scholarly journals Fostering Open Science at WSL with the EnviDat Environmental Data Portal

2018 ◽  
Author(s):  
Ionut Iosifescu Enescu ◽  
Marielle Fraefel ◽  
Gian-Kasper Plattner ◽  
Lucia Espona-Pernas ◽  
Dominik Haas-Artho ◽  
...  
Keyword(s):  
Open Science ◽  
Research Data ◽  
Environmental Data ◽  
Data Sets ◽  
Institutional Research ◽  
Data Set ◽  
Digital Resources ◽  
Federal Institute ◽  
Data Policy ◽  
Data Portal

EnviDat is the institutional research data portal of the Swiss Federal Institute for Forest, Snow and Landscape WSL. The portal is designed to provide solutions for efficient, unified and managed access to the WSL’s comprehensive reservoir of monitoring and research data, in accordance with the WSL data policy. Through EnviDat, WSL is fostering open science, making curated, quality-controlled, publication-ready research data accessible. Data producers can document author contributions for a particular data set through the EnviDat-DataCRediT taxonomy. The publication of research data sets can be complemented with additional digital resources, such as, e.g., supplementary documentation, processing software or detailed descriptions of code (i.e. as Jupyter Notebooks). The EnviDat Team is working towards generic solutions for enhancing open science, in line with WSL’s commitment to accessible research data.

scholarly journals Fostering Open Science at WSL with the EnviDat Environmental Data Portal

2018 ◽  
Author(s):  
Ionut Iosifescu Enescu ◽  
Marielle Fraefel ◽  
Gian-Kasper Plattner ◽  
Lucia Espona-Pernas ◽  
Dominik Haas-Artho ◽  
...  
Keyword(s):  
Open Science ◽  
Research Data ◽  
Environmental Data ◽  
Data Sets ◽  
Institutional Research ◽  
Data Set ◽  
Digital Resources ◽  
Federal Institute ◽  
Data Policy ◽  
Data Portal

EnviDat is the institutional research data portal of the Swiss Federal Institute for Forest, Snow and Landscape WSL. The portal is designed to provide solutions for efficient, unified and managed access to the WSL’s comprehensive reservoir of monitoring and research data, in accordance with the WSL data policy. Through EnviDat, WSL is fostering open science, making curated, quality-controlled, publication-ready research data accessible. Data producers can document author contributions for a particular data set through the EnviDat-DataCRediT taxonomy. The publication of research data sets can be complemented with additional digital resources, such as, e.g., supplementary documentation, processing software or detailed descriptions of code (i.e. as Jupyter Notebooks). The EnviDat Team is working towards generic solutions for enhancing open science, in line with WSL’s commitment to accessible research data.

Towards a Specialized Environmental Data Portal: Challenges and Opportunities

2020 ◽  
Author(s):  
Ionut Iosifescu-Enescu ◽  
Gian-Kasper Plattner ◽  
Dominik Haas-Artho ◽  
David Hanimann ◽  
Konrad Steffen
Keyword(s):  
Data Management ◽  
Scientific Information ◽  
Central Element ◽  
Research Data ◽  
Environmental Data ◽  
Research Data Management ◽  
Environmental Domain ◽  
Federal Institute ◽  
Wide Range ◽  
Data Portal

<p>EnviDat – www.envidat.ch – is the institutional Environmental Data portal of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. Launched in 2012 as a small project to explore possible solutions for a generic WSL-wide data portal, it has since evolved into a strategic initiative at the institutional level tackling issues in the broad areas of Open Research Data and Research Data Management. EnviDat demonstrates our commitment to accessible research data in order to advance environmental science.</p><p>EnviDat actively implements the FAIR (Findability, Accessibility, Interoperability and Reusability) principles. Core EnviDat research data management services include the registration, integration and hosting of quality-controlled, publication-ready data from a wide range of terrestrial environmental systems, in order to provide unified access to WSL’s environmental monitoring and research data. The registration of research data in EnviDat results in the formal publication with permanent identifiers (EnviDat own PIDs as well as DOIs) and the assignment of appropriate citation information.</p><p>Innovative EnviDat features that contribute to the global system of modern documentation and exchange of scientific information include: (i) a DataCRediT mechanism designed for specifying data authorship (Collection, Validation, Curation, Software, Publication, Supervision), (ii) the ability to enhance published research data with additional resources, such as model codes and software, (iii) in-depth documentation of data provenance, e.g., through a dataset description as well as related publications and datasets, (iv) unambiguous and persistent identifiers for authors (ORCIDs) and, in the medium-term, (v) a decentralized “peer-review” data publication process for safeguarding the quality of available datasets in EnviDat.</p><p>More recently, the EnviDat development has been moving beyond the set of core features expected from a research data management portal with a built-in publishing repository. This evolution is driven by the diverse set of researchers’ requirements for a specialized environmental data portal that formally cuts across the five WSL research themes forest, landscape, biodiversity, natural hazards, and snow and ice, and that concerns all research units and central IT services.</p><p>Examples of such recent requirements for EnviDat include: (i) immediate access to data collected by automatic measurements stations, (ii) metadata and data visualization on charts and maps, with geoservices for large geodatasets, and (iii) progress towards linked open data (LOD) with curated vocabularies and semantics for the environmental domain.</p><p>There are many challenges associated with the developments mentioned above. However, they also represent opportunities for further improving the exchange of scientific information in the environmental domain. Especially geospatial technologies have the potential to become a central element for any specialized environmental data portal, triggering the convergence between publishing repositories and geoportals. Ultimately, these new requirements demonstrate the raised expectations that institutions and researchers have towards the future capabilities of research data portals and repositories in the environmental domain. With EnviDat, we are ready to take up these challenges over the years to come.</p>

scholarly journals The reproducibility challenge – what researchers need

2017 ◽  
Author(s):  
Federica Rosetta
Keyword(s):  
Scientific Discovery ◽  
Open Data ◽  
Science Research ◽  
Open Science ◽  
Research Data ◽  
Data Sets ◽  
Scientific Practices ◽  
Data Citation ◽  
Materials Used ◽  
High Level

Watch the VIDEO here.Within the Open Science discussions, the current call for “reproducibility” comes from the raising awareness that results as presented in research papers are not as easily reproducible as expected, or even contradicted those original results in some reproduction efforts. In this context, transparency and openness are seen as key components to facilitate good scientific practices, as well as scientific discovery. As a result, many funding agencies now require the deposit of research data sets, institutions improve the training on the application of statistical methods, and journals begin to mandate a high level of detail on the methods and materials used. How can researchers be supported and encouraged to provide that level of transparency? An important component is the underlying research data, which is currently often only partly available within the article. At Elsevier we have therefore been working on journal data guidelines which clearly explain to researchers when and how they are expected to make their research data available. Simultaneously, we have also developed the corresponding infrastructure to make it as easy as possible for researchers to share their data in a way that is appropriate in their field. To ensure researchers get credit for the work they do on managing and sharing data, all our journals support data citation in line with the FORCE11 data citation principles – a key step in the direction of ensuring that we address the lack of credits and incentives which emerged from the Open Data analysis (Open Data - the Researcher Perspective https://www.elsevier.com/about/open-science/research-data/open-data-report ) recently carried out by Elsevier together with CWTS. Finally, the presentation will also touch upon a number of initiatives to ensure the reproducibility of software, protocols and methods. With STAR methods, for instance, methods are submitted in a Structured, Transparent, Accessible Reporting format; this approach promotes rigor and robustness, and makes reporting easier for the author and replication easier for the reader.

Sharing Open Data in Agriculture

2021 ◽  
pp. 244-266
Author(s):  
Liah Shonhe
Keyword(s):  
Agricultural Sector ◽  
Open Data ◽  
Research Data ◽  
Data Sets ◽  
Research Activity ◽  
African Countries ◽  
Data Set ◽  
Data Repositories ◽  
Bibliographic Data ◽  
Prolific Authors

The main focus of the study was to explore the practices of open data sharing in the agricultural sector, including establishing the research outputs concerning open data in agriculture. The study adopted a desktop research methodology based on literature review and bibliographic data from WoS database. Bibliometric indicators discussed include yearly productivity, most prolific authors, and enhanced countries. Study findings revealed that research activity in the field of agriculture and open access is very low. There were 36 OA articles and only 6 publications had an open data badge. Most researchers do not yet embrace the need to openly publish their data set despite the availability of numerous open data repositories. Unfortunately, most African countries are still lagging behind in management of agricultural open data. The study therefore recommends that researchers should publish their research data sets as OA. African countries need to put more efforts in establishing open data repositories and implementing the necessary policies to facilitate OA.

scholarly journals OPEN SCIENCE, KNOWLEDGE SHARING AND REPRODUCIBILITY AS DRIVERS FOR THE ADOPTION OF FOSS4G IN ENVIRONMENTAL RESEARCH

2019 ◽  
Vol XLII-4/W14 ◽  
pp. 107-110
Author(s):  
I. Iosifescu Enescu ◽  
G-K. Plattner ◽  
L. Bont ◽  
M. Fraefel ◽  
R. Meile ◽  
...  
Keyword(s):  
Knowledge Sharing ◽  
Open Source ◽  
Open Source Software ◽  
Academic Research ◽  
Open Science ◽  
Environmental Data ◽  
Environmental Research ◽  
Data Repository ◽  
User Requirement ◽  
Data Portal

<p><strong>Abstract.</strong> Support for open science is a highly relevant user requirement for the environmental data portal EnviDat. EnviDat, the institutional data portal and publication data repository of the Swiss Federal Research Institute WSL, actively implements the FAIR (Findability, Accessibility, Interoperability and Reusability) principles and provides a range of services in the area of research data management. Open science, with its requirements for improved knowledge sharing and reproducibility, is driving the adoption of free and open source software for geospatial (FOSS4G) in academic research. Open source software can play a key role in the proper documentation of data sets, processes and methodologies, because it supports the transparency of methods and the precise documentation of all steps needed to achieve the published results. EnviDat actively supports these activities to enhance its support for open science. With EnviDat, WSL contributes to the ongoing cultural evolution in research towards open science and opportunities for distant collaboration.</p>

scholarly journals Ein Instrument zur Schätzung von Holzernteproduktivitäten mittels der kNN-Methode

2012 ◽  
Vol 163 (4) ◽  
pp. 119-129
Author(s):  
Fabian Kostadinov ◽  
Renato Lemm ◽  
Oliver Thees
Keyword(s):  
Software Tool ◽  
Estimation Accuracy ◽  
Data Sets ◽  
Data Set ◽  
Wood Harvesting ◽  
Federal Institute ◽  
Nearest Neighbours ◽  
Order Of Magnitude ◽  
Landscape Research ◽  
Cable Crane

A software tool for the estimation of wood harvesting productivity using the kNN method For operational planning and management of wood harvests it is important to have access to reliable information on time consumption and costs. To estimate these efficiently and reliably, appropriate methods and calculation tools are needed. The present article investigates whether use of the method of the k nearest neighbours (kNN) is appropriate in this case. The kNN algorithm is first explained, then is applied to two sets of data “combined cable crane and processor” and “skidder”, both containing wood harvesting figures, and thus the estimation accuracy of the method is determined. It is shown that the kNN method's estimation accuracy lies within the same order of magnitude as that of a multiple linear regression. Advantages of the kNN method are that it is easy to understand and to visualize, together with the fact that estimation models do not become out of date, since new data sets can be constantly taken into account. The kNN Workbook has been developed by the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). It is a software tool with which any data set can be analysed in practice using the kNN method. This tool is also presented in the article.

PEP725 a European phenological database

2021 ◽  
Author(s):  
Hans Ressl ◽  
Helfried Scheifinger ◽  
Thomas Hübner ◽  
Anita Paul ◽  
Markus Ungersböck
Keyword(s):  
Data Base ◽  
Science Research ◽  
Data Access ◽  
Data Sets ◽  
Ministry Of Education ◽  
Data Set ◽  
Phenological Data ◽  
Data Policy ◽  
Research And Education ◽  
Education Science

&lt;p&gt;&amp;#8220;Phenology &amp;#8211; the timing of seasonal activities of animals and plants &amp;#8211; is perhaps the simplest process in which to track changes in the ecology of species in response to climate change&amp;#8221; (IPCC 2007).&lt;/p&gt;&lt;p&gt;PEP725, the Pan-European Phenological Database, is a European research infrastructure to promote and facilitate phenological research. Its main objective is to build up and maintain a European-wide phenological database with an open, unrestricted data access for science, research and education. So far, 20 European meteorological services and 6 partners from different phenological network operators have joined PEP725.&lt;/p&gt;&lt;p&gt;The PEP725 phenological data base (www.pep725.eu) now offers more than 12 million phenological observations, all of them classified according to the so called BBCH scale. The first datasets in PEP725 date back to 1868; however, there are only a few observations available until 1950. Having accepted the PEP725 data policy and finished the registration, the data download is quick and easy and can be done according to various criteria, e.g., by a specific plant or all data from one country. The integration of new data sets for future partners is also easy to perform due to the flexible structure of the PEP725 database as well as the classification of the observed plants via the so-called gss format (genus, species and subspecies).&lt;/p&gt;&lt;p&gt;PEP725 is funded by EUMETNET, the network of European meteorological services, ZAMG, who is the acting host for PEP, and the Austrian ministry of education, science and research.&lt;/p&gt;&lt;p&gt;The phenological data set has been growing by about 100000 observations per year. Also the number of user registrations has continually been increasing, amounting to 305 new users and more than 28000 downloads in 2020. The greatest number of users are found in China, followed by Germany and the US. To date we could count 78 reviewed publications based on the PEP725 data set with 18 in 2020 and a total of 9 published in Nature and one in Science.&lt;/p&gt;&lt;p&gt;The data base statistics demonstrate the great demand and potential of the PEP725 phenological data set, which urgently needs development including a facilitated access, gridded versions and near real time products to attract a greater range of users.&lt;/p&gt;

Representing High-Dimensional Data Sets as Closed Surfaces

2002 ◽  
Vol 1 (2) ◽  
pp. 111-119 ◽  
Author(s):  
Archana Sangole ◽  
George K. Knopf
Keyword(s):  
Data Visualization ◽  
Visual Cues ◽  
Geometric Model ◽  
Scientific Data ◽  
Environmental Data ◽  
Surface Model ◽  
Data Sets ◽  
Surface Geometry ◽  
Data Set ◽  
Self Organizing

Scientific data visualization provides scientists and engineers with a deeper insight and greater understanding about physical phenomena through the use of graphical tools. Individuals are able to identify patterns embedded in data sets using visual cues such as color and shape, rather than directly searching through a vast volume of numbers. The visualization algorithm described in this paper utilizes a spherical self-organizing feature map (SOFM) to automatically cluster and develop a well-defined topology of arbitrary data vectors, based on a pre-defined measure of similarity, and generate a three-dimensional color-coded surface model that reflects cluster variations. Implementation of this self-organizing surface geometry for data visualization applications is illustrated by examining the graphical forms created for a small synthetic test data set and a large environmental data-base. The proposed methodology provides the researcher with a new tool to encode information into shape and easily transfer the geometric model to an immersive virtual reality (IVR) environment for interactive information analysis.

scholarly journals Zonal-mean data set of global atmospheric reanalyses on pressure levels

2018 ◽  
Author(s):  
Patrick Martineau ◽  
Jonathon S. Wright ◽  
Nuanliang Zhu ◽  
Masatomo Fujiwara
Keyword(s):  
Three Dimensional ◽  
Short Wave ◽  
Reanalysis Data ◽  
Environmental Data ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Intercomparison Project ◽  
Complete Set ◽  
Transformed Eulerian Mean

Abstract. This data set, which is prepared for the SPARC-Reanalysis Intercomparison Project (S-RIP), provides several zonal-mean diagnostics computed from reanalysis data on pressure levels. Diagnostics are currently provided for a variety of reanalyses, including ERA-40, ERA-Interim, ERA-20C, NCEP-NCAR, NCEP-DOE, CFSR, 20CR v2 and v2c, JRA-25, JRA-55, JRA-55C, JRA-55AMIP, MERRA, and MERRA-2. The data set will be expanded to include additional reanalyses as they become available. Basic dynamical variables (such as temperature, geopotential height and three-dimensional winds) are provided in addition to a complete set of terms from the Eulerian-mean and transformed Eulerian-mean momentum equations. Total diabatic heating and its long-wave and short-wave components are included as availability permits, along with heating rates diagnosed from the basic dynamical variables using the zonal-mean thermodynamic equation. Two versions of the data set are provided, one that uses horizontal and vertical grids provided by the various reanalysis centers, and another that uses a common grid to facilitate comparison among data sets. For the common grid, all diagnostics are interpolated horizontally onto a regular 2.5° ×2.5° grid for a subset of pressure levels that are common amongst all included reanalyses. The dynamical (Martineau, 2017, http://dx.doi.org/10.5285/b241a7f536a244749662360bd7839312) and diabatic (Wright, 2017, http://dx.doi.org/10.5285/70146c789eda4296a3c3ab6706931d56) variables are archived and maintained by the Centre for Environmental Data Analysis (CEDA).

Improved FAIR Data Publication Quality in Specialized Environmental Data Portals

2021 ◽  
Author(s):  
Ionut Iosifescu Enescu ◽  
Gian-Kasper Plattner ◽  
Lucia Espona Pernas ◽  
Dominik Haas-Artho ◽  
Rebecca Buchholz
Keyword(s):  
Scientific Information ◽  
Open Science ◽  
Research Data ◽  
Environmental Data ◽  
Environmental Research ◽  
Data Publishing ◽  
Data Provenance ◽  
Publication Process ◽  
Data Publication ◽  
Metadata Record

&lt;p&gt;Environmental research data from the Swiss Federal Research Institute WSL, an Institute of the ETH Domain, is published through the environmental data portal EnviDat (https://www.envidat.ch). EnviDat actively implements the FAIR (Findability, Accessibility, Interoperability and Reusability) principles and offers guidance and support to researchers throughout the research data publication process.&lt;/p&gt;&lt;p&gt;WSL strives to increase the fraction of environmental data easily available for reuse in the public domain. At the same time, WSL facilitates the publication of high-quality environmental research datasets by providing an appropriate infrastructure, a formal publication process and by assigning Document Object Identifiers (DOIs) and appropriate citation information.&lt;/p&gt;&lt;p&gt;Within EnviDat, we conceptualize and implement data publishing workflows that include automatic validation, interactive quality checks, and iterative improvement of metadata quality. The data publication workflow encompasses a number of steps, starting from the request for a DOI, to an approval process with a double-checking principle, and the submission of the metadata-record to DataCite for the final data publication. This workflow can be viewed as a decentralized peer-review and quality improvement process for safeguarding the quality of published environmental datasets. The workflow is being further developed and refined together with partner institutions within the ETH Domain.&lt;/p&gt;&lt;p&gt;We have defined and implemented additional features in EnviDat, such as (i) in-depth tracing of data provenance through related datasets; (ii) the ability to augment published research data with additional resources which support open science such as model codes and software; and (iii) a DataCRediT mechanism designed for specifying data authorship (Collection, Validation, Curation, Software, Publication, Supervision).&lt;/p&gt;&lt;p&gt;We foresee that these developments will help to further improve approaches targeted at modern documentation and exchange of scientific information. This is timely given the increasing expectations that institutions and researchers have towards capabilities of research data portals and repositories in the environmental domain.&lt;/p&gt;

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