Ecological data sharing

Abstract

Data sharing is the practice of making data available for use by others. Ecologists are increasingly generating and sharing an immense volume of data. Such data may serve to augment existing data collections and can be used for synthesis efforts such as meta-analysis, for parameterizing models, and for verifying research results (i.e., study reproducibility). Large volumes of ecological data may be readily available through institutions or data repositories that are the most comprehensive available and can serve as the core of ecological analysis. Ecological data are also employed outside the research context and are used for decision-making, natural resource management, education, and other purposes. Data sharing has a long history in many domains such as oceanography and the biodiversity sciences (e.g., taxonomic data and museum specimens), but has emerged relatively recently in the ecological sciences. A review of several of the large international and national ecological research programs that have emerged since the mid-1900s highlights the initial failures and more recent successes as well as the underlying causes-from a near absence of effective policies to the emergence of community and data sharing policies coupled with the development and adoption of data and metadata standards and enabling tools. Sociocultural change and the move towards more open science have evolved more rapidly over the past two decades in response to new requirements set forth by governmental organizations, publishers and professional societies. As the scientific culture has changed so has the cyberinfrastructure landscape. The introduction of community-based data repositories, data and metadata standards, software tools, persistent identifiers, and federated search and discovery have all helped promulgate data sharing. Nevertheless, there are many challenges and opportunities especially as we move towards more open science. Cyberinfrastructure challenges include a paucity of easy-to-use metadata management systems, significant difficulties in assessing data quality and provenance, and an absence of analytical and visualization approaches that facilitate data integration and harmonization. Challenges and opportunities abound in the sociocultural arena where funders, researchers, and publishers all have a stake in clarifying policies, roles and responsibilities, as well as in incentivizing data sharing. A set of best practices and examples of software tools are presented that can enable research transparency, reproducibility and new knowledge by facilitating idea generation, research planning, data management and the dissemination of data and results.

The Next Decade of Big Data in Ecosystem Science

“…Following pre-processing, validation, and quality control, data (and/or their metadata) can be archived as standalone synthetic products through a number of online repositories (for example, Ecological Archives (http://esapubs.org/archive/), Knowledge Network for Biocomplexity (KNB, https://knb.ecoinformatics.org/), and others). Although these online data products are becoming more commonplace in ecological research, the majority of the workflow is still largely developed on an individual basis, in part because the data products are individually unique (Michener and others 2012;Michener 2015). Finding and using existing datasets can be a time-consuming and error-prone process (Roche and others 2015).…”

“…Developing a more standardized and streamlined process for data science in ecology is increasingly necessary, and the DataONE platform has greatly advanced this goal (Michener and others 2012). The DataONE platform (www.dataone.org) represents an important advance in big-data cyberinfrastructure and practice in ecosystem science (Michener and others 2012;Michener 2015). This platform is an organizational nexus for discovering data from across member nodes and a resource for training in data sharing, ethics, and informatics.…”

Open, Sharable, and Extensible Data Management for the Korea National Aquatic Ecological Monitoring and Assessment Program: A RESTful API-Based Approach

“…In order to realize such potentials and opportunities fully, effective management and sharing of the ecological monitoring data is crucial [2][3][4][5][6]. However, the development of a data management system for ecological monitoring is really challenging because not only aquatic ecosystems per se but also approaches to ecological studies are very complicated and diverse.…”

“…For the last three decades, there have been active research efforts to develop data management systems for the sharing of ecological monitoring datasets [2,[16][17][18][19][20][21]. In general, there are two kinds of approaches to data sharing: metadata-level sharing and data-level sharing.…”

Technical note: Open-paleo-data implementation pilot – the PAGES 2k special issue

“…The benefit of open data for accelerating scientific discovery and safeguarding scientific integrity is widely recognized (e.g., Michener, 2015), but the procedures for making data readily available for future use are still being developed. The paleo-science community has a long history of pooling data to advance the understanding of global change.…”