Peatland measurements of CO 2 and CH 4 flux were obtained at scales appropriate to the in situ biological community below the tree layer to demonstrate representativeness of the spruce and peatland responses under climatic and environmental change (SPRUCE) experiment. Surface flux measurements were made using dual open-path analyzers over an area of 1.13 m 2 in daylight and dark conditions along with associated peat temperatures, water table height, hummock moisture, atmospheric pressure and incident radiation data. Observations from August 2011 through December 2014 demonstrated seasonal trends correlated with temperature as the dominant apparent driving variable. The S1-Bog for the SPRUCE study was found to be representative of temperate peatlands in terms of CO 2 and CH 4 flux. Maximum net CO 2 flux in midsummer showed similar rates of C uptake and loss: daytime surface uptake was −5 to −6 µmol m −2 s −1 and dark period loss rates were 4–5 µmol m −2 s −1 (positive values are carbon lost to the atmosphere). Maximum midsummer CH 4 -C flux ranged from 0.4 to 0.5 µmol m −2 s −1 and was a factor of 10 lower than dark CO 2 –C efflux rates. Midwinter conditions produced near-zero flux for both CO 2 and CH 4 with frozen surfaces. Integrating temperature-dependent models across annual periods showed dark CO 2 –C and CH 4 –C flux to be 894 ± 34 and 16 ± 2 gC m −2 y −1 , respectively. Net ecosystem exchange of carbon from the shrub-forb- Sphagnum -microbial community (excluding tree contributions) ranged from −3.1 gCO 2 –C m −2 y −1 in 2013, to C losses from 21 to 65 gCO 2 –C m −2 y −1 for the other years.

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE project (Spruce and Peatland Responses Under Climatic and Environmental Change, http://mnspruce.ornl.gov) is such an experiment funded by the Department of Energy's (DOE), Office of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, and the cycling and release of CO2 and CH4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. To successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are the following: 1. data acquisition and control system – set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components; 2. data collection system – set of hardware and software to deliver data to a central depository for storage and further processing; 3. data management plan – set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an efficient data system for managing high volume sources of in situ observations in a remote, harsh environmental location. The approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data.

The Next-Generation Ecosystem Experiments (NGEE Arctic) project is committed to implementing a rigorous and high-quality data management program. The goal is to implement innovative and cost-effective guidelines and tools for collecting, archiving, and sharing data within the project, the larger scientific community, and the public. The NGEE Arctic web site is the framework for implementing these data management and data sharing tools. The open sharing of NGEE Arctic data among project researchers, the broader scientific community, and the public is critical to meeting the scientific goals and objectives of the NGEE Arctic project and critical to advancing the mission of the Department of Energy (DOE), Office of Science, Biological and Environmental (BER) Terrestrial Ecosystem Science (TES) program.

Nobody is better suited to describe data than the scientist who created it. This description about a data is called Metadata. In general terms, Metadata represents the who, what, when, where, why and how of the dataset [1]. eXtensible Markup Language (XML) is the preferred output format for metadata, as it makes it portable and, more importantly, suitable for system discoverability. The newly developed ORNL Metadata Editor (OME) is a Web-based tool that allows users to create and maintain XML files containing key information, or metadata, about the research. Metadata include information about the specific projects, parameters, time periods, and locations associated with the data. Such information helps put the research findings in context. In addition, the metadata produced using OME will allow other researchers to find these data via Metadata clearinghouses like Mercury [2][4]. OME is part of ORNL s Mercury software fleet [2][3]. It was jointly developed to support projects funded by the United States Geological Survey (USGS), U.S. Department of Energy (DOE), National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA). OME s architecture provides a customizable interface to support project-specific requirements. Using this new architecture, the ORNL team developed OME instances formore » USGS s Core Science Analytics, Synthesis, and Libraries (CSAS&L), DOE s Next Generation Ecosystem Experiments (NGEE) and Atmospheric Radiation Measurement (ARM) Program, and the international Surface Ocean Carbon Dioxide ATlas (SOCAT). Researchers simply use the ORNL Metadata Editor to enter relevant metadata into a Web-based form. From the information on the form, the Metadata Editor can create an XML file on the server that the editor is installed or to the user s personal computer. Researchers can also use the ORNL Metadata Editor to modify existing XML metadata files. As an example, an NGEE Arctic scientist use OME to register their datasets to the NGEE data archive and allows the NGEE archive to publish these datasets via a data search portal (http://ngee.ornl.gov/data). These highly descriptive metadata created using OME allows the Archive to enable advanced data search options using keyword, geo-spatial, temporal and ontology filters. Similarly, ARM OME allows scientists or principal investigators (PIs) to submit their data products to the ARM data archive. How would OME help Big Data Centers like the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC)? The ORNL DAAC is one of NASA s Earth Observing System Data and Information System (EOSDIS) data centers managed by the Earth Science Data and Information System (ESDIS) Project. The ORNL DAAC archives data produced by NASA's Terrestrial Ecology Program. The DAAC provides data and information relevant to biogeochemical dynamics, ecological data, and environmental processes, critical for understanding the dynamics relating to the biological, geological, and chemical components of the Earth's environment. Typically data produced, archived and analyzed is at a scale of multiple petabytes, which makes the discoverability of the data very challenging. Without proper metadata associated with the data, it is difficult to find the data you are looking for and equally difficult to use and understand the data. OME will allow data centers like the NGEE and ORNL DAAC to produce meaningful, high quality, standards-based, descriptive information about their data products in-turn helping with the data discoverability and interoperability. Useful Links: USGS OME: http://mercury.ornl.gov/OME/ NGEE OME: http://ngee-arctic.ornl.gov/ngeemetadata/ ARM OME: http://archive2.ornl.gov/armome/ Contact: Ranjeet Devarakonda (devarakondar@ornl.gov) References: [1] Federal Geographic Data Committee. Content standard for digital geospatial metadata. Federal Geographic Data Committee, 1998. [2] Devarakonda, Ranjeet, et al. Mercury: reusable metadata management, data discovery and access system. Earth Science Informatics 3.1-2 (2010): 87-94. [3] Wilson, B. E., Palanisamy, G., Devarakonda, R., Rhyne, B. T., Lindsley, C., & Green, J. (2010). Mercury Toolset for Spatiotemporal Metadata. [4] Pouchard, L. C., Branstetter, M. L., Cook, R. B., Devarakonda, R., Green, J., Palanisamy, G., ... & Noy, N. F. (2013). A Linked Science investigation: enhancing climate change data discovery with semantic technologies. Earth science informatics, 6(3), 175-185.« less

The open sharing of data and informa1on among the NGEE Team, the broader scien1fic community, and the public is cri1cal to mee1ng the scien1fic goals of the Next- Genera1on Ecosystem Experiment (NGEE) Arc1c project. In implemen1ng the integrated approach, the project is genera1ng diverse data sets from observa1ons, experiments, and models across field plot, polygonal landform, regional, and global scales and is drawing in a wealth of exis1ng data products collected and generated by other research organiza1ons across the Arc1c. Developing the data management infrastructure to support this approach is a significant challenge. Nonetheless, the NGEE Arc1c project is commiHed to upholding a rigorous and high- quality data management strategy and the implementa1on of that strategy in an innova1ve, cost- effec1ve data collec1on, management, distribu1on, and archival framework. The NGEE Arc1c Data Portal will support the current research in Barrow and provide a consistent framework to support future research efforts as they expand to other regions.

In the recent years, there have been significant advancements in the areas of scientific data management and retrieval techniques, particularly in terms of standards and protocols for archiving data and metadata. Scientific data is rich, and spread across different places. In order to integrate these pieces together, a data archive and associated metadata should be generated. Data should be stored in a format that can be retrievable and more importantly it should be in a format that will continue to be accessible as technology changes, such as XML. While general-purpose search engines (such as Google or Bing) are useful for finding many things on the Internet, they are often of limited usefulness for locating Earth Science data relevant (for example) to a specific spatiotemporal extent. By contrast, tools that search repositories of structured metadata can locate relevant datasets with fairly high precision, but the search is limited to that particular repository. Federated searches (such as Z39.50) have been used, but can be slow and the comprehensiveness can be limited by downtime in any search partner. An alternative approach to improve comprehensiveness is for a repository to harvest metadata from other repositories, possibly with limits based on subject matter or accessmore » permissions. Searches through harvested metadata can be extremely responsive, and the search tool can be customized with semantic augmentation appropriate to the community of practice being served. One such system, Mercury, a metadata harvesting, data discovery, and access system, built for researchers to search to, share and obtain spatiotemporal data used across a range of climate and ecological sciences. Mercury is open-source toolset, backend built on Java and search capability is supported by the some popular open source search libraries such as SOLR and LUCENE. Mercury harvests the structured metadata and key data from several data providing servers around the world and builds a centralized index. The harvested files are indexed against SOLR search API consistently, so that it can render search capabilities such as simple, fielded, spatial and temporal searches across a span of projects ranging from land, atmosphere, and ocean ecology. Mercury also provides data sharing capabilities using Open Archive Initiatives Protocol for Metadata Handling (OAI-PMH). In this paper we will discuss about the best practices for archiving data and metadata, new searching techniques, efficient ways of data retrieval and information display.« less

The EPA Supersites Research Program needs consistency of metadata and data structures to facilitate information sharing among investigators, analysts, and ultimately secondary data users. Under the auspices of NARSTO a successful mechanism was created to develop and implement reporting standards. The development effort included working closely with Supersites data coordinators, investigators, and technical experts, and also leveraging from existing data standards and practices. Overall, the standards are getting good acceptance from the atmospheric research community.