V-FOR-WaTer: A Virtual Research Environment for Environmental Research

2021 ◽  
Author(s):  
Marcus Strobl ◽  
Elnaz Azmi ◽  
Sibylle K. Hassler ◽  
Mirko Mälicke ◽  
Jörg Meyer ◽  
...  
Keyword(s):  
Data Access ◽  
Environmental Data ◽  
Environmental Research ◽  
Easy Access ◽  
Web Portal ◽  
Environmental Sciences ◽  
Research Environment ◽  
Data Services ◽  
Virtual Research Environment ◽  
The Web

<p>The virtual research environment V-FOR-WaTer aims at simplifying data access for environmental sciences, fostering data publications and facilitating data analyses. By giving scientists from universities, research facilities and state offices easy access to data, appropriate pre-processing and analysis tools and workflows, we want to accelerate scientific work and facilitate the reproducibility of analyses.</p><p>The prototype of the virtual research environment consists of a database with a detailed metadata scheme that is adapted to water and terrestrial environmental data. Present datasets in the web portal originate from university projects and state offices. We are also finalising the connection of V-FOR-WaTer to GFZ Data Services, an established repository for geoscientific data. This will ease publication of data from the portal and in turn give access to datasets stored in this repository. Key to being compatible with GFZ Data Services and other systems is the compliance of the metadata scheme with international standards (INSPIRE, ISO19115).</p><p>The web portal is designed to facilitate typical workflows in environmental sciences. Map operations and filter options ensure easy selection of the data, while the workspace area provides tools for data pre-processing, scaling, and common hydrological applications. The toolbox also contains more specific tools, e.g. for geostatistics and soon for evapotranspiration. It is easily extendable and will ultimately also include user-developed tools, reflecting the current research topics and methodologies in the hydrology community. Tools are accessed through Web Processing Services (WPS) and can be joined, saved and shared as workflows, enabling more complex analyses and ensuring reproducibility of the results.</p>

scholarly journals V-FOR-WaTer – a virtual research environment to access and process environmental data

2020 ◽  
Author(s):  
Marcus Strobl ◽  
Elnaz Azmi ◽  
Sibylle K. Hassler ◽  
Mirko Mälicke ◽  
Jörg Meyer ◽  
...  
Keyword(s):  
Modular Design ◽  
Data Access ◽  
International Standards ◽  
Environmental Data ◽  
Web Portal ◽  
Environmental Sciences ◽  
Research Environment ◽  
Wide Range ◽  
Virtual Research Environment ◽  
The Web

<p>V-FOR-WaTer, as a virtual research environment, wants to simplify data access for environmental sciences, foster data publications and facilitate preparation of data and their analyses with a comprehensive toolbox. A large number of datasets, covering a wide range of spatial and temporal resolution, is still hardly accessible for others than the original data collector. Frequently these datasets are stored on local storage devices. By giving scientists from universities and state offices open access to data, appropriate pre-processing and analysis tools and workflows, we accelerate scientific work and facilitate the reproducibility of analyses.</p><p>The prototype of the virtual research environment was developed during the last three years. Today it consists of a database with a detailed metadata scheme that is adapted to water and terrestrial environmental data and compliant with international standards (INSPIRE, ISO19115). Data in the web portal originate from university projects and state offices. The connection of V-FOR-WaTer to established repositories, like the GFZ Data Services, is work in progress. This will simplify both, the process of accessing publicly available datasets and publishing the portal users’ data, which is increasingly demanded by journals and funding organisations.</p><p>The appearance of the web portal is designed to reproduce typical workflows in environmental sciences. A filter menu, based on the metadata, and a graphical selection on the map gives access to the data. A workspace area provides tools for data pre-processing, scaling, common hydrological applications and more specific tools, e.g. geostatistics. The toolbox is easily extendable due to the modular design of the system and will ultimately also include user-developed tools. The selection of the tools is based on current research topics and methodologies in the hydrology community. They are implemented as Web Processing Services (WPS); hence, the tool executions can be joined with one another and saved as workflows, enabling more complex analyses and reproducibility of the research.</p>

VirES for Aeolus - Virtual Research Environment (VRE)

2021 ◽  
Author(s):  
Daniel Santillan Pedrosa ◽  
Alexander Geiss ◽  
Isabell Krisch ◽  
Fabian Weiler ◽  
Peggy Fischer ◽  
...  
Keyword(s):  
Application Programming Interface ◽  
Data Access ◽  
Easy Access ◽  
Research Environment ◽  
Web Browser ◽  
Explorer Mission ◽  
Virtual Research Environment ◽  
Application Programming ◽  
Open Service ◽  
Programming Interface

<p><span>The VirES for Aeolus service (https://aeolus.services) has been successfully running </span><span>by EOX </span><span>since August 2018. The service </span><span>provides</span><span> easy access </span><span>and</span><span> analysis functions for the entire data archive of ESA's Aeolus Earth Explorer mission </span><span>through a web browser</span><span>.</span></p><p><span>This </span>free and open service <span>is being extended with a Virtual Research Environment (VRE). </span><span>The VRE </span><span>builds on the available data access capabilities of the service and provides </span><span>a </span><span>data access Application Programming Interface (API) a</span><span>s part of a </span><span>developing environment </span><span>i</span><span>n the cloud </span><span>using </span><span>JupyterHub and </span><span>JupyterLab</span><span> for processing and exploitation of the Aeolus data. </span>In collaboration with Aeolus DISC user requirements are being collected, implemented and validated.</p><p>Jupyter Notebook templates, an extensive set of tutorials, and documentation are being made available to enable a quick start on how to use VRE in projects. <span>The VRE is intended to support and simplify </span><span>the </span><span>work of (citizen-) scientists </span><span>interested in</span><span> Aeolus data by being able to </span><span>quickly develop processes or algorithms that can be </span><span>shar</span><span>ed or used to create </span><span>visualizations</span><span> for publications. Having a unified constant platform could potentially also be very helpful for calibration and validation activities </span><span>by </span><span>allowing easier result comparisons. </span></p>

scholarly journals Lessons Learned from the NOAA CoastWatch Ocean Satellite Course Developed for Integrating Oceanographic Satellite Data into Operational Use

2019 ◽  
Vol 8 (8) ◽  
pp. 354 ◽  
Author(s):  
Cara Wilson ◽  
Dale H. Robinson
Keyword(s):  
Satellite Data ◽  
Distribution System ◽  
Data Access ◽  
Lessons Learned ◽  
Easy Access ◽  
Financial Barriers ◽  
Data Services ◽  
Course Effectiveness ◽  
Resource Managers ◽  
Operational Activities

Satellite data are underutilized in many branches of operational oceanography. Users outside of the satellite community often encounter difficulty in discovering the types of satellite measurements that are available, and determining which satellite products are best for operational activities. In addition, the large choice of satellite data providers, each with their own data access protocols and formats, can make data access challenging. The mission of the NOAA CoastWatch Program is to make ocean satellite data easier to access and to apply to operational uses. As part of this mission, the West Coast Node of CoastWatch developed the NOAA Ocean Satellite Course, which introduces scientists and resource managers to ocean satellite products, and provides them tools to facilitate data access when using common analysis software. These tools leverage the data services provided by ERDDAP, a data distribution system designed to make data access easier via a graphical user interface and via machine-to-machine connections. The course has been offered annually since 2006 and has been attended by over 350 participants. Results of post-course surveys are analyzed to measure course effectiveness. The lessons learned from conducting these courses include using the preferred software of the course participants, providing easy access to datasets that are appropriate (fit for purpose) for operation applications, developing tools that address common tasks of the target audience, and minimizing the financial barriers to attend the course.

Bridging the gap between Big Earth data users and future (cloud-based) data systems - Towards a better understanding of user requirements of cloud-based data systems

2020 ◽  
Author(s):  
Julia Wagemann ◽  
Stephan Siemen ◽  
Jörg Bendix ◽  
Bernhard Seeger
Keyword(s):  
Data Access ◽  
Google Earth ◽  
Earth Observation ◽  
Environmental Data ◽  
User Requirements ◽  
Observation Data ◽  
Data Systems ◽  
Data Services ◽  
Study Results ◽  
The Future

<p>The European Commission’s Earth Observation programme Copernicus produces an unprecedented amount of openly available multi-dimensional environmental data. However, data ‘accessibility’ remains one of the biggest obstacles for users of open Big Earth Data and hinders full data exploitation. Data services have to evolve from pure download services to offer an easier and more on-demand data access. There are currently different concepts explored to make Big Earth Data better accessible for users, e.g. virtual research infrastructures, data cube technologies, standardised web services or cloud processing services, such as the Google Earth Engine or the Copernicus Climate Data Store Toolbox. Each offering provides different types of data, tools and functionalities. Data services are often developed solely satisfying specific user requirements and needs.</p><p>For this reason, we conducted a user requirements survey between November 2018 and June 2019 among users of Big Earth Data (including users of Earth Observation data, meteorological and environmental forecasts and other geospatial data) to better understand user requirements of Big Earth Data. To reach an active data user community for this survey, we partnered with ECMWF, which has 40 years of experience in providing data services for weather forecast data and environmental data sets of the Copernicus Programme.</p><p>We were interested in which datasets users currently use, which datasets they would like to use in the future and the reasons why they have not yet explored certain datasets. We were interested in the tools and software they use to process the data and what challenges they face in accessing and handling Big Earth Data. Another part focused on future (cloud-based) data services and there, we were interested in the users’ motivation to migrate their data processing tasks to cloud-based data services and asked them what aspects of these services they consider being important.</p><p>While preliminary results of the study were released last year, this year the final study results are presented. A specific focus will be put on users’ expectation of future (cloud-based) data services aligned with recommendations for data users and data providers alike to ensure the full exploitation of Big Earth Data in the future.</p>

scholarly journals Towards an interoperability framework for observable property terminologies

2020 ◽  
Author(s):  
Barbara Magagna ◽  
Gwenaelle Moncoiffe ◽  
Anusuriya Devaraju ◽  
Pier Luigi Buttigieg ◽  
Maria Stoica ◽  
...  
Keyword(s):  
Working Group ◽  
Design Patterns ◽  
Best Practice ◽  
Scientific Data ◽  
Environmental Data ◽  
Environmental Research ◽  
Environmental Sciences ◽  
Data Annotation ◽  
Observable Property ◽  
Research Communities

<p>In October 2019, a new working group (InteroperAble Descriptions of Observable Property Terminology or I-ADOPT WG<sup>1</sup>) officially launched its 18-month workplan under the auspices of the Research Data Alliance (RDA) co-led by ENVRI-FAIR<sup>2</sup> project members. The goal of the group is to develop a community-wide, consensus framework for representing observable properties and facilitating semantic mapping between disjoint terminologies used for data annotation. The group has been active for over two years and comprises research communities, data centers, and research infrastructures from environmental sciences. The WG members have been heavily involved in developing or applying terminologies to semantically enrich the descriptions of measured, observed, derived, or computed environmental data. They all recognize the need to enhance interoperability between their efforts through the WG’s activities.</p><p>Ongoing activities of the WG include gathering user stories from research communities (Task 1), reviewing related terminologies and current annotation practices (Task 2) and - based on this - defining and iteratively refining requirements for a community-wide semantic interoperability framework (Task 3). Much like a generic blueprint, this framework will be a basis upon which terminology developers can formulate local design patterns while at the same time remaining globally aligned. This framework will assist interoperability between machine-actionable complex property descriptions observed across the environmental sciences, including Earth, space, and biodiversity science. The WG will seek to synthesize well-adopted but still disparate approaches into global best practice recommendations for improved alignment. Furthermore, the framework will help mediate between generic observation standards (O&M<sup>3</sup>, SSNO<sup>4</sup>, SensorML<sup>5</sup>, OBOE<sup>6</sup>, ..) and current community-led terminologies and annotation practices, fostering harmonized implementations of observable property descriptions. Altogether, the WG’s work will boost the Interoperability component of the FAIR principles (especially principle I3) by encouraging convergence and by enriching the terminologies with qualified references to other resources. We envisage that this will greatly enhance the global effectiveness and scope of tools operating across terminologies. The WG will thus strengthen existing collaborations and build new connections between terminology developers and providers, disciplinary experts, and representatives of scientific data user groups. </p><p>In this presentation, we introduce the working group to the EGU community, and invite them to join our efforts. We report the methodology applied, the results from our first three tasks and the first deliverable, namely a catalog of domain-specific terminologies in use in environmental research, which will enable us to systematically compare existing resources for building the interoperability framework. </p><p><sup>1</sup>https://www.rd-alliance.org/groups/interoperable-descriptions-observable-property-terminology-wg-i-adopt-wg<br><sup>2</sup>https://envri.eu/home-envri-fair/<br><sup>3</sup>https://www.iso.org/standard/32574.html<br><sup>4</sup>https://www.w3.org/TR/vocab-ssn/<br><sup>5</sup>https://www.opengeospatial.org/standards/sensorml<br><sup>6</sup>https://github.com/NCEAS/oboe/</p>

Improving Service Management for Federated Resources to Support Virtual Research Environments

2018 ◽  
Vol 19 (2) ◽  
pp. 203-214
Author(s):  
Anastas Mishev ◽  
Sonja Filiposka ◽  
Ognjen Prnjat ◽  
Ioannis Liabotis
Keyword(s):  
Service Management ◽  
Large Body ◽  
Easy Access ◽  
Successful Implementation ◽  
Research Environment ◽  
Management Standards ◽  
Research Environments ◽  
Service Oriented ◽  
Unified View ◽  
Virtual Research Environment

Virtual research environments provide an easy access to e-Infrastructures for researchers by creating an abstracted service-oriented layer on top of the available resources. Using the portal, researchers can focus on the research workflow and data analysis while being provided with a consolidated unified view of all tools necessary for their activities. The sustainable lifecycle of a virtual research environment can only be achieved if it is going to be used with high quality of experience by a large body of users. Aiming for this goal, in this paper we analyse the requirements and implementation of a cross-community virtual research environment that brings together researchers from three different domains. Promoting interdisciplinary research and cooperation, the federated virtual research environment is based on the service orientation paradigm, offering anything as a service solutions. Thus, the main pillar for a successful implementation of this solution is the careful design and management of the underlying elementary services and service compositions. The rest of the paper discusses the challenges of the service management implementation focusing on interoperability by design and service management standards.

Converging Seismic and Geodetic Data Services

2020 ◽  
Author(s):  
Jerry A Carter ◽  
Charles Meertens ◽  
Chad Trabant ◽  
James Riley
Keyword(s):  
Interdisciplinary Research ◽  
Data Access ◽  
Geodetic Data ◽  
Easy Access ◽  
Data Types ◽  
Data Services ◽  
Use Of Data ◽  
Data Policy ◽  
Sage Data ◽  
Combined Data

<p>One of the fundamental tenets of the Incorporated Research Institutions for Seismology’s (IRIS’s) mission is to “Promote exchange of seismic and other geophysical data … through pursuing policies of free and unrestricted data access.”  UNAVCO also adheres to a data policy that promotes free and unrestricted use of data.  A major outcome of these policies has been to reduce the time that researchers spend finding, obtaining, and reformatting data.  While rapid, easy access to large archives of data has been successfully achieved in seismology, geodesy and many other distinct disciplines, integrating different data types in a converged data center that promotes interdisciplinary research remains a challenge.  This challenge will be addressed in an integrated seismological and geodetic data services facility that is being mandated by the National Science Foundation (NSF).  NSF’s Seismological Facility for the Advancement of Geoscience (SAGE), which is managed by IRIS, will be integrated with NSF’s Geodetic Facility for the Advancement of Geoscience (GAGE), which is managed by UNAVCO.  The combined data services portion of the facility, for which a prototype will be developed over the next two to three years, will host a number of different data types including seismic, GNSS, magnetotelluric, SAR, infrasonic, hydroacoustic, and many others.  Although IRIS and UNAVCO have worked closely for many years on mutually beneficial projects and have shared their experience with each other, combining the seismic and geodetic data services presents challenges to the well-functioning SAGE and GAGE data facilities that have served their respective scientific communities for more than 30 years. This presentation describes some preliminary thoughts and guiding principles to ensure that we build upon the demonstrated success of both facilities and how an integrated GAGE and SAGE data services facility might address the challenges of fostering interdisciplinary research. </p>

scholarly journals Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018)

2021 ◽  
Vol 18 (3) ◽  
pp. 1333
Author(s):  
Ahmad R. Alsaber ◽  
Jiazhu Pan ◽  
Adeeba Al-Hurban 
Keyword(s):  
Air Quality ◽  
Missing Data ◽  
Random Forest ◽  
Missing Values ◽  
Imputation Method ◽  
Environmental Data ◽  
Environmental Research ◽  
Quality Data ◽  
Data Set ◽  
Air Quality Data

In environmental research, missing data are often a challenge for statistical modeling. This paper addressed some advanced techniques to deal with missing values in a data set measuring air quality using a multiple imputation (MI) approach. MCAR, MAR, and NMAR missing data techniques are applied to the data set. Five missing data levels are considered: 5%, 10%, 20%, 30%, and 40%. The imputation method used in this paper is an iterative imputation method, missForest, which is related to the random forest approach. Air quality data sets were gathered from five monitoring stations in Kuwait, aggregated to a daily basis. Logarithm transformation was carried out for all pollutant data, in order to normalize their distributions and to minimize skewness. We found high levels of missing values for NO2 (18.4%), CO (18.5%), PM10 (57.4%), SO2 (19.0%), and O3 (18.2%) data. Climatological data (i.e., air temperature, relative humidity, wind direction, and wind speed) were used as control variables for better estimation. The results show that the MAR technique had the lowest RMSE and MAE. We conclude that MI using the missForest approach has a high level of accuracy in estimating missing values. MissForest had the lowest imputation error (RMSE and MAE) among the other imputation methods and, thus, can be considered to be appropriate for analyzing air quality data.

The Web Portal ‘meereisportal.de’ in Context of ESKP

2018 ◽  
pp. 69-72 ◽  
Author(s):  
Klaus Grosfeld ◽  
Renate Treffeisen ◽  
Jölund Asseng ◽  
Georg Heygster
Keyword(s):  
Web Portal ◽  
The Web

scholarly journals File Not Found: Rarity in an Age of Digital Plenty

2014 ◽  
Vol 15 (1) ◽  
pp. 68-74 ◽  
Author(s):  
Doug Reside
Keyword(s):  
Cultural Heritage ◽  
Good Deal ◽  
The State ◽  
Web Portal ◽  
Web Based ◽  
Rare Books ◽  
The One ◽  
The Web

In the first section of the submission guidelines for this esteemed journal, would-be authors are informed, “RBM: A Journal of Rare Books, Manuscripts, and Cultural Heritage uses a web-based, automated, submission system to track and review manuscripts. Manuscripts should be sent to the editor, […], through the web portal[…]” The multivalent uses of the word “manuscript” in this sentence reveal a good deal about the state of our field. This journal is dedicated to the study of manuscripts, and it is understood by most readers that the manuscripts being studied are of the “one-of-a-kind” variety (even rarer than the “rare . . .

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