Data Management and Sharing for Collaborative Science: Lessons Learnt From the Euromammals Initiative

Abstract

The current and future consequences of anthropogenic impacts such as climate change and habitat loss on ecosystems will be better understood and therefore addressed if diverse ecological data from multiple environmental contexts are more effectively shared. Re-use requires that data are readily available to the scientific scrutiny of the research community. A number of repositories to store shared data have emerged in different ecological domains and developments are underway to define common data and metadata standards. Nevertheless, the goal is far from being achieved and many challenges still need to be addressed. The definition of best practices for data sharing and re-use can benefit from the experience accumulated by pilot collaborative projects. The Euromammals bottom-up initiative has pioneered collaborative science in spatial animal ecology since 2007. It involves more than 150 institutes to address scientific, management and conservation questions regarding terrestrial mammal species in Europe using data stored in a shared database. In this manuscript we present some key lessons that we have learnt from the process of making shared data and knowledge accessible to researchers and we stress the importance of data management for data quality assurance. We suggest putting in place a pro-active data review before data are made available in shared repositories via robust technical support and users’ training in data management and standards. We recommend pursuing the definition of common data collection protocols, data and metadata standards, and shared vocabularies with direct involvement of the community to boost their implementation. We stress the importance of knowledge sharing, in addition to data sharing. We show the crucial relevance of collaborative networking with pro-active involvement of data providers in all stages of the scientific process. Our main message is that for data-sharing collaborative efforts to obtain substantial and durable scientific returns, the goals should not only consist in the creation of e-infrastructures and software tools but primarily in the establishment of a network and community trust. This requires moderate investment, but over long-term horizons.

Prerequisites for coexistence: human pressure and refuge habitat availability shape continental-scale habitat use patterns of a large carnivore

“…Combining tracking datasets collected across several Eurasian lynx populations at a continental scale allowed us to provide new insights into how lynx adjust their habitat use in response to human pressure and refuge habitat availability. Such 'big' tracking datasets, enabled by large-scale collaborations and initiatives for harmonizing and sharing tracking datasets (Kranstauber et al 2011;Urbano et al 2021) are particularly valuable for large carnivore research as they allow understanding the adaptive capacity of species under different environment contexts and overcome the often small sample sizes of local studies, thereby providing important information to transboundary conservation efforts needed to safeguard many large carnivores (Thompson et al 2021). Methodologically, our analysis demonstrates that using functional response models offers a simple, yet effective approach for understanding how the availability of multiple factors interactively shape patterns of wildlife habitat use.…”

“…1). Prior to all analyses, tracking datasets were harmonized through a standardized procedure of quality checks (Urbano et al 2021).…”

“…Understanding how large carnivore habitat use varies across gradients of human pressures and different landscape compositions requires datasets spanning multiple populations. While such datasets have traditionally been missing, the ongoing proliferation of animal tracking data, along with efforts to share and integrate datasets in harmonized databases through the establishment of collaborative networks opens new opportunities in this regard (Urbano et al 2021;Thompson et al 2021). Methodologically, such analyses require disentangling how habitat use varies in response to changes in multiple variables simultaneously (e.g., human pressure and refuge habitat availability).…”

(Almost) all the humpback whales of the North Pacific: A collaborative and comprehensive photo-ID dataset

“…An ideal collaboration builds datasets that directly answer present biological and management questions and simultaneously creates data sharing readiness. Data readiness for study of ecological change depends on both standardized repositories and aligned research interests 17,57,58 . The NPPID dataset has been successfully applied in this context, contributing to challenging management issues such as, for example, the US West Coast Dungeness crab shery.…”

CEBA: A Data Lake for Data Sharing and Environmental Monitoring

“…It draws the importance of standards in data and metadata, for example in ecology [ 4 ] without being completely defined yet. In this domain, even if a number of repositories to store shared data have been created and on going developments are trying to define common data and metadata standards [ 5 ], existing data are not exposed in a standard, machine-readable format using a common vocabulary. Common to all fields, this problem has for example been addressed by the biodiversity community with the creation of the Darwin Core [ 3 ].…”