Living Norway Ecological Data Network – Status and vision
Open science and open data is providing some new challenges but also opportunities for applied ecologists that are unprecedented in the history of science. Living Norway Ecological Data Network has a core mission to promote open data based on the FAIR guiding principles, but also engage with and work for an open scientific culture across the ecological and related sciences. Although Living Norway Ecological Data Network is – as the name implies – based in Norway, the ideas, data, tools and workflows we share and develop are open and universal. In this opening talk, the main vision, activities and motivation behind our project will be presented, and we will argue why we believe building a strong culture for open data and open science in general is needed to successfully increase the societal impact of applied ecological research in the years and decades ahead of us.
Recent paperNilsen, E. B., Bowler, D. E. & Linnell, J. D. C. (2020). Exploratory and confirmatory research in the open science era. Journal of Applied Ecology, 57, 8423-847
The why, how and when to use data standards in ecology
The current focus on global challenges along with advances in analytical methods have provided an increasing imperative for sharing and integration of ecological data. Furthermore, recent progress in biodiversity informatics and associated infrastructures have made this possible. However, while global biodiversity data discovery platforms such as GBIF currently make available over 1 billion data records, these usually only contain information on occurrence of a given taxon in space and time.
Comparable few datasets containing richer information on for example sampling scope and effort, needed for many types of ecological inference, are currently available. This is not due to lack of standards and infrastructure per se. Complex data-structures, such as hierarchical nested designs, can be documented, shared and integrated using current standards and protocols such as Darwin Core with extentions. However, clear guidelines and a community embrace of such is lacking. There is a need for a common set of minimum standards for information content shared from various types of data collection protocols across taxonons and ecosystems.
The status of the “reproducibility crisis” in the wildlife sciences
We evaluated computational reproducibility in randomly selected studies published in the two main North American wildlife journals, the Wildlife Society Bulletin and the Journal of Wildlife Management. Challenges to reproducibility mostly arose from obtaining and processing raw data.
Our results highlight the need for increased awareness and transparency throughout the entire data analysis and publication process.
Recent paperArchMiller, A, Nolan J, Johnson A, Edwards M, Elliot L, Ferguson J, Iannarilli F, Velez J, Vitense K, Johnson D, Fieberg J. 2020. Computational reproducibility in The Wildlife Society’s flagship journals. The Journal of Wildlife Management.
IPBES goes FAIR! Lessons Learned and the Way Foreward
IPBES, [the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services] (https://ipbes.net) has the overall mission “to strengthen the science-policy interface for biodiversity and ecosystem services for the conservation and sustainable use of biodiversity, long-term human well-being and sustainable development”.
In this capacity, IPBES is integrating existing data and knowledge and provides assessments on topics it is mandated to by the member governments. Based on these assessments, Summaries for Policy Makers are produced, which are the documents used for policy support. This whole process does not involve the generation of new data. So why does an organisation like this need a Data Management Policy? Which lessons did we learn from developing this DM Policy? And are there areas, in which a DM Policy by an orginisation like IPBES should develop, in contrast to other data generating organisations? I will discuss these issues, provide some answers, but will leave many questions open for discussion, as not much existing experiences in this area is available.
Recent paperIPBES Data Management Policy. Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Krug, Rainer M. University of Zurich; Aboki Omare, Benedict D.; Niamir, Aidin
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LivingNorwayR – an R package for facilitating the sharing of complex ecological data using the Darwin Core Standard (DwC)
I will outline some of the core functions of the R package (e.g. importing and interacting with a DwC; exporting raw data to DwC with associated metadata etc.) as well as discuss some of the future developments that we envisage.
Recent paperGrainger, Matthew J, Bolam, Friederike C., Stewart, Gavin B. & Nilsen, Erlend B. Evidence synthesis for tackling Research Waste. Nature Ecology Evolution 2020
How can a consistent vocabulary of ecological data types facilitate FAIR data management?
Many data custodians may be held back from publishing their data by a lack of awareness of existing infrastructures for disseminating data from heterogeneous sources in a harmonized manner. One factor contributing to this limitation is the lack of commonly agreed upon vocabulary for heterogeneous data types, which makes data difficult to standardize, index, and search for. Here we present a consistent vocabulary that can be used to describe data that is heterogeneous across multiple axes.
Open Science in general
This will be an introduction to Open Science: what is it, what is the vision and why is this relevant for you as a researcher? The talk gives an overview over some of the most important terms, initiatives and guidelines, as well as some examples of Open Science in practice and how academic libraries work to support Open Science.
Global Biodiversity Information Facility (GBIF)
A recent review report by CODATA (2020) describes GBIF as “the most comprehensive, openly available, application-agnostic (most unbiased), easiest-to-use, and modern access point to known digital species occurrence data”. GBIF is an international network and research infrastructure funded by the world’s governments and aimed at providing anyone, anywhere, open access to data about all types of life on Earth.
With an original mandate (set by OECD in 1999) of facilitating open access to natural history museum specimen catalogues and to aggregate lists of the known and named species, or taxa, the scope of GBIF is expanding to cover all types of georeferenced species occurrence information, including citizen science observations, biodiversity survey data, private sector data, and occurrences based on genetic sequence data from environment DNA samples, to name just a few. GBIF is working with networks such as Living Norway to ensure that data exchange models and services are fit for scientific use by a broader seat of communities. Living Norway Ecological Data Network is a part of the national Participant Node in GBIF and contributes to the global GBIF community in many ways, including in particular on the development of new data models for ecological datasets around the Darwin Core sampling event standard to increase the utility of GBIF not only in Norway, but also on the global scene. Through research infrastructures such as Living Norway, the member countries of GBIF, such as Norway, ripe the benefits of their long-term national investments in establishing and operating this global research infrastructure.
ReferenceCODATA, the Committee on Data of the International Science Council, Pfeiffenberger H & Uhlir P (2020). Twenty-Year Review of GBIF.
How can journals support open data in ecology?
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From bad science and science fiction to Evidence-based X: How we can fix the world with evidence synthesis
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