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Ramachandran, Rahul

Publications and source records attributed to Ramachandran, Rahul.

104 records · Page 6
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NASA NTRS2014

Anticipated Changes in Conducting Scientific Data-Analysis Research in the Big-Data Era

A Big-Data environment is one that is capable of orchestrating quick-turnaround analyses involving large volumes of data for numerous simultaneous users. Based on our experiences with a prototype Big-Data analysis environment, we anticipate some important changes in research behaviors and processes while conducting scientific data-analysis research in the near future as such Big-Data environments become the mainstream. The first anticipated change will be the reduced effort and difficulty in most parts of the data management process. A Big-Data analysis environment is likely to house most of the data required for a particular research discipline along with appropriate analysis capabilities. This will reduce the need for researchers to download local copies of data. In turn, this also reduces the need for compute and storage procurement by individual researchers or groups, as well as associated maintenance and management afterwards. It is almost certain that Big-Data environments will require a different "programming language" to fully exploit the latent potential. In addition, the process of extending the environment to provide new analysis capabilities will likely be more involved than, say, compiling a piece of new or revised code.We thus anticipate that researchers will require support from dedicated organizations associated with the environment that are composed of professional software engineers and data scientists. A major benefit will likely be that such extensions are of higherquality and broader applicability than ad hoc changes by physical scientists. Another anticipated significant change is improved collaboration among the researchers using the same environment. Since the environment is homogeneous within itself, many barriers to collaboration are minimized or eliminated. For example, data and analysis algorithms can be seamlessly shared, reused and re-purposed. In conclusion, we will be able to achieve a new level of scientific productivity in the Big-Data analysis environments.

Kuo, Kwo-Sen↗
NASA NTRS2014

Research Data Alliance: Understanding Big Data Analytics Applications in Earth Science

The Research Data Alliance (RDA) enables data to be shared across barriers through focused working groups and interest groups, formed of experts from around the world - from academia, industry and government. Its Big Data Analytics (BDA) interest groups seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. BDA seeks to analyze different scientific domain applications (e.g. earth science use cases) and their potential use of various big data analytics techniques. These techniques reach from hardware deployment models up to various different algorithms (e.g. machine learning algorithms such as support vector machines for classification). A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. This contribution will outline initial parts of such a classification and recommendations in the specific context of the field of Earth Sciences. Given lessons learned and experiences are based on a survey of use cases and also providing insights in a few use cases in detail.

Riedel, Morris↗
NASA NTRS2014

Constructing Data Albums for Significant Severe Weather Events

There is need in the research community for weather-related case studies to improve prediction of and recovery after convective thunderstorms that produce damaging winds, hail, and tornadoes. One of the largest continuing challenges in any Earth Science investigation is the discovery of and access to useful science content from the increasingly large volumes of available Earth Science data. The Information Technology and Systems Center at the University of Alabama in Huntsville has developed a software system called Noesis 2.0 that can be used to produce Data Albums for weather events relevant to NASA Earth Science researchers. Noesis is an Internet search tool that combines relevant storm research, pictures and videos of an event or event aftermath, web pages containing news reports and official storm summaries, background information about damage, injuries, and deaths, and NASA datasets from field campaigns and satellites into a "one-stop shop" database. The Data Album concept has been previously applied to hurricane cases from 2010 to present. The objective of this paper is to extend that Hurricane Data Album concept to focus on development of an ontology for significant severe weather to aid in selecting appropriate NASA datasets for inclusion in a severe weather Data Album. Recent severe weather events in Moore and El Reno, Oklahoma will be analyzed as an example of how these events can be incorporated into a Data Album.

Greene, Ethan↗
NASA NTRS2014

Constructing Data Albums for Significant Severe Weather Events

Data Albums provide a one-stop-shop combining datasets from NASA, NWS, online new sources, and social media. Data Albums will help meteorologists better understand severe weather events to improve predictive models. Developed a new ontology for severe weather based off current hurricane Data Album and selected relevant NASA datasets for inclusion.

Greene, Ethan↗
NASA NTRS2014

Earth Science Informatics Comes of Age

The volume and complexity of Earth science data have steadily increased, placing ever-greater demands on researchers, software developers and data managers tasked with handling such data. Additional demands arise from requirements being levied by funding agencies and governments to better manage, preserve and provide open access to data. Fortunately, over the past 10-15 years significant advances in information technology, such as increased processing power, advanced programming languages, more sophisticated and practical standards, and near-ubiquitous internet access have made the jobs of those acquiring, processing, distributing and archiving data easier. These advances have also led to an increasing number of individuals entering the field of informatics as it applies to Geoscience and Remote Sensing. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of data, information, and knowledge. Informatics also encompasses the use of computers and computational methods to support decisionmaking and other applications for societal benefits.

Jodha, Siri↗
NASA NTRS2014

Collaborative WorkBench for Researchers - Work Smarter, Not Harder

It is important to define some commonly used terminology related to collaboration to facilitate clarity in later discussions. We define provisioning as infrastructure capabilities such as computation, storage, data, and tools provided by some agency or similarly trusted institution. Sharing is defined as the process of exchanging data, programs, and knowledge among individuals (often strangers) and groups. Collaboration is a specialized case of sharing. In collaboration, sharing with others (usually known colleagues) is done in pursuit of a common scientific goal or objective. Collaboration entails more dynamic and frequent interactions and can occur at different speeds. Synchronous collaboration occurs in real time such as editing a shared document on the fly, chatting, video conference, etc., and typically requires a peer-to-peer connection. Asynchronous collaboration is episodic in nature based on a push-pull model. Examples of asynchronous collaboration include email exchanges, blogging, repositories, etc. The purpose of a workbench is to provide a customizable framework for different applications. Since the workbench will be common to all the customized tools, it promotes building modular functionality that can be used and reused by multiple tools. The objective of our Collaborative Workbench (CWB) is thus to create such an open and extensible framework for the Earth Science community via a set of plug-ins. Our CWB is based on the Eclipse [2] Integrated Development Environment (IDE), which is designed as a small kernel containing a plug-in loader for hundreds of plug-ins. The kernel itself is an implementation of a known specification to provide an environment for the plug-ins to execute. This design enables modularity, where discrete chunks of functionality can be reused to build new applications. The minimal set of plug-ins necessary to create a client application is called the Eclipse Rich Client Platform (RCP) [3]; The Eclipse RCP also supports thousands of community-contributed plug-ins, making it a popular development platform for many diverse applications including the Science Activity Planner developed at JPL for the Mars rovers [4] and the scientific experiment tool Gumtree [5]. By leveraging the Eclipse RCP to provide an open, extensible framework, a CWB supports customizations via plug-ins to build rich user applications specific for Earth Science. More importantly, CWB plug-ins can be used by existing science tools built off Eclipse such as IDL or PyDev to provide seamless collaboration functionalities.

Ramachandran, Rahul↗
NASA NTRS2014

Use of Semantic Technology to Create Curated Data Albums

One of the continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available online. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the data sets they need can obtain the specific files using these systems. However, in cases where researchers are interested in studying an event of research interest, they must manually assemble a variety of relevant data sets by searching the different distributed data systems. Consequently, there is a need to design and build specialized search and discover tools in Earth science that can filter through large volumes of distributed online data and information and only aggregate the relevant resources needed to support climatology and case studies. This paper presents a specialized search and discovery tool that automatically creates curated Data Albums. The tool was designed to enable key elements of the search process such as dynamic interaction and sense-making. The tool supports dynamic interaction via different modes of interactivity and visual presentation of information. The compilation of information and data into a Data Album is analogous to a shoebox within the sense-making framework. This tool automates most of the tedious information/data gathering tasks for researchers. Data curation by the tool is achieved via an ontology-based, relevancy ranking algorithm that filters out nonrelevant information and data. The curation enables better search results as compared to the simple keyword searches provided by existing data systems in Earth science.

Ramachandran, Rahul↗
NASA NTRS2014

Use of Semantic Technology to Create Curated Data Albums

One of the continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available online. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the data sets they need can obtain the specific files using these systems. However, in cases where researchers are interested in studying an event of research interest, they must manually assemble a variety of relevant data sets by searching the different distributed data systems. Consequently, there is a need to design and build specialized search and discovery tools in Earth science that can filter through large volumes of distributed online data and information and only aggregate the relevant resources needed to support climatology and case studies. This paper presents a specialized search and discovery tool that automatically creates curated Data Albums. The tool was designed to enable key elements of the search process such as dynamic interaction and sense-making. The tool supports dynamic interaction via different modes of interactivity and visual presentation of information. The compilation of information and data into a Data Album is analogous to a shoebox within the sense-making framework. This tool automates most of the tedious information/data gathering tasks for researchers. Data curation by the tool is achieved via an ontology-based, relevancy ranking algorithm that filters out non-relevant information and data. The curation enables better search results as compared to the simple keyword searches provided by existing data systems in Earth science.

Ramachandran, Rahul↗
NASA NTRS2011

Cross-Cutting Interoperability in an Earth Science Collaboratory

An Earth Science Collaboratory is: A rich data analysis environment with: (1) Access to a wide spectrum of Earth Science data, (3) A diverse set of science analysis services and tools, (4) A means to collaborate on data, tools and analysis, and (5)Supports sharing of data, tools, results and knowledge

Lynnes, Christopher↗
NASA NTRS2008

Earth Science Mining Web Services

To allow scientists further capabilities in the area of data mining and web services, the Goddard Earth Sciences Data and Information Services Center (GES DISC) and researchers at the University of Alabama in Huntsville (UAH) have developed a system to mine data at the source without the need of network transfers. The system has been constructed by linking together several pre-existing technologies: the Simple Scalable Script-based Science Processor for Measurements (S4PM), a processing engine at he GES DISC; the Algorithm Development and Mining (ADaM) system, a data mining toolkit from UAH that can be configured in a variety of ways to create customized mining processes; ActiveBPEL, a workflow execution engine based on BPEL (Business Process Execution Language); XBaya, a graphical workflow composer; and the EOS Clearinghouse (ECHO). XBaya is used to construct an analysis workflow at UAH using ADam components, which are also installed remotely at the GES DISC, wrapped as Web Services. The S4PM processing engine searches ECHO for data using space-time criteria, staging them to cache, allowing the ActiveBPEL engine to remotely orchestras the processing workflow within S4PM. As mining is completed, the output is placed in an FTP holding area for the end user. The goals are to give users control over the data they want to process, while mining data at the data source using the server's resources rather than transferring the full volume over the internet. These diverse technologies have been infused into a functioning, distributed system with only minor changes to the underlying technologies. The key to the infusion is the loosely coupled, Web-Services based architecture: All of the participating components are accessible (one way or another) through (Simple Object Access Protocol) SOAP-based Web Services.

Pham, Long↗
NASA NTRS2003

ESML for Earth Science Data Sets and Analysis

The primary objective of this research project was to transition ESML from design to application. The resulting schema and prototype software will foster community acceptance for the Define once, use anywhere concept central to ESML. Supporting goals include: 1) Refinement of the ESML schema and software libraries in cooperation with the user community; 2) Application of the ESML schema and software to a variety of Earth science data sets and analysis tools; 3) Development of supporting prototype software for enhanced ease of use; 4) Cooperation with standards bodies in order to assure ESML is aligned with related metadata standards as appropriate; and 5) Widespread publication of the ESML approach, schema, and software.

Graves, Sara↗
NASA NTRS2002

Earth Science Markup Language: Transitioning From Design to Application

The primary objective of the proposed Earth Science Markup Language (ESML) research is to transition from design to application. The resulting schema and prototype software will foster community acceptance for the "define once, use anywhere" concept central to ESML. Supporting goals include: 1. Refinement of the ESML schema and software libraries in cooperation with the user community. 2. Application of the ESML schema and software libraries to a variety of Earth science data sets and analysis tools. 3. Development of supporting prototype software for enhanced ease of use. 4. Cooperation with standards bodies in order to assure ESML is aligned with related metadata standards as appropriate. 5. Widespread publication of the ESML approach, schema, and software.

Moe, Karen↗
NASA NTRS1998

Total Lightning and Radar Storm Characteristics Associated with Severe Storms in Central Florida

A number of prior studies have examined the association of lightning activity with the occurrence of severe weather and tornadoes, in particular. High flash rates are often observed in tornadic storms (Taylor, 1973; Johnson, 1980; Goodman and Knupp, 1993) but not always. Taylor found that 23% of nontornadic storms and 1% of non-severe storms had sferics rates comparable to the tornadic storms. MacGorman (1993) found that storms with mesocyclones produced more frequent intracloud (IC) lightning than cloud-to-ground (CG) lightning. MacGorman (1993) and others suggest that the lightning activity accompanying tomadic storms will be dominated by intracloud lightning-with an increase in intracloud and total flash rates as the updraft increases in depth, size, and velocity. In a recent study, Perez et al. (1998) found that CG flash rates alone are too variable to be a useful predictor of (F4, F5) tornado formation. Studies of non-tomadic storms have also shown that total lightning flash rates track the updraft, with rates increasing as the updraft intensities and decreasing rapidly with cessation of vertical growth or downburst onset (Goodman et al., 1988; Williams et al., 1989). Such relationships result from the development of mixed phase precipitation and increased hydrometer collisions that lead to the efficient separation of charge. Correlations between updraft strength and other variables such as cloud-top height, cloud water mass, and hail size have also been observed.

Goodman, Steven J.↗