VISAGE (Visualization for Integrated Satellite, Airborne, and Ground-based data Exploration) aims to provide visualization and analytic capabilities for diverse datasets in an interactive user interface. Proof-of-concept use cases are centered around the Global Precipitation Measurement (GPM) mission’s Ground Validation (GV) program, which provides a wealth of intensive, coincident observations of atmospheric phenomena from a wide variety of ground-based, airborne and satellite instruments. These data have diverse temporal and spatial scales, variables, and data formats and organization. Key technical challenges include: 3D data rendering and visualization of multiple diverse datasets on a web-based platform 3D data interrogation via map user interface Temporal alignment of data with diverse time scales and resolutions Computations on data fields across instruments and platforms To address these issues, the VISAGE project is working with cloud-native serverless technologies to render data as 3D Tile Point Clouds for display in the Cesium geospatial 3D global mapping platform.

Diverse airborne and ground-based environmental observations are important technologies for disaster assessment and response, as well as for the validation of environmental satellite observations and atmospheric models which can improve forecasts. The VISAGE (Visualization for Integrated Satellite, Airborne and Ground-based data Exploration) project is working to provide three-dimensional visualization and basic analytics capabilities for such datasets in an interactive user interface. The use of cloud-native, serverless technologies and analysis optimized data storage will position VISAGE for integration with other technologies into a Data Analytic Center Framework.

The primary goal of the VISAGE project is to facilitate more efficient Earth Science investigations via a tool that can provide visualization and analytic capabilities for diverse coincident datasets. This proof-of-concept project will be centered around the GPM Ground Validation program, which provides a valuable source of intensive, coincident observations of atmospheric phenomena. The data are from a wide variety of ground-based, airborne and satellite instruments, with a wide diversity in spatial and temporal scales, variables, and formats, which makes these data difficult to use together. VISAGE will focus on golden cases where most ground instruments were in operation and multiple research aircraft sampled a significant weather event, ideally while the GPM Core Observatory passed overhead. The resulting tools will support physical process studies as well as satellite and model validation.

In the spring of 2013, NASA conducted a field campaign known as Iowa Flood Studies (IFloodS) as part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission. The purpose of IFloodS was to enhance the understanding of flood-related, space-based observations of precipitation processes in events that transpire worldwide. NASA used a number of scientific instruments such as ground-based weather radars, rain and soil moisture gauges, stream gauges, and disdrometers to monitor rainfall events in Iowa. This article presents the cyberinfrastructure tools and systems that supported the planning, reporting, and management of the field campaign and that allow these data and models to be accessed, evaluated, and shared for research. The authors describe the collaborative informatics tools, which are suitable for the network design, that were used to select the locations in which to place the instruments. How the authors used information technology tools for instrument monitoring, data acquisition, and visualizations after deploying the instruments and how they used a different set of tools to support data analysis and modeling after the campaign are also explained. All data collected during the campaign are available through the Global Hydrology Resource Center (GHRC), a NASA Distributed Active Archive Center (DAAC).

The knowledge base for healthcare providers working in the field of organ transplantation has grown exponentially. However, the field has no centralized 'space' dedicated to efficient access and sharing of information. The ease of use and portability of mobile applications (apps) make them ideal for subspecialists working in complex healthcare environments. In this article, the authors review the literature related to healthcare technology; describe the development of health-related technology; present their mobile app pilot project assessing the effects of a collaborative, mobile app based on a freely available content manage framework; and report their findings. They conclude by sharing both lessons learned while completing this project and future directions.

Service registries can play a big role in helping developers, collaborators and agencies find deployed resources without difficulty. A service registry is especially useful if it follows a well-known, predefined specification that allows for automatic machine interactions and interoperability, such as the Open Geospatial Consortium (OGC) specification for Catalog Services for the Web (CSW). This chapter discusses a CSW-compliant registry developed as part of an OGC-sponsored interoperability experiment involving the ocean sciences community. The development approach for selecting, adapting and enhancing an open source implementation of the CSW is described. Implementation goals for the registry included support for OGC Sensor Observation Services (SOS) and additional functionality to minimize requirements on service providers and maximize the robustness of the registry. The registry’s role in the OGC Ocean Science Interoperability Experiment is also discussed.

Data-intensive science is a scientific discovery process that is driven by knowledge extracted from large volumes of data rather than the traditional hypothesis driven discovery process. One of the key challenges in data-intensive science is development of enabling technologies to allow researchers to effectively utilize these large volumes of data in an effective manner. This paper introduces the concept of “data prospecting” to address the challenges of data intensive science. With data prospecting, we extend the familiar metaphor of data mining to describe an initial phase of data exploration used to determine promising areas for deeper analysis. Data prospecting enhances data selection through the use of interactive discovery engines. Interactive exploration enables a researcher to filter the data based on the “first look” analytics, discover interesting and previously unknown patterns to start new science investigations, verify the quality of the data, and corroborate whether patterns in the data match existing science theories or mental models. This paper describes our initial evaluation of the value of“data prospecting” to Earth Science researchers as part of their research process. The paper describes our discovery engine prototype to support data prospecting for specific data products along with its current limitations. Example science investigations from three different researchers using our prototype discovery engine to explore the Special Sensor Microwave/Imager and Sounder (SSM/I, SSMIS) data products are also presented.

Accurate provenance information facilitates improved understanding of Earth science data and scientific reproducibility and can serve as an indicator of data quality. Provenance capture is an integral part of many modern workflow systems but may not have been considered in the design of legacy data production systems. Furthermore, in addition to data lineage, it is also important to capture contextual information needed for understanding how a data set was produced. This paper describes our experience in retrofitting a legacy data system to support capture, storage, and dissemination of provenance. Data inputs and transformations are logged automatically, while broader context information describing science algorithms and ancillary files is manually compiled. Provenance and context information are integrated for interactive user access and embedded into data files as XML documents compliant with the “Lineage” specification for geographic metadata defined by the International Organization for Standardization in the ISO 19115-2 standard. Lessons learned from this approach can inform others who need to incorporate provenance into a data system after the fact.

Service registries can play a big role in helping developers, collaborators and agencies find deployed resources without difficulty. A service registry is especially useful if it follows a well-known, predefined specification that allows for automatic machine interactions and interoperability, such as the Open Geospatial Consortium (OGC) specification for Catalog Services for the Web (CSW). This chapter discusses a CSW-compliant registry developed as part of an OGC-sponsored interoperability experiment involving the ocean sciences community. The development approach for selecting, adapting and enhancing an open source implementation of the CSW is described. Implementation goals for the registry included support for OGC Sensor Observation Services (SOS) and additional functionality to minimize requirements on service providers and maximize the robustness of the registry. The registry's role in the OGC Ocean Science Interoperability Experiment is also discussed.