Facilitating and Improving Environmental Research Data Repository Interoperability

Environmental research data repositories provide much needed services for data preservation and data dissemination to diverse communities with domain specific or programmatic data needs and standards. Due to independent development these repositories serve their communities well, but were developed with different technologies, data models and using different ontologies. Hence, the effectiveness and efficiency of these services can be vastly improved if repositories work together adhering to a shared community platform that focuses on the implementation of agreed upon standards and best practices for curation and dissemination of data. Such a community platform drives forward the convergence of technologies and practices that will advance cross-domain interoperability. It will also facilitate contributions from investigators through standardized and streamlined workflows and provide increased visibility for the role of data managers and the curation services provided by data repositories, beyond preservation infrastructure. Ten specific suggestions for such standardizations are outlined without any suggestions for priority or technical implementation. Although the recommendations are for repositories to implement, they have been chosen specifically with the data provider/data curator and synthesis scientist in mind

ecocomDP: A flexible data design pattern for ecological community survey data

The idea of harmonizing data is not new. Decades of amassing data in databases according to community standards - both locally and globally - have been more successful for some research domains than others. It is particularly difficult to harmonize data across studies where sampling protocols vary greatly and complex environmental conditions need to be understood to apply analytical methods correctly. However, a body of longterm ecological community observations is increasingly becoming publicly available and has been used in important studies. Here, we discuss an approach to preparing harmonized community survey data by an environmental data repository, in collaboration with a national observatory. The workflow framework and repository infrastructure are used to create a decentralized, asynchronous model to reformat data without altering original data through cleaning or aggregation, while retaining metadata about sampling methods and provenance, and enabling programmatic data access. This approach does not create another data ‘silo’ but will allow the repository to contribute subsets of available data to a variety of different analysis-ready data preparation efforts. With certain limitations (e.g., changes to the sampling protocol over time), data updates and downstream processing may be completely automated. In addition to supporting reuse of community observation data by synthesis science, a goal for this harmonization and workflow effort is to contribute these datasets to the Global Biodiversity Information Facility (GBIF) to increase the data’s discovery and use

A Discussion of Value Metrics for Data Repositories in Earth and Environmental Sciences

Despite growing recognition of the importance of public data to the modern economy and to scientific progress, long-term investment in the repositories that manage and disseminate scientific data in easily accessible-ways remains elusive. Repositories are asked to demonstrate that there is a net value of their data and services to justify continued funding or attract new funding sources. Here, representatives from a number of environmental and Earth science repositories evaluate approaches for assessing the costs and benefits of publishing scientific data in their repositories, identifying various metrics that repositories typically use to report on the impact and value of their data products and services, plus additional metrics that would be useful but are not typically measured. We rated each metric by (a) the difficulty of implementation by our specific repositories and (b) its importance for value determination. As managers of environmental data repositories, we find that some of the most easily obtainable data-use metrics (such as data downloads and page views) may be less indicative of value than metrics that relate to discoverability and broader use. Other intangible but equally important metrics (e.g., laws or regulations impacted, lives saved, new proposals generated), will require considerable additional research to describe and develop, plus resources to implement at scale. As value can only be determined from the point of view of a stakeholder, it is likely that multiple sets of metrics will be needed, tailored to specific stakeholder needs. Moreover, economically based analyses or the use of specialists in the field are expensive and can happen only as resources permit

A global database of lake surface temperatures collected by in situ and satellite methods from 1985–2009

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985–2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues

Facilitating and Improving Environmental Research Data Repository Interoperability

Environmental research data repositories provide much needed services for data preservation and data dissemination to diverse communities with domain specific or programmatic data needs and standards. Due to independent development these repositories serve their communities well, but were developed with different technologies, data models and using different ontologies. Hence, the effectiveness and efficiency of these services can be vastly improved if repositories work together adhering to a shared community platform that focuses on the implementation of agreed upon standards and best practices for curation and dissemination of data. Such a community platform drives forward the convergence of technologies and practices that will advance cross-domain interoperability. It will also facilitate contributions from investigators through standardized and streamlined workflows and provide increased visibility for the role of data managers and the curation services provided by data repositories, beyond preservation infrastructure. Ten specific suggestions for such standardizations are outlined without any suggestions for priority or technical implementation. Although the recommendations are for repositories to implement, they have been chosen specifically with the data provider/data curator and synthesis scientist in mind

Long-term ecological research in a human-dominated world

Author Posting. © American Institute of Biological Sciences, 2012. This article is posted here by permission of American Institute of Biological Sciences for personal use, not for redistribution. The definitive version was published in BioScience 62 (2012): 342-253, doi:10.1525/bio.2012.62.4.6.The US Long Term Ecological Research (LTER) Network enters its fourth decade with a distinguished record of achievement in ecological science. The value of long-term observations and experiments has never been more important for testing ecological theory and for addressing today's most difficult environmental challenges. The network's potential for tackling emergent continent-scale questions such as cryosphere loss and landscape change is becoming increasingly apparent on the basis of a capacity to combine long-term observations and experimental results with new observatory-based measurements, to study socioecological systems, to advance the use of environmental cyberinfrastructure, to promote environmental science literacy, and to engage with decisionmakers in framing major directions for research. The long-term context of network science, from understanding the past to forecasting the future, provides a valuable perspective for helping to solve many of the crucial environmental problems facing society today.2012-10-0

Generating community-built tools for data sharing and analysis in environmental networks

Rapid data growth in many environmental sectors has necessitated tools to manage and analyze these data. The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network (GLEON) collaborative model supports an efficient and comprehensive data–analysis–insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks

BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL

The Tao of open science for ecology

The field of ecology is poised to take advantage of emerging technologies that facilitate the gathering, analyzing, and sharing of data, methods, and results. The concept of transparency at all stages of the research process, coupled with free and open access to data, code, and papers, constitutes “open science.” Despite the many benefits of an open approach to science, a number of barriers to entry exist that may prevent researchers from embracing openness in their own work. Here we describe several key shifts in mindset that underpin the transition to more open science. These shifts in mindset include thinking about data stewardship rather than data ownership, embracing transparency throughout the data life‐cycle and project duration, and accepting critique in public. Though foreign and perhaps frightening at first, these changes in thinking stand to benefit the field of ecology by fostering collegiality and broadening access to data and findings. We present an overview of tools and best practices that can enable these shifts in mindset at each stage of the research process, including tools to support data management planning and reproducible analyses, strategies for soliciting constructive feedback throughout the research process, and methods of broadening access to final research products

A global database of lake surface temperatures collected by in situ and satellite methods from 1985–2009

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985–2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues