Abstract
Sierra Nevada is a unique setting in which a broad and extensive research tradition converges in both time and space with intensive monitoring of the environment. Our aim is to establish a large data set together with an information network based on a powerful e-Infrastructure of communications, supercomputing, and distributed “cloud.” This e-infrastructure will be made available to the scientific community, environmental managers, and the general public. It will allow, among many other things, access to large volumes of data including biotic components (fauna and flora) as well as abiotic ones (atmospheric, terrestrial, and freshwater elements). This will allow the user to work with analytical tools in a number of virtual research environments (VREs) such as virtual laboratories for researchers, support tools for environmental managers, or social science data for the general public. To answer the questions and provide the information required by the different users of the system, we propose the creation of the following VLABs: Ecosystems, Species, and Climate. These laboratories will have a specific part (associated with their subject matter) and another transversal part that can be extended to any laboratory of the same type. Laboratories will emerge from the scientific proposal resulting from the use of e-infrastructure. The following have been identified as examples: (i) Climate: Meteorology in Sierra Nevada environment—VRE ClimaNevada; (ii) Species: Iberian ibex (Capra pyrenaica)—VRE Capra; (iii) Ecosystems: Sierra Nevada high-mountain lakes—VRE MountainLakes. All laboratories will have tools that can be structured in the following interdependent hierarchical levels: Access to data, Statistics, GIS & Artificial Intelligence, Modelling and Simulation. Currently, a multitude of initiatives around the world promote the creation and use of VREs. These are web-based, community-oriented, flexible, and secure collaborative working environments designed to meet the premises of Open Science. In the present study, we identify and analyze the main challenges to be solved (starting with the data) to fully achieve the proposed vision.
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References
Barker M, Olabarriaga SD, Wilkins-Diehr N et al (2019) The global impact of science gateways, virtual research environments and virtual laboratories. Future Gener Comput Syst 95:240–248
Carusi A, Reimer T (2010) Virtual research environment collaborative landscape study. JISC Report
Chavan V, Penev L (2011) The data paper: a mechanism to incentivize data publishing in biodiversity science. BMC Bioinform 12(S15):S2
Cook R, Lineback P (2008) Sierra nevada network data management plan
Corti L, Van den Eynden V, Bishop L, et al (2020) Managing and sharing research data: a guide to good practice (second). SAGE Publications Ltd.
Enquist CA, Jackson F, Garfin ST et al (2017) Foundations of translational ecology. Front Ecol Environ 15(10):541–550
Goodman A, Pepe A, Blocker AW et al (2014) Ten simple rules for the care and feeding of scientific data. PLoS Comput Biol 10(4):e1003542
Hampton SE, Anderson SS, Bagby SC, et al (2015) The Tao of open science for ecology. Ecosphere 6(7):art120
Jacobson SK, Morris JK, Sanders JS, et al (2006) Understanding barriers to implementation of an adaptive land management program. Conserv Biol 20(5):1516–1527. http://www.jstor.org/stable/3879143
Lawrence KA, Zentner M, Wilkins-Diehr N et al (2015) Science gateways today and tomorrow: positive perspectives of nearly 5000 members of the research community. Concurrency Comput Pract Exp 27(16):4252–4268
Meadow AM, Ferguson DB, Guido Z et al (2015) Moving toward the deliberate coproduction of climate science knowledge. Weather, Clim Soc 7(2):179–191
Michener WK (2015) Ten simple rules for creating a good data management plan. PLoS Comput Biol 11(10):e1004525
Michener WK, Jones MB (2012) Ecoinformatics: supporting ecology as a data-intensive science. Trends Ecol Evol 27(2):85–93
Peng RD (2011) Reproducible research in computational science. Science 334(6060):1226
Reichman OJ, Jones MB, Schildhauer MP (2011) Challenges and opportunities of open data in ecology. Science 331(6018):703
Rüegg J, Gries C, Bond-Lamberty B et al (2014) Completing the data life cycle: using information management in macrosystems ecology research. Front Ecol Environ 12:24–30
Sáenz AJ, Alcácer C, Rodríguez S (2017) Entornos Virtuales de Investigación para la toma de decisiones en el áambito del Medio Ambiente Urbano. WPS Review International on Sustainable Housing and Urban Renewal 1(5)
Serrano JC (2018) Repositorios públicos frente a la mercantilización de la Ciencia: apostando por la ciencia abierta y la evaluación cualitativa. MÉI: Métodos de Información 9(17):74–101. https://dialnet.unirioja.es/servlet/articulo?codigo=6840541
Spierenhurg M (2012) Getting the message across: biodiversity science and policy interfaces: a review. GAIA 21(2):125–134. http://www.ingentaconnect.com/content/oekom/gaia
Stodden V, McNutt M, Bailey DH et al (2016) Enhancing reproducibility for computational methods. Science 354(6317):1240
Vogel C, Moser SC, Kasperson RE, Dabelko GD (2007) Linking vulnerability, adaptation, and resilience science to practice: pathways, players, and partnerships. Glob Environ Change 17(3):349–364
Wilkinson MD, Dumontier M, Aalbersberg IJ et al (2016) The FAIR guiding principles for scientific data management and stewardship. Sci Data 3(1):160018
Wohner C, Peterseil J, Poursanidis D (2019) DEIMS-SDR—a web portal to document research sites and their associated data. Ecol Inform 51:15–24
Young JC, Waylen KA, Sarkki S et al (2014) Improving the science-policy dialogue to meet the challenges of biodiversity conservation: having conversations rather than talking at one-another. Biodivers Conserv 23(2):387–404
Zamora R, Pérez Luque AJ, Bonet FJ et al (2016) Global change impacts in Sierra Nevada: challenges for conservation. Consejería de Medio Ambiente y Ordenación del Territorio. Junta de Andalucía. http://hdl.handle.net/10481/5468.
Acknowledgements
This work has been carried out within the framework of the collaboration agreement between the Ministry of Environment and Territorial Planning of the Regional Government of Andalusia and the University of Granada for the implementation of activities related to the Sierra Nevada Global Change Observatory. We are also grateful for the partial support received from the LIFE-ADAPTAMED (LIFE14 CCA/ES/ 000612) projects: Protection of key ecosystem services threatened by climate change through adaptive management of Mediterranean socio-ecosystems, from the H2020 European Long-Term Ecosystem and socio-ecological Research Infrastructure (eLTER) project and from the Smart Ecomountain Lifewatch ERIC Thematic Center (LifeWatch-2019-10-UGR-01). We are grateful to the management and technical team of the Sierra Nevada Natural Area for their continued collaboration in the framework of the joint activities that we develop in the Global Change Observatory. Juan Miguel González Aranda, Antonio José Sáenz Albanés, and Antonio Pérez Luque have contributed to the development of the ideas expressed in this chapter.
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Guerrero Alonso, P.D., Merino Ceballos, M., Moreno Llorca, R., Ros Candeira, A., Zamora, R. (2022). Data Model, E-Infrastructure Services, and the Virtual Research Environment (VRE). In: Zamora, R., Oliva, M. (eds) The Landscape of the Sierra Nevada. Springer, Cham. https://doi.org/10.1007/978-3-030-94219-9_22
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