Christopher Lynnes

Bio: Christopher Lynnes is an academic researcher from Goddard Space Flight Center. The author has contributed to research in topics: Data management & Data quality. The author has an hindex of 9, co-authored 40 publications receiving 271 citations.

Semantic Web Data Discovery of Earth Science Data at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC)

Abstract: Mirador is a web interface for searching Earth Science data archived at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Mirador provides keyword-based search and guided navigation for providing efficient search and access to Earth Science data. Mirador employs the power of Google's universal search technology for fast metadata keyword searches, augmented by additional capabilities such as event searches (e.g., hurricanes), searches based on location gazetteer, and data services like format converters and data sub-setters. The objective of guided data navigation is to present users with multiple guided navigation in Mirador is an ontology based on the Global Change Master directory (GCMD) Directory Interchange Format (DIF). Current implementation includes the project ontology covering various instruments and model data. Additional capabilities in the pipeline include Earth Science parameter and applications ontologies.

Access, Visualization, and Interoperability of Air Quality Remote Sensing Data Sets via the Giovanni Online Tool

Abstract: This paper describes the air quality data products and services available through Giovanni, a web based tool for access, visualization, and analysis of satellite remote sensing products, and also model output and surface observations relevant to global air quality. Available datasets include total column aerosol measurements from numerous satellite instruments, column NO2 and SO2, vertical aerosol products from CALIPSO, surface PM2.5 concentrations over the continental U.S, and speciated model Aerosol Optical Depth. Giovanni was designed to make satellite and ground-based data easier to use; it does not require separate access to or downloading of data sets, making the visualizations and analysis services accessible to both the novice and the experienced user. Giovanni air quality data products are provided on a common grid and can also be obtained in KMZ format for Google Earth visualization. This feature allows collocation of datasets to aid in analysis of pollution events and to facilitate satellite/monitor comparisons and aerosol intercomparison studies in a fraction of the time compared to traditional methods. Giovanni also supports multiple interoperability protocols which permit data sharing with other online tools, in order to enhance access to the datasets for improved air quality decision making. The Giovanni team is currently actively involved in several data networking initiatives with service oriented tools at other institutions such as DataFed.

Giovanni: The Bridge between Data and Science

Abstract: NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a web-based remote sensing and model data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional data sets, covering atmospheric dynamics, atmospheric chemistry, hydrology, oceanographic, and land surface. Data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. Visualization options enable comparisons of multiple variables and easier refinement. Recently, new features have been developed, such as interactive scatter plots and maps. The performance is also being improved, in some cases by an order of magnitude for certain analysis functions with optimized software. We are working toward merging current Giovanni portals into a single omnibus portal with all variables in one (virtual) location to help users find a variable easily and enhance the intercomparison capability

Big Data Challenges in Climate Science: Improving the next-generation cyberinfrastructure

Abstract: The knowledge we gain from research in climate science depends on the generation, dissemination, and analysis of high-quality data. This work comprises technical practice as well as social practice, both of which are distinguished by their massive scale and global reach. As a result, the amount of data involved in climate research is growing at an unprecedented rate. Some examples of the types of activities that increasingly require an improved cyberinfrastructure for dealing with large amounts of critical scientific data are climate model intercomparison (CMIP) experiments; the integration of observational data and climate reanalysis data with climate model outputs, as seen in the Observations for Model Intercomparison Projects (Obs4MIPs), Analysis for Model Intercomparison Projects (Ana4MIPs), and Collaborative Reanalysis Technical Environment-Intercomparison Project (CREATE-IP) activities; and the collaborative work of the Intergovernmental Panel on Climate Change (IPCC). This article provides an overview of some of climate science's big data problems and the technical solutions being developed to advance data publication, climate analytics as a service, and interoperability within the Earth System Grid Federation (ESGF), which is the primary cyberinfrastructure currently supporting global climate research activities.

Scientific Data Management in the Coming Decade

Abstract: This is a thought piece on data-intensive science requirements for databases and science centers. It argues that peta-scale datasets will be housed by science centers that provide substantial storage and processing for scientists who access the data via smart notebooks. Next-generation science instruments and simulations will generate these peta-scale datasets. The need to publish and share data and the need for generic analysis and visualization tools will finally create a convergence on common metadata standards. Database systems will be judged by their support of these metadata standards and by their ability to manage and access peta-scale datasets. The procedural stream-of-bytes-file-centric approach to data analysis is both too cumbersome and too serial for such large datasets. Non-procedural query and analysis of schematized self-describing data is both easier to use and allows much more parallelism.

A land data assimilation system for sub-Saharan Africa food and water security applications

Abstract: Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa. Machine-accessible metadata file describing the reported data (ISA-Tab format)

Google Earth as a virtual globe tool for Earth science applications at the global scale: progress and perspectives

Abstract: Research on global environmental change requires new data processing and analysis tools that can integrate heterogeneous geospatial data from real-time in situ measurement, remote sensing RS and geographic information systems GISs at the global scale. The rapid growth of virtual globes for global geospatial information management and display holds promise to meet such a requirement. Virtual globes, Google Earth in particular, enable scientists around the world to communicate their data and research findings in an intuitive three-dimensional 3D global perspective. Different from traditional GIS, virtual globes are low cost and easy to use in data collection, exploration and visualization. Since 2005, a considerable number of papers have been published in peer-reviewed journals and proceedings from a variety of disciplines. In this review, we examine the development and applications of Google Earth and highlight its merits and limitations for Earth science studies at the global scale. Most limitations are not unique to Google Earth, but to all virtual globe products. Several recent efforts to increase the functionalities in virtual globes for studies at the global scale are introduced. The power of virtual globes in their current generations is mostly restricted to functions as a ‘geobrowser’; a better virtual globe tool for Earth science and global environmental change studies is described.

Open knowledge: challenges and facts

Abstract: Purpose – The purpose of this paper is to open the special issue of Online Information Review on open knowledge management in higher education. Its aim is to review the concept and extension of the movement or philosophy of open knowledge in universities and higher education institutions.Design/methodology/approach – The approach follows the reference model used by the University of Salamanca (Spain) to promote open knowledge in the institution through its Open Knowledge Office. This model comprises four areas: free software, open educational content and cultural dissemination, open science, and open innovation.Findings – For each of the four areas mentioned above, milestones and the most significant projects are presented, showing how they are promoting publication and information transmission in an open environment, without restrictions and favouring knowledge dissemination in all fields.Originality/value – Open knowledge is an approach which, although somewhat controversial, is growing relentlessly as ...