SimpleGrid toolkit: Enabling geosciences gateways to cyberinfrastructure

Cyberinfrastructure science and engineering gateways have become an important modality to connect science and engineering communities and cyberinfrastructure. The use of cyberinfrastructure through gateways is fundamental to the advancement of science and engineering. However, learning science gateway technologies and developing science gateways remain a significant challenge, given that science gateway technologies are still actively evolving and often include a number of sophisticated components. A geosciences gateway must be designed to accommodate legacy methods that geoscientists use in conventional computational tools. The research described in this paper establishes an open-source toolkit—SimpleGrid for learning and developing science gateways based on a service-oriented architecture using a component-based approach that allows flexible separation and integration of the components between geocomputation applications and cyberinfrastructure. The design and implementation of SimpleGrid is based on the National Science Foundation TeraGrid—a key element of the U.S. and world cyberinfrastructure. This paper illustrates our experience of using SimpleGrid and a spatial interpolation method in a tutorial to teach TeraGrid science gateways.     

A centralized tool for managing,archiving, and serving point-in-time data in ecological research laboratories

The recent proliferation of software tools that aid researchers in various phases of data tracking and analysis undoubtedly contribute to successful development of increasingly complex and data-intensive scientific investigations. However, the lack of fully integrated solutions to data acquisition and storage, quality assurance/control, visualization, and provenance tracking of heterogeneous temporal data streams collected at numerous geospatial locations continues to occupy a general problem area for scientists and data managers working in the environmental sciences. We present a new Service Oriented Architecture (SOA) that allows users to: 1) automate the process of pushing real-time data streams from networks of environmental sensors or other data sources to an electronic data archive; 2) to perform basic data management and quality control tasks; and 3) to publish any subset of the data to existing cyberinfrastructure platforms for global discovery and distribution via the World Wide Web. The approach outlined here supports management of: 1) repeated field observations, 2) data from laboratory analysis of field samples, 3) simulation results, and 4) derived values. We describe how the use of Hypertext Transfer Protocol (HTTP) Application Programming Interfaces (APIs) Representational State Transfer (REST) methods for data model objects and Resource Query Language (RQL) interfaces respond to a basic problem area in environmental modelling by enabling researchers to integrate an electronic data repository with existing workflows, simulation models, or third-party software.     

Development and application of a real-time water environment cyberinfrastructure for kayaker safety in the Apostle Islands,Lake Superior

Assessing all pertinent environmental variables to categorize a skill level to safely navigate the water environment can be difficult for inexperienced kayakers, especially at a remote site where internet access is limited. A real-time kayaker safety assessment of water environmental conditions at the Mainland Sea Caves of the Apostle Islands National Lakeshore, Lake Superior is achieved. We present a new cyberinfrastructure that provides kayakers with real-time data access and a Safety Index (SI) with consideration of multiple environmental factors to characterize the degree of navigational difficulty for classifying kayaker skill levels. Specifically, radar reflectivity is added to improve forecasts of dangerous conditions caused by convective storms using state-of-the-art weather and wave modeling. Spectral characteristics of surface waves are employed to correlate the occurrences of extreme and freak waves. In addition, unexpectedly dangerous conditions like coastal upwelling and freak wave occurrence due to changing wind directions are considered. A contingency plan is implemented to handle the issue of possibly missing required environmental data. Display of the SI and visualization of other real-time environmental data are communicated by a power-efficient kiosk. Web analytics demonstrates a public interest in real-time water conditions and the need for the on-site kiosk to provide the latest information before kayakers enter the water. The new real-time water environment cyberinfrastructure for kayaker safety in the Apostle Islands, Lake Superior has been successfully operated since 2014.     

Identification and characterization of information-networks in long-tail data collections

Scientists' ability to synthesize and reuse long-tail scientific data lags far behind their ability to collect and produce these data. Many Earth Science Cyberinfrastructures enable sharing and publishing their data over the web using metadata standards. While profiling data attributes advances the Linked Data approach, it has become clear that building information-networks among distributed data silos is essential to increase their integration and reusability. In this research, we developed a Long-Tail Information-Network (LTIN) model, which uses a metadata-driven approach to build semantic information-networks among datasets published over the web and aggregate them around environmental events. The model identifies and characterizes the spatial and temporal contextual association links and dependencies among datasets. This paper presents the design and application of the LTIN model, and an evaluation of its performance. The model capabilities were demonstrated by inferring the information-network of a stream discharge located at the downstream end of the Illinois River.     

Observations Data Model 2: A community information model for spatially discrete Earth observations

Integrated access to and analysis of data for cross-domain synthesis studies are hindered because common characteristics of observational data, including time, location, provenance, methods, and units are described differently within different information models, including physical implementations and exchange schema. We describe a new information model for spatially discrete Earth observations called the Observations Data Model Version 2 (ODM2) aimed at facilitating greater interoperability across scientific disciplines and domain cyberinfrastructures. ODM2 integrates concepts from ODM1 and other existing cyberinfrastructures to expand capacity to consistently describe, store, manage, and encode observational datasets for archival and transfer over the Internet. Compared to other systems, it accommodates a wider range of observational data derived from both sensors and specimens. We describe the identification of community information requirements for ODM2 and then present the core information model and demonstrate how it can be formally extended to accommodate a range of information requirements and use cases.     

Towards an integrated Flood Information System: Centralized data access,analysis, and visualization

The Iowa Flood Information System (IFIS) is a web-based platform developed at the Iowa Flood Center (IFC) in order to provide access to flood inundation maps, real-time flood conditions, flood forecasts, flood-related data, information, applications, and interactive visualizations for communities in Iowa. The IFIS provides community-centric watershed and river characteristics, rainfall conditions, and stream-flow data and visualization tools. Interactive interfaces allow access to inundation maps for different stage and return period values as well as to flooding scenarios with contributions from multiple rivers. Real-time and historical data of water levels, gauge heights, hourly and seasonal flood forecasts, and rainfall conditions are made available by integrating data from NEXRAD radars, IFC stream sensors, and USGS and National Weather Service (NWS) stream gauges. The IFIS provides customized flood-related data, information, and visualization for over 1000 communities in Iowa. To help reduce the damage from floods, the IFIS helps communities make better-informed decisions about the occurrence of floods and alerts communities in advance using NWS and IFC forecasts. The integrated and modular design and structure of the IFIS allows easy adaptation of the system in other regional and scientific domains. This paper provides an overview of the design and capabilities of the IFIS that was developed as a platform to provide one-stop access to flood-related information.     

SWATShare – A web platform for collaborative research and education through online sharing,simulation and visualization of SWAT models

Hydrologic models for a particular watershed or a region are created for addressing a specific research or management problem, and most of the models do not get reused after the project is completed. Similarly, multiple models may exist for a particular geographic location from different researchers or organizations. To avoid the duplication of efforts, and enable model reuse and enhancement through collaborative efforts, a prototype cyberinfrastructure, called SWATShare, is developed for sharing, execution and visualization of Soil and Water Assessment Tool (SWAT). The objective of this paper is to present the software architecture, functional capabilities and implementation of SWATShare as a collaborative environment for hydrology research and education using the models published and shared in the system. Besides the capability of publishing, sharing, discovery and downloading of SWAT models, some of the functions in SWATShare such as model calibration are supported by providing access to high performance computing resources including the XSEDE and cloud. Additionally, SWATShare can create dynamic spatial and temporal plots of model outputs at different scales. SWATShare can also be used as an educational tool within a classroom setting for comparing the hydrologic processes under different geographic and climatic settings. The utility of SWATShare for collaborative research and education is demonstrated by using three case studies. Even though this paper focuses on the SWAT model, the system’s architecture can be replicated for other models as well.     

Life sciences and cyberinfrastructure: Dual and interacting revolutions that will drive future science

Over the past quarter century, two revolutions, one in biomedicine, the other in computing and information technology leading to cyberinfrastructure, have made the largest advances and the most significant impacts on science, technology, and society. The interface between these areas is rich with opportunity for major advances. The Life Sciences Grid Research Group (LSG-RG) of the Global Grid Forum recognized the opportunities and needs to bring the communities together to ensure the cyberinfrastructure will be constructed for the benefit of science. This article gives an overview of the area, the activities of the LSG-RG, and the minisymposium organized by LSG-RG, and introduces the papers in this Special Issue of New Generation Computing. Peter Arzberger, Ph.D.: He is the Director of Life Sciences Initiatives, University of California San Diego; Director of the National Biomedical Computation Resource (http://nbcr.ucsd.edu), funded by the National Center of Research Resource of NIH; and the Chair of the Pacific Rim Application and Grid Middleware Assembly (http://www.pragma-grid.edu), an organization of 20 institutions around the pacific rim whose mission is to establish sustained collaborations and to advance the use of grid technologies in applications. He serves on the US National CODATA Committee and the National Advisory Board of the US Long Term Ecological Research. His hobby is working on Lloyds. Abbas Farazdel, Ph.D.: He is a Senior Scientist and an IT Solution Strategist in the Advanced Technologies unit at the IBM Life Sciences. Previously, Dr. Farazdel worked at several positions in IBM including Cluster System Strategist; Data Warehousing and Data Mining Solutions Implementation Manager; and High Performance Computing Consultant. Abbas is the co-chair of the Global Grid Forum (GGF) Life Sciences Grids Research Group. He serves on the Scientific Board of the European Health Grid and the Mid Hudson Technology Council of New York. Abbas received his Ph.D. in Quantum Chemistry and M.Sc. in Computational Physics from the University of Massachusetts concurrently. Akihiko Konagaya, Dr. Eng.: He is Project Director of Bioinformatics Group, RIKEN Genomic Sciences Center. He received his B.S. and M.S. from Tokyo Institute of Technology in 1978 and 1980 in Informatics Science, and joined NEC Corporation in 1980, Japan Advanced Institute of Science and Technology in 1997, RIKEN GSC in 2003. His research covers wide area from computer architectures to bioinformatics. He has been much involved into the Open Bioinformatics Grid project since 2002. Larry Ang: As the Project Director in the Bioinformatics Institute (BII), he is in charge of major international collaborative projects on biomedical grids between BII and other research organizations (http://web.bii.a-star.edu.sg/ larry/). In particular, he works actively with bodies such as Pragma where he serves on the Steering Committee. He is also the Secretary of the Life Sciences Grid Research Group of GGF (Global Grid Forum) He serves on the Gelato Federation; Gelato was started by HP Labs and pushes open source software on linux platforms. Shinji Shimojo, Ph.D.: He received his M.E. and Ph.D. degrees from Osaka University in 1983 and 1986, respectively. He was an Assistant Professor with the Department of Information and Computer Sciences, Faculty of Engineering Science at Osaka University from 1986, and an Associate Professor with Computation Center from 1991 to 1998. During the period, he also worked as a visiting researcher at the University of California, Irvine for a year. He has been a Professor with Cybermedia Center (then Computation Center) at Osaka University since 1998. His current research work is focusing on a wide variety of multimedia applications, peer-to-peer communication networks, ubiquitous network systems and Grid technologies. He is a member of ACM, IEEE and IEICE. Rick L. Stevens, Ph.D.: He is Professor, University of Chicago; director, Mathematics and Computer Science Division/Argonne National Laboratory; director, ANL/UC Computation Institute; project director for National Science Foundation supported TeraGrid project; head of the Argonne/Chicago Futures Lab. He is interested in the development of innovative tools and techniques that enable computational scientists to solve important large-scale problems effectively on advanced scientific computers. His research focuses on three principal areas: advanced collaboration and visualization environments, high-performance computer architectures (including Grids), and computational problems in life sciences and systems biology. He teaches courses on computer architecture, collaboration technology, virtual reality, parallel computing, and computational science.     

Sharing and caring of eScience data

This commentary reflects on the issues presented in this volume from the perspective of a large eScience project, GEON, whose aim is to promote data integration in the geosciences within the US and abroad. Technical, social, and regulatory challenges accompanying the collection, curation, and sharing of eScience data are discussed. Opportunities and barriers to engaging in international eScience collaborations are highlighted.     

eScience today and tomorrow—Part 2

This special section contains the second part of a set of top papers from the 10th IEEE International eScience Conference (eScience 2014), held in October 2014 in Guarujá, Brazil). The authors of strongly-reviewed papers published in that conference were invited to extend their papers, which then went through a second peer review. This special section contains the three papers that comprise the second set of the extended papers. Part 1, with another seven extended papers, was already published in a previous issue of FGCS  [1].