full control over individual-level data. We encourage additional collaborative research networks in epidemiology, public health, and the social sciences to make use of the open source tools presented herein.
Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK's proposed 'care.data' initiative, and these issues reflectdoi:10.1093/ije/dyu188 pmid:25261970 pmcid:PMC4276062 fatcat:ykgoyojworhhdiog4davtpwft4
more »... rtant societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Methods: Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Results: Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. Conclusions: DataSHIELD facilitates important research in settings where: (i) a coanalysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis. • DataSHIELD provides a solution when ethico-legal considerations prevent or impede data-sharing and analysis. • It promotes and facilitates collaborations by empowering data owners and affording them better control over their data. • DataSHIELD has the potential to protect the intellectual property of researchers in institutions and countries with limited resources, thus enabling more balanced collaborations with wealthier partners. • It also improves the governance and management of data by allowing them to be maintained locally.
Motivation: Improving the dissemination of information on existing epidemiological studies and facilitating the interoperability of study databases are essential to maximizing the use of resources and accelerating improvements in health. To address this, Maelstrom Research proposes Opal and Mica, two inter-operable open-source software packages providing out-of-the-box solutions for epidemiological data management, harmonization and dissemination. Implementation: Opal and Mica are twodoi:10.5451/unibas-ep57738 fatcat:qhlx3nmwgjedth6f3ccf5e2utq
Marcon, « De la réalité au mythe », dans Yannick Pelletier (dir.), Louis Guilloux, op. cit ., p. (...) 35 Le Réveil des Côtes-du-Nord , n° 18, 1 er mars 1908. ... Marcon, « De la réalité au mythe », dans Yannick Pelletier (dir.), Louis Guilloux, op. cit ., p. 49-56. 35 Le Réveil des Côtes-du-Nord , n° 18, 1 er mars 1908. ...doi:10.4000/chrhc.2377 fatcat:52zibg225ram7pqhqq7xxyvx5u
étrangers de haut niveau et les aide à évoluer dans un milieu multiculturel. www.hec.fr www.polytechnique.fr www.fondation.renault.com UNE ENTREPRISE FRANÇAISE SUR 5 EST À REPRENDRE, AVANT 5 ANS André Marcon ... Xavier Michel, Directeur Général de l'Ecole Polytechnique, Bernard Ramanantsoa, Directeur Général du Groupe HEC, et Jean-Bernard Lartigue, Délégué Général de la Fondation de Polytechnique, en présence de Yannick ...doi:10.3917/rsg.228.0057 fatcat:mbs3ukzfmfdr3drqv6luho4wry
., 16586 Marchand, André, 5114, 7935, 23281 Marchand, David, 18500 Marchand, Nadége, 19103 Marchand, Yannick, 16747 Marchand-Martella, Nancy, 26897 Marchant, Barrie K., 22513 Marchant, Daryl, 17915 Marchant ... M., 18770 Marco, Eva M., 9953, 18739 Marcoen, Alfons, 2457, 31263 Marcolin, Barbara L., 9232 Marcomini, Monique, 9929 Marcon, Gabriella, 23267 Marcopulos, Bernice A., 18094, 34389 Marcos, T., 19984 Marcotte ...
Chefs such as Eric Fréchon, Guy Savoy, Bernard Pacaud or Régis Marcon are representative of Class 2. ... Chefs such as Gilles Goujon, Yannick Alléno, Arnaud Lallement and Alain Passard are representative of this class. ...doi:10.1108/ijchm-07-2021-0851 fatcat:gnwbnkepwvbnlmhavfxolmqqci
Marchi, Michela Malmgren-Hansen, David Marciniak, Michael Malone, Andrew Marciotto, Edson Roberto Malone, Brendan Marco, Falocchi Malone, David Marcolin, Enrico Maltezos, Evangelos Marcon, Caroline ... Ellenburg, Lee Ducke, Benjamin Ellenson, Ashley Dudczyk, Janusz Elliot, Thomas Duguay, Yannick Elmahdy, Samy Duine, Gert-Jan Elmes, Arthur Duma, Virgil-Florin Elmi, Omid Dumić, Emil El-Rawy ...doi:10.3390/rs13030449 fatcat:5jvlro5ylvddfmjxanwajk3fnu
We also thank Yannick Marcon, Chao Pang, Eric Johnson, Federico Fabbri, Daniela Fecht, D2K team and ESCAPE project for their contributions to this work. 1.020 (0.977 to 1.065) *reference category; #: number ...doi:10.1183/13993003.02127-2015 pmid:27824608 fatcat:3pxmjw3jajh4fjpsqfgcj55u5q
Acknowledgements We thank our collaborators in BioSHaRE, Maelstrom Research and OBiBa (most notably Yannick Marcon, Vincent Ferreti), the contributing biobanks (LifeLines, Prevend and Mitchelstown), our ...doi:10.1093/bioinformatics/btw155 pmid:27153686 pmcid:PMC4937195 fatcat:6viasbcnrfh3haoih4lhocngxa
., 2015; Marcon et al., 2014; Sardiu et al., 2008; Sowa et al., 2009; Van Leene et al., 2010) , there is a need to keep improving these methods in order to reduce perturbations in the stoichiometry of ...doi:10.1016/j.celrep.2015.09.009 pmid:26456817 fatcat:khxrbpnpgvbs3efxy6nabuz2ga
« Previous Showing results 1 — 15 out of 32 results