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Inferring causation from time series in Earth system sciences

2019, Runge, Jakob, Bathiany, Sebastian, Bollt, Erik, Camps-Valls, Gustau, Coumou, Dim, Deyle, Ethan, Glymour, Clark, Kretschmer, Marlene, Mahecha, Miguel D., Muñoz-Marí, Jordi, van Nes, Egbert H., Peters, Jonas, Quax, Rick, Reichstein, Markus, Scheffer, Marten, Schölkopf, Bernhard, Spirtes, Peter, Sugihara, George, Sun, Jie, Zhang, Kun, Zscheischler, Jakob

The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted correlation techniques. Here, we give an overview of causal inference frameworks and identify promising generic application cases common in Earth system sciences and beyond. We discuss challenges and initiate the benchmark platform causeme.net to close the gap between method users and developers. © 2019, The Author(s).

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Three Rs for Re-Use in Digital Preservation

2020-02-05, Lindlar, Michelle

This presentation was given at the " Hergebruik / Re-use Seminar " held for and by Barbara Sierman at the KB Netherlands on February 5th, 2020. 4 speakers were given the topic "Re-Use", asking for their take on the subject. This presentations highlights how three attributes are closely connected / describe re-use: research-based, reproducible, responsible. It is shown how they connect to re-use and digital preservation and where the digital preservation community has room for improvement.

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Data Sharing Under the General Data Protection Regulation: Time to Harmonize Law and Research Ethics?

2021, Vlahou, Antonia, Hallinan, Dara, Apweiler, Rolf, Argiles, Angel, Beige, Joachim, Benigni, Ariela, Bischoff, Rainer, Black, Peter C., Boehm, Franziska, Ceraline, Jocelyn, Chrousos, George P., Delles, Christian, Evenepoel, Pieter, Fridolin, Ivo, Glorieux, Griet, van Gool, Alain J., Heidegger, Isabel, Ioannidis, John P. A., Jankowski, Joachim, Jankowski, Vera, Jeronimo, Carmen, Kamat, Ashish M., Masereeuw, Rosalinde, Mayer, Gert, Mischak, Harald, Ortiz, Alberto, Remuzzi, Giuseppe, Rossing, Peter, Schanstra, Joost P., Schmitz-Draeger, Bernd J., Spasovski, Goce, Staessen, Jan A., Stamatialis, Dimitrios, Stenvinkel, Peter, Wanner, Christoph, Williams, Stephen B., Zannad, Faiez, Zoccali, Carmine, Vanholder, Raymond

The General Data Protection Regulation (GDPR) became binding law in the European Union Member States in 2018, as a step toward harmonizing personal data protection legislation in the European Union. The Regulation governs almost all types of personal data processing, hence, also, those pertaining to biomedical research. The purpose of this article is to highlight the main practical issues related to data and biological sample sharing that biomedical researchers face regularly, and to specify how these are addressed in the context of GDPR, after consulting with ethics/legal experts. We identify areas in which clarifications of the GDPR are needed, particularly those related to consent requirements by study participants. Amendments should target the following: (1) restricting exceptions based on national laws and increasing harmonization, (2) confirming the concept of broad consent, and (3) defining a roadmap for secondary use of data. These changes will be achieved by acknowledged learned societies in the field taking the lead in preparing a document giving guidance for the optimal interpretation of the GDPR, which will be finalized following a period of commenting by a broad multistakeholder audience. In parallel, promoting engagement and education of the public in the relevant issues (such as different consent types or residual risk for re-identification), on both local/national and international levels, is considered critical for advancement. We hope that this article will open this broad discussion involving all major stakeholders, toward optimizing the GDPR and allowing a harmonized transnational research approach.

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NCIO 1.0: A simple Fortran NetCDF interface

2015, Robinson, A., Perrette, M.

The NetCDF (Network Common Data Form) library has become an indispensable tool for data and model output management in geoscience. However for simple tasks, particularly in Fortran, the complexity of native NetCDF functionality can be cumbersome. The NCIO (NetCDF Input/Output) module has been designed as an interface to the NetCDF library with simplicity and ease of use in mind. While this implies that some NetCDF functionality is masked from the user, the subroutines provided here are adequate for basic serial reading and writing tasks of up to 6-D data arrays along with corresponding data attributes. The code is available online via a GitHub repository (http://www.github.com/alex-robinson/ncio), which includes an example program to illustrate the approach.