Chaitan Baru

Managing scientific data: From data integration to scientific workflows*

Scientists are confronted with significant datamanagement problems due to the large volume and high complexity of scientific data. In particular, the latter makes data integration a difficult technical challenge. In this paper, we describe our work on semantic mediation and scientific workflows, and discuss how these technologies address integration challenges in scientific data management. We first give an overview of the main data-integration problems that arise from heterogeneity in the syntax, structure, and semantics of data. Starting from a traditional mediator approach, we show how semantic extensions can facilitate data integration in complex, multipleworlds scenarios, where data sources cover different but related scientific domains. Such scenarios are not amenable to conventional schema-integration approaches. The core idea of semantic mediation is to augment database mediators and query evaluation algorithms with appropriate knowledge-representation techniques to exploit information from shared ontologies. Semantic mediation relies on semantic data registration, which associates existing data with semantic information from an ontology. The Kepler scientific workflow system addresses the problem of synthesizing, from existing tools and applications, reusable workflow components and analytical pipelines to automate scientific analyses. After presenting core features and example workflows in Kepler, we present a framework for adding semantic information to scientific workflows. The resulting system is aware of semantically plausible connections between workflow components as well as between data sources and workflow components. This information can be used by the scientist during workflow design, and by the workflow engineer for creating data transformation steps between semantically compatible but structurally incompatible analytical steps. ∗Work supported by NSF/ITR 0225673 (GEON), NSF/ITR 0225676 (SEEK), NIH/NCRR 1R24 RR019701-01 Biomedical Informatics Research Network (BIRN-CC), and DOE SciDAC DE-FC02-01ER25486 (SDM) †San Diego Supercomputer Center, University of California, San Diego, {ludaesch,lin,bowers,efrat,baru}@sdsc.edu ‡Natural Resources of Canada, brodaric@nrcan.gc.ca

The GEON portal: accelerating knowledge discovery in the geosciences

Geoscience studies produce data from various observations, experiments, and simulations at an enormous rate. With proliferation of applications and data formats, the geoscience research community faces many challenges in effectively managing and sharing resources and in efficiently integrating and analyzing the data. In this paper, we discuss how this challenge is being addressed by the GEON Portal, a Web based distributed resource management system that provides integrated access to data and tools needed for knowledge discovery in the geosciences. Unlike previous data management efforts that were either data-driven or application-driven, the GEON Portal provides facilities for efficient sharing, discovery and integration of both data and services that use geoscience data. We identify the challenges involved in managing geoscientific resources and provide solutions that exploit the syntactic, semantic, temporal and spatial metadata associated with the resources. One of our goals is to provide some insight into the challenges involved in providing a comprehensive scientific data management solution based on our experiences with geoscientific data.

GEONGrid portal: design and implementations

We have developed the GEONGrid system for coordinating and managing naturally distributed computing, data, and cluster resources on the cyberinfrastructure. Recently, since the use of Grid technology is still very complex for researchers and scientists, the area of Grid Portals has made excellent progress. The Grid portal system is an emerging open Grid computing environment that promises to provide users with uniform seamless access to remote computing and data resources by providing an easy to use interface to cover over the complexity of more sophisticated Grid technologies. In this paper, we present our initial efforts in the design and implementation of service components in the GEONGrid portal. These service components may be implemented as Web services that follow the conventions of service‐oriented architecture design. In this approach, service components are self‐contained, have a well‐defined programming interface defined in WSDL, and communicate using SOAP messaging. In building a GEONGrid portal, we also use a component‐based user interface design. Portlets provide the desired component model for user interfaces in the same way as Web services. Using this approach, which allows Grid portals to be built out of reusable components, has the obvious advantages of reusability and modularity. Copyright

CYberinfrastructure for COmparative effectiveness REsearch (CYCORE): improving data from cancer clinical trials

ABSTRACTImproved approaches and methodologies are needed to conduct comparative effectiveness research (CER) in oncology. While cancer therapies continue to emerge at a rapid pace, the review, synthesis, and dissemination of evidence-based interventions across clinical trials lag in comparison. Rigorous and systematic testing of competing therapies has been clouded by age-old problems: poor patient adherence, inability to objectively measure the environmental influences on health, lack of knowledge about patients’ lifestyle behaviors that may affect cancer’s progression and recurrence, and limited ability to compile and interpret the wide range of variables that must be considered in the cancer treatment. This lack of data integration limits the potential for patients and clinicians to engage in fully informed decision-making regarding cancer prevention, treatment, and survivorship care, and the translation of research results into mainstream medical care. Particularly important, as noted in a 2009 report on CER to the President and Congress, the limited focus on health behavior-change interventions was a major hindrance in this research landscape (DHHS 2009). This paper describes an initiative to improve CER for cancer by addressing several of these limitations. The Cyberinfrastructure for Comparative Effectiveness Research (CYCORE) project, informed by the National Science Foundation’s 2007 report “Cyberinfrastructure Vision for 21st Century Discovery” has, as its central aim, the creation of a prototype for a user-friendly, open-source cyberinfrastructure (CI) that supports acquisition, storage, visualization, analysis, and sharing of data important for cancer-related CER. Although still under development, the process of gathering requirements for CYCORE has revealed new ways in which CI design can significantly improve the collection and analysis of a wide variety of data types, and has resulted in new and important partnerships among cancer researchers engaged in advancing health-related CI.

A three tier architecture for LiDAR interpolation and analysis

Emerging Grid technologies enable solving scientific problems that involve large datasets and complex analyses. Coordinating distributed Grid resources and computational processes requires adaptable interfaces and tools that provide a modularized and configurable environment for accessing Grid clusters and executing high performance computational tasks. In addition, it is beneficial to make these tools available to the community in a unified framework through a shared cyberinfrastructure, or a portal, so scientists can focus on their scientific work and not be concerned with the implementation of the underlying infrastructure. In this paper we describe a scientific workflow approach to coordinate various resources as data analysis pipelines. We present a three tier architecture for LiDAR interpolation and analysis, a high performance processing of point intensive datasets, utilizing a portal, a scientific workflow engine and Grid technologies. Our proposed solution is available through the GEON portal and, though focused on LiDAR processing, is applicable to other domains as well.

Using 9-1-1 call data and the space–time permutation scan statistic for emergency event detection

The space-time permutation scan statistic has been previously used to detect disease outbreaks, without need for uniform population at risk, control group data, or information about the distribution of population-at-risk in order to establish the statistical significance of found clusters of cases. This paper shows results from using the space-time permutation scan statistic to detect clusters of 9-1-1 emergency calls. These clusters are then correlated with wide-scale emergency events as reported on the news. Using several examples, it is shown that these clusters are useful for estimating the location, temporal extent, and human impact of such emergency events.

Leveraging XSEDE HPC resources to address computational challenges with high-resolution topography data

Leveraging service-oriented architectures and taking advantage of the high-performance compute resources provided by XSEDE, we have developed standards-based web services to address the challenges associated with processing large volumes of high resolution topography data. These web services make results from community software packages and other cyberinfrastructure-based applications available to the wider earth sciences community via the OpenTopography Facility and the CyberGIS Gateway.

Representation and display of geospatial information: a comparison of ArcXML and SVG

The move to Web-based geographic information systems (GIS) has led to the creation of XML languages for representing geospatial information and publishing map services. One such language, developed by the Environmental Systems Research Institute (ESRI), is ArcXML. ArcXML provides a range of functionality, including representation of geospatial information and presentation of map information. We compare the spatial representation and presentation capabilities of ArcXML with those of the Scalable Vector Graphics (SVG) standard, which is an XML-based standard for 2D graphics. Our objective is to study the differences in representation and display capabilities of GIS versus non-GIS XML languages.

The GEON service-oriented architecture for Earth Science applications

Abstract The Geosciences Network (GEON) project has been developing cyberinfrastructure for data sharing in the Earth Science community based on a service-oriented architecture. The layered architecture consists of Core, Middleware, and Applications services. Core services provide system-level functions (e.g. user authentication), Middleware services provide generic capabilities (e.g. catalog search), and Application services provide functions that users directly interact with, including applications that are specific to Earth Sciences. The GEON ‘service stack’ includes a standardized set of these services and the corresponding software modules. The GEON Portal provides Web-based access to these services via a set of portlets. This service-oriented approach has enabled GEON to expand to new partner sites and leverage GEON services for other projects. To facilitate interoperation in a distributed geoinformatics environment, GEON is focusing on standards for distributed search across federated catalogs.

Spatiotemporal analysis of 9-1-1 call stream data

Currently, archival 9-1-1 call stream data is used mainly for administrative purposes. We present spatiotemporal analysis of thirteen months worth of call stream data for the purpose of illustrating how this data might be used for enhancing emergency response in the State of California. An analysis of the data shows regularity in the 9-1-1 call volume which can facilitate the automatic detection of abnormally high call volumes that are associated with environmental, medical emergency, and law enforcement events. Thus, this is a first step towards the detection of unusual trends that could indicate widely spread events that require response beyond that of isolated incidents.