This Building Blocks project offers a unique and transformative approach to integrate existing and emerging long-tail model and data resources. The goal of this research is to develop a framework rooted in semantic techniques and approaches to support long-tail models and data integration. The vision is to develop a decentralized knowledge-based platform that can be easily adopted across geoscience communities comprising of individual and small group researchers. This project will focus on integrating two long-tail resources, the Community Surface Dynamic Modeling System (CSDMS) and Sustainable Environment Actionable Data (SEAD) as an example of closing the loop from model queries back to data sources.  In addition, the concepts and tools developed will be developed to allow automated coupling of models and data coming from different contributors.

This project lays the groundwork for the whole-earth analysis and simulation capability envisioned through EarthCube, by bringing critical zone scientists together with hands-on training to test available cyberinfrastructure tools with comprehensive multiparameter datasets spanning a wide range of scales. The project will further improve access to the products of critical zone research by promoting the sharing, standardization, synthesis and analysis of biogeochemical and metagenomic data via EarthCube cyberinfrastructure, enabling a broader array of geosciences communities to shape future EarthCube activities and outcomes. Project findings and products will be used to inform future EarthCube development through the activity of the PIs and collaborators in the EarthCube Science Committee and Technology and Architecture Committee, as well as through the broader engagement of critical zone scientists into EarthCube activities.                

The network elements of the ECOGEO Research Coordination Network reach across diverse communities of ocean scientists, geoscientists, computer scientists and bioinformaticians, and will forge new cross-disciplinary connections. Although the scientific goals of the proposed ECOGEO community network are diverse, common challenges and requirements for big data analyses are identified across this broad community. The ECOGEO RCN will establish a virtual network with a goal of coordinating communication and collaboration in omics, data sharing and analysis as well as providing cyber-training for upcoming ocean and geoscience students and young professionals. A large part of the work within ECOGEO will focus on the identification of data standards, ontologies and methods or sharing data, and development of scenarios to inspire the next generation of researchers.

The SeaView project is building connections between the rich data resources in five major oceanographic data facilities - R2R, BCO-DMO, CCHDO, OBIS and OOI* - and an ocean data visualization and exploration tool, the Ocean Data View (ODV), having over 40,000 registered users. To do so, it is leveraging from NSF investments into two previous EarthCube projects: CINERGI, as the registry where users will find and access data they wish to use, and GeoLink, which is providing interconnections between existing data resources, allowing users to explore a knowledge base of related information. SeaView leverages existing resources to provide improved tools and data access in support of fundamental research in two areas of ocean sciences: deep water hydrography and marine community-environment interactions. Both feed directly into research identified by the 2015 Decadal Survey of Ocean Sciences as of the highest priority. It will also engage scientists from currently underrepresented communities in EarthCube.

This project brings together six paleobiological databases so that they share a single set of Internet-based commands by which researchers and the public can easily access fossil records from all of Earth history. By coordinating with other emerging efforts in geological and biological data sharing, best practices, and protocols, we ensure that data will be freely available to all, enabling new scientific syntheses and discovery, more powerful educational opportunities, and general exploration of the history of life on Earth.  This project establishes a Paleobiological Data Consortium, consisting of leaders of cyberinfrastructure resources in the paleobiosciences and allied disciplines, with the goal of sharing best practices and protocols among the geoinformatic and bioinformatic communities.                

The Cloud-Hosted Real-time Data Services for the Geosciences (CHORDS), a real-time data management infrastructure will provide a system to archive, navigate and distribute real-time data streams via the Internet, and employ data and metadata formats that adhere to standards, which simplify the user experience.

This project develops the Coral Reef Science & Cyberinfrastructure Network (CReSCyNT). The coral reef community has exceptionally diverse data structures and analysis requirements necessary to forward integrative science. It is therefore an exemplar for cyberinfrastructure-enabled advances to other geosciences communities. CReSCyNT will develop a network of disciplinary and technology nodes focused on coral reef science and extending to the broader ocean and geoscience communities. The objectives of the RCN are to identify the needs, best practices and challenges facing the coral reef domain and how those might be translatable to the broader geoscience community.

This Building Blocks project will 1) significantly increase research productivity in the Earth science modeling community, 2) enable the effective use of the existing Sensor Web data and Earth Observations through open Web interfaces and metadata standards, 3) foster collaborations among Earth system modelers, geospatial information scientists, and information technologists, and 4) enhance infrastructure for Earth science research and education. CyberConnector is intended to facilitate automatic preparation and feeding of customized data and derived products into Earth science models.  This project seeks to make model creation and inter-comparison significantly easier, by starting with available data and expanding the CyberConnector infrastructure to many different Earth models.

This EarthCube conceptual design project is to develop a data-oriented and human-centric EarthCube enterprise architecture for achieving the goal of EarthCube as a community-driven activity to transform the conduct of geoscience research and education. The proposed EarthCube enterprise architecture will have geoscientists and domain experts at its center and facilitate them to communicate and collaborate through data sharing, and ultimately bring geosciences forward in a holistic fashion. This project seeks to design a conceptual architecture that can bring geoscientists, computing scientists, and social scientists together to collaborate on networks of data, technology, applications, business models, and stakeholders.

This Building Blocks project develops the Digital Crust, an online workspace that allows for the linking, access, and extraction of all data related to the Earth’s crust, with the goal of facilitating the creation of 4D data products from those linked data sets. The platform can serve as a resource to bring together geoscientists working on separate aspects of the Earth system, by bringing their data/ideas together and by providing an environment to view the Earth from different perspectives. Hosting multiple data types and sometimes conflicting interpretations and hypotheses of Earth processes will promote community discussion and debate on Earth processes that will foster interaction, collaboration, and data/idea sharing among scientists who might otherwise never have met. Digital Crust also seeks to be a resource for educators and other interested in introducing students to the Earth sciences, and to expose gaps in data-knowledge with regards to the Earth’s crust.

This EarthCube Building Blocks project will draw from significant disciplinary and interdisciplinary expertise in the development, implementation and support of geoscientific modeling architectures and in the adoption of community standards in model development and data management. This team will integrate existing model architectures, model coupling standards, and data standards into a set of open-source Earth System Bridge building blocks that will transform the process of Earth system model coupling, and bridge the present technological gap.

The ECITE federated Integration and Test (I&T) environment has the potential to scale and extend to an NSF wide integration and test capability that can serve as a model and example for other agencies. The ECITE team will actively engage EarthCube and the wider geosciences community in definition of requirements, design, and testing of the system. ECITE will consist of a seamless federated system of scalable and location independent distributed computational resources (nodes) across the US. The nodes will provide compute and storage resources requiring minimal system administration. ECITE is an important step in ensuring that EarthCube components will be able to work together to provide a successful framework that can continue to evolve to meet the needs of the geosciences community. This research addresses timely issues of integration, test and evaluation methodologies and best practices with a strong interoperability theme to advance disciplinary research through the integration of diverse and heterogeneous data, algorithms, systems and sciences. The results and findings will provide guidance for EarthCube evolution and future integration efforts. Access to the resulting platform will enable and encourage the EarthCube community to develop prototypes, try out new technologies, and to share ideas, concepts and experiments                

This Building Blocks project brings together the National Center for Atmospheric Research (NCAR), UNAVCO, and Cornell University to understand how to improve the processes of collaboration and resource sharing in the geosciences by demonstrating and encouraging the adoption of structured information systems rooted in common standards. Using two large geoscience research programs as case studies, this effort will demonstrate how semantic web and linked data technology can play an essential role in the coordination and organization of scientific virtual organizations and their products, thereby accelerating the pace of scientific discovery and innovation. Using the open source VIVO software, this project will seek to interlink information and data across platforms and research projects in an ontology-based standard data format (RDF), utilizing well developed web identifier and vocabulary structures.

This project will develop software tools to connect three established, well-supported, and critically important data sources: the Paleobiology Database (PBDB, paleontological, literature based), iDigPaleo (paleontological, specimen based) and iDigBio (neontological, specimen based). This project will allow users of any one of these databases to access and query the others at the same time, returning a much richer, combined set of data to the user. The development of this system will allow scientists to ask and answer new research questions affecting fields as diverse as biogeographic/niche modeling, systematics, functional morphology, evolutionary biology, ecology, climatology, conservation biology, oceanography, and petroleum geology. This project will fundamentally change the nature of the research questions that can be addressed by the scientific community.

When developing, testing, validating, and comparing models, particularly coupled models, the number of such data elements and the complexity associated with their management soon outgrows human memory capacity. The unfortunate consequence is that researchers often narrow the scope of a model analysis, compromise research quality, or conduct analysis within restricted teams. This Building Blocks project will demonstrate a mechanism to overcome this challenge in the scientific community.  GeoDataspace seeks to develop methods of defining, sharing and accessing the collections of metadata needed to define the files used in a given computational model, and details of the model run.  It is the goal that this approach will simplify model use and enhance sharing, reuse, and the reproducibility of models, data and computation properties.

This project will help NSF/EarthCube identify the most suitable IT environment in which the EarthCube should deploy and support shared infrastructure.

GeoTrust will develop sandboxing-based systems and tools that help scientists effectively isolate computational artifacts associated with an experiment, use languages and semantics to preserve artifacts, and re-execute /reproduce experiments by deploying the artifacts, changing datasets, algorithms, models, environments, etc.

This project builds upon previous work focused on integrated discovery of common information themes including precipitation in discrete data from the CUAHSI hydrologic information system and continuous data from the Unidata THREDDS data server. Investigators will advance that work by exploring the creation of new technologies for publishing and discovery of information through the Global Earth Observation System of Systems (GEOSS) Common Infrastructure, the definition of a Common Information Model for discrete and continuous data, development of shared software tools for using this Common Information Model, and extension of the concepts to similar information in the Polar, Ocean and Solid Earth Sciences.

The EarthCube Research Coordination Network for Intelligent Systems for Geosciences (IS-GEO RCN) will catalyze collaborations to enable advances in our understanding of Earth systems through innovative applications of intelligent and information systems to fundamental geosciences problems.

The ability to connect protein distributions in the oceans, with their implied chemical functionality, with chemical and biological ocean datasets has the potential to enable a broad array of microbial and biogeochemical discovery. The proposed cyberinfrastructure will benefit the broader biological and chemical oceanographic communities through making microbial protein data widely accessible and enabling connections between biogeochemical data and the enzymes that catalyze their reactions. This foundational infrastructure would be accessible to life scientists from other (non-ocean) domains as well. The portal will also contribute to the interpretation of GEOTRACES trace metal and isotope ocean full depth ocean via the incorporation of future protein datasets and linkages to the chemical datasets in BCO-DMO. This project will provide BCO-DMO with an opportunity to research and employ new techniques for efficient data mining combined with semantic technologies that will enable better data discovery and access for its community. In addition, working closely with the proteomics community will allow BCO-DMO data managers to gain working experience with this emerging data type.Specific goals include:

1. creating text-based and sequence-based search capability of processed protein datasets,
2. creating a geospatial global map visualization as well as table output of the query protein?s occurrence in the oceans,
3. providing an Ocean Data View compatible table export of geospatial and temporal distributions of the queried protein,
4. providing an analytic capability to answer the question the taxonomic origin of the protein components, building on our METATRYP Python software and including a lowest common ancestor analysis for each peptide component of the queried protein sequence,
5. creating linkages between protein datasets and relevant environmental datasets within BCO-DMO, and
6. creating a repository for processed and raw ocean protein data.

There is currently no universal way to share paleoclimate data between users or machines, hindering integration and synthesis. The platform will be combined with editorial and community-driven processes which will result in a system that has the potential to engage a broad user base in geoscientific data curation. The proposed framework will lower barriers to participation in the geosciences, enabling more "dark data" to join the public domain using community-sanctioned protocols. The pilot project will facilitate the work of hundreds of paleoclimate scientists, accelerating scientific discovery and the dissemination of its results to society.

The team will work closely to develop, evaluate,and deploy the computer infrastructure to improve the performance and scalability of geophysical analysis for scientific discovery and education. By making the system available to other researchers, it will facilitate the development of new scalable solutions. Interactive geosciences applications will be used as an effective means to promote students interest in science and engineering studies, and to attract and retain students for geosciences community growth. The innovation and the basis of our technique approach are to develop an optimal data layout algorithm for indexing and placing massive heterogeneous observation data across distributed devices of a cluster. The new data layout is tailored to the spatial-temporal characteristics of Earth observation data, and can directly account for advanced compute techniques, including non-volatile storage resources and GPU- and Manycore-based computing nodes, and support high-throughput and high-resolution exploration of large-scale data. 

This project will support advances in computing tools and techniques that will enable the Polar Sciences Community to address significant challenges, both in the short and long-term. The impact of this project will be in the improvements in the ability to utilize advanced cyberinfrastructure and high-performance distributed computing to fundamentally alter the scale, sophistication and scope of polar science problems that will be addressed. This project will not implement those changes but will identify and lay the groundwork for such impact across the Polar Sciences. The Project will identify primary barriers to the uptake of high-performance and distributed computing and will help alleviate them through a combination of community based solutions and training. The project will also produce a roadmap detailing a credible and effective way to meet the long-term computing challenges faced by the Polar Science community and possible plans to effectively address them. This project will establish mechanisms for community engagement which include gathering technical requirements for polar cyberinfrastructure and supporting and training early career scientists and graduate students.                

This EarthCube building blocks project intends to build ODSIP (Open Data Services Invocation Protocol) in order to provide an array of open specification in client/server libraries. This project also seeks to provide a system in which EarthCube can be built effectively around clients and servers that employ common and conceptually rich protocols for data acquisition.