Science Gateway Research Articles

Science Gateway Workshops 2015 Special Issue Conference Publications

[Extract] The special issue combines extended versions of submissions to the International Workshop on Science Gateways (Budapest, June, 2016), the Gateway Computing Environments workshop (Boulder, CO, September, 2016) and the International Workshop on Science Gateways – Australia (Brisbane, October). These events serve to foster the world-wide community of those involved in developing science gateways – advanced web portals used by the scientists and scholars to conduct their work. Four main areas have been addressed in the submissions: domain gateways, gateways adapted for diverse research infrastructures, data management in gateways and gateway workflows.

Enabling Workflow-Oriented Science Gateways to Access Multi-Cloud Systems

In this paper we present a solution to cloud-enable workflow-oriented science gateways. The integration mechanism described in the paper is a generic method that can be followed by other gateway developers. The paper describes the principles and the concrete ways to integrate science gateways with multi-cloud systems. The concrete example to demonstrate the integration principles builds on the integration of WS-PGRADE/gUSE and the CloudBroker Platform (CBP). The integration of WS-PGRADE and the CloudBroker Platform offers a complete cloud-enabled science gateway platform for a diverse set of use-cases and user communities, with the availability to use mainstream cloud middleware types and services (Amazon, IBM, OpenStack, OpenNebula). The advantage of the integrated WS-PGRADE and CloubBroker Platform system is that if a domain-specific science gateway is customized from WS-PGRADE gateway framework it immediately inherits this cloud access flexibility, i.e. the user community of that gateway can access all the cloud types enabled by the integrated system presented.

Web Services as Building Blocks for Science Gateways in Astrophysics

An efficient exploitation of Distributed Computing Infrastructures (DCIs) is needed to deal with the data deluge that the scientific community is facing, in particular the Astrophysics one due to the emerging Square Kilometre Array (SKA) telescope that will reach data rates in the exascale domain. Hence, Science Gateways are being enriched with advanced tools that not only enable the scientists to build their experiments but also to optimize their adaptation to different infrastructures. In this work we present a method, called two-level workflow system, to build this kind of tools and we apply it to a set of analysis tasks of interest for some use applications to the SKA. This method uses the Software-as-a-Service model to keep the scientists insulated from technical complexity of DCIs, and the COMPSs programming model to achieve an efficient use of the computing resources.

Using Science Gateways for Bridging the Differences between Research Infrastructures

Researchers can perform large-scale analyses on diverse computing and data infrastructures such as NGIs (National Grid Infrastructures), XSEDE (Extreme Science and Engineering Discovery Environment) and PRACE (Partnership for Advanced Computing in Europe). Some are national like NGIs and XSEDE, some are international like PRACE and all of them require a more or less restrictive application process to get access to resources. Science gateways integrating diverse infrastructures provide the possibility to re-use methods independent of such underlying infrastructures and thus potentially deliver the technical prerequisite for creating reproducible science. To achieve this goal, science gateways have to be integrated seamlessly with security mechanisms and job, data as well as workflow management of the targeted resources. This paper gives an overview on general findings for porting science gateways as well as the challenges faced for porting the German MoSGrid science gateway (Molecular Simulation Grid) to exploit XSEDE and PRACE infrastructures.

Increasing Exposure to Programming: A Comparison of Demographic Characteristics of Students Enrolled in Introductory Computer Science Programming Courses vs. a Multidisciplinary Data Analysis Course

Upward trends in programming careers and increases in programming in less traditionally computer-oriented occupations threaten to further increase the current underrepresentation of both females and individuals from racial minority groups in these disciplines. Using administrative data (2009 – 2014), the present study compares demographic characteristics of students enrolled in a course that introduced programming: a multidisciplinary data analysis course, an introductory programming course, or an introductory computer science (CS) gateway course. The multidisciplinary data analysis course enrolled significantly more female students and students with lower Math SAT scores. Females were overrepresented in the data analysis course and underrepresented in the introductory programming and CS gateway courses relative to the larger campus community, with similar findings for underrepresented minority students. Less emphasis on traditional approaches to introductory programming and increased interdisciplinary opportunities to tackle real world questions may be one way to improve access to programming experiences for students from a wider range of educational, social and economic backgrounds.

Development of Science Gateways Using QCG — Lessons Learned from the Deployment on Large Scale Distributed and HPC Infrastructures

Today, various Science Gateways created in close collaboration with scientific communities provide access to remote and distributed HPC, Grid and Cloud computing resources and large-scale storage facilities. However, as we have observed there are still many entry barriers for new users and various limitations for active scientists. In this paper we present our latest achievements and software solutions that significantly simplify the use of large scale and distributed computing. We describe several Science Gateways that have been successfully created with the help of our application tools and the QCG (Quality in Cloud and Grid) middleware, in particular Vine Toolkit, QCG-Portal and QCG-Now, and make the use of HPC, Grid and Cloud more straightforward and transparent. Additionally, we share the best practices and lessons learned after creating jointly with user communities many domain-specific Science Gateways, e.g. dedicated for physicists, medical scientists, chemists, engineers and external communities performing multi-scale simulations. As our deployed software solutions have reached recently a critical mass of active users in the PLGrid e-infrastructure in Poland, we also discuss in this paper how changing technologies, visual design and user experience could impact the way we should re-design Science Getaways or even develop new attractive tools, e.g. desktop or mobile-based applications in the future. Finally, we present information and statistics regarding the behaviour of users to help readers understand how new capabilities and functionalities may influence the growth of user interest in Science Gateways and HPC technologies.

From Lesson Learned to the Refactoring of the DRIHM Science Gateway for Hydro-meteorological Research

A full hydro-meteorological (HM) simulation, from rainfall to impact on urban areas, is a multidisciplinary activity which consists in the execution of a workflow composed by complex and heterogeneous model engines. Moreover an extensive set of configuration parameters have to be selected consistently among the models, otherwise the simulation can fail or produce unreliable results. The DRIHM portal is a Web-based science gateway aiming to support HM researchers in designing, executing and managing HM simulations. The first version of the portal was developed during the DRIHM project using the gUSE science gateway toolkit. The lesson we learned is guiding a refactoring process that, together with a review of the most relevant technologies for the development of a science gateway, represent the focus of this paper. Beside the technological aspects, the need of a strong interplay between ICT and other domain-specific communities clearly emerged, together with coherent policies in the management of data, computational resources and software components that represent the ecosystem of a science gateways.

Portals and Web-Based Resources for Virtual Screening.

Virtual screening for active compounds has become an essential step within the drug development pipeline. The computer based prediction of compound binding modes is one of the most time and cost efficient methods for screening ligand libraries and enrich results of potential drugs. Here we present an overview about currently available online resources regarding compound databases, docking applications, and science gateways for drug discovery and virtual screening, in order to help structural biologists in choosing the best tools for their analysis. The appearance of the user interface, authentication and security aspects, data management, and computational performance will be discussed. We anticipate a broad overview about currently available solutions, guiding computational chemists and users from related fields towards scientifically reliable results.

A Meta-Brokering Framework for Science Gateways

Recently scientific communities produce a growing number of computation-intensive applications, which calls for the interoperation of distributed infrastructures including Clouds, Grids and private clusters. The European SHIWA and ER-flow projects have enabled the combination of heterogeneous scientific workflows, and their execution in a large-scale system consisting of multiple Distributed Computing Infrastructures. One of the resource management challenges of these projects is called parameter study job scheduling. A parameter study job of a workflow generally has a large number of input files to be consumed by independent job instances. In this paper we propose a meta-brokering framework for science gateways to support the execution of such workflows. In order to cope with the high uncertainty and unpredictable load of the utilized distributed infrastructures, we introduce the so called resource priority services. These tools are capable of determining and dynamically updating priorities of the available infrastructures to be selected for job instances. Our evaluations show that this approach implies an efficient distribution of job instances among the available computing resources resulting in shorter makespan for parameter study workflows.

The Essential Components of a Successful Galaxy Service

Driven by advances in data generation technologies and fuelled by radical reduction in costs, genomics has become a data science. Nonetheless the field of genomics has been restrained by the ability to analyse data. Science gateways, such as Galaxy, have the potential to enable bench biologists to analyse their own data without needing be familiar with the command line. Implementing a production scale Galaxy service, sufficiently well-featured and resourced to meet the needs of the end-users, is a significant undertaking and requires the consideration and combination of a number of factors to be successfully adopted by the community. In this paper, we describe the process that we undertook to implement a Galaxy service and describe what we consider to be the essential components of such a service. Our experience and insights will be of interest to those who are planning on implementing a science gateway service in a research organisation.

Developing science gateways for drug discovery in a grid environment.

BackgroundMethods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources.ResultsTo this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows.ConclusionsOur implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.

Science gateways community institute

Science gateways community institute

Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud

Cloud computing offers massive scalability and elasticity required by many scientific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new opportunities for application developers. This paper investigates how workflow systems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.

Metadata Management in the MoSGrid Science Gateway - Evaluation and the Expansion of Quantum Chemistry Support

Science gateways are employed to hide increasingly complex IT infrastructures from users via easy-to-use graphical interfaces while enabling IT-driven research not possible before. The science gateway MoSGrid (Molecular Simulation Grid) is a valuable and user-friendly workbench to submit and process molecular simulation studies on a large scale. With regard to the needs of the users, we focus on the interoperability of simulations using two prominent quantum chemical codes, Gaussian09 and NWChem. At a first glimpse, the definition of functionals and basis sets seems to be sufficient to evoke the same type of calculation in both codes using the quantum chemical workflows in MoSGrid. In more detail, this is not true and more aspects such as integration grids, convergence criteria and basis set dimensions have to be well defined in order to obtain a trustworthy comparability between quantum chemical codes. In previous work, these details have not been defined and included in the MSML (Molecular Simulation Markup Language) implementation within MoSGrid. After the investigation presented here, all these details can be integrated to extend the quantum chemical workflows in MoSGrid. Furthermore, a performance evaluation of the underlying metadata management is performed to investigate its suitability and scalability to the MSML extension.

Neuroscience Gateway � Cyberinfrastructure Providing Supercomputing Resources for Large Scale Computational Neuroscience Research

Neuroscience Gateway � Cyberinfrastructure Providing Supercomputing Resources for Large Scale Computational Neuroscience Research

Community Science Exemplars in SEAGrid Science Gateway: Apache Airavata Based Implementation of Advanced Infrastructure

We describe the science discovered by some of the community of researchers using the SEAGrid Science gateway. Specific science projects to be discussed include calcium carbonate and bicarbonate hydrochemistry, mechanistic studies of redox proteins and diffraction modeling of metal and metal-oxide structures and interfaces. The modeling studies involve a variety of ab initio and molecular dynamics computational techniques and coupled execution of a workflows using specific set of applications enabled in the SEAGrid Science Gateway. The integration of applications and resources that enable workflows that couple empirical, semi-empirical, ab initio DFT, and Moller-Plesset perturbative models and combine computational and visualization modules through a single point of access is now possible through the SEAGrid gateway. Integration with the Apache Airavata infrastructure to gain a sustainable and more easily maintainable set of services is described. As part of this integration we also provide a web browser based SEAGrid Portal in addition to the SEAGrid rich client based on the previous GridChem client. We will elaborate the services and their enhancements in this process to exemplify how the new implementation will enhance the maintainability and sustainability. We will also provide exemplar science workflows and contrast how they are supported in the new deployment to showcase the adoptability and user support for services and resources.

Citizen science in risk communication in the era of ICT

SummaryRisk communication is the exchange of information among stakeholders about an impending disaster and its risks to help individuals take appropriate actions to mitigate hazard impacts. While traditional risk communication follows a command and control structure such that information from hierarchical and vertically integrated organizations is disseminated to broader community, social media uses a decentralized, collaborative, and network based communication approach. The growth of information and communication technologies has made social media a popular channel for disseminating alert and warning messages both by citizens and agencies. However, social media suffers from spreading rumors and hoaxes. To minimize rumors and increase citizen communication, a science gateway (Cyber‐Infrastructure for GeoInformatics and Community Resilience) has been deployed. This gateway, resulted from a research conducted along the Mississippi Gulf Coast communities, incorporates citizen science to evaluate warning message sources, message contents and dissemination channels to increase public response to warnings. This gateway built on the social construct of risk communication provides opportunities to citizens to share data and information about a hazard, and participate in building community resilience. Copyright © 2015 John Wiley & Sons, Ltd.

Failure analysis and prediction for the CIPRES science gateway

SummaryScience gateways promote collaboration among researchers by providing them with access to community‐developed tools and data collections. The Cyberinfrastructure for Phylogenetic Research (CIPRES) science gateway is one of the most popular gateways, with approximately 3000 active users since 2012, and the user base is growing each year. While increasing the number of compute resources available to CIPRES would address their growth needs, it also introduces additional complexity as the likelihood of failure increases. In this paper, we analyze historical job data from CIPRES and combine it with historical software and services monitoring data to create a machine learning model to predict where a user's job will complete successfully on resources. At one operating point of our classifier, we are able to detect 50% of jobs that will fail with a false detection rate less than 5%. In 2014, accurately predicting 50% of CIPRES job failures and redirecting them to other resources would have resulted in 900K compute core hours saved, furthering phylogenetic research. These statistical models will also be used as a base to build a more generic automated monitoring analysis service for science gateways. Copyright © 2015 John Wiley & Sons, Ltd.

Science gateway workshops 2014 special issue conference publications

Science gateway workshops 2014 special issue conference publications

Lessons learned implementing a science gateway for hydro‐meteorological research

SummaryA full hydrometeorological (HM) simulation, from rainfall to impact on urban areas, is a multidisciplinary job, which relies on the execution of a workflow composed of complex and heterogeneous model engines. Moreover, the accuracy of the simulation is strongly dependent on an extensive set of configuration parameters, which have to be selected in a consistent way among the models. Within the Distributed Research Infrastructure for Hydro‐Meteorology project, a Web‐based science gateway was developed with the aim to support HM researchers in designing, executing, and managing HM experiments. The core of this science gateway is the portal, which takes care of generating all the configuration files and handles the execution of simulation steps on a heterogeneous computing infrastructure composed of high‐performance computing, Grid resources, and Cloud resources. This paper presents technological insights about the implementation of the portal, with an analysis of the adopted technologies and infrastructures. Our experience highlights the need of coherent policies in the management of data, computational resources, and software components that represent the ecosystem to develop science gateways. Copyright © 2015 John Wiley & Sons, Ltd.