J. Bernsdorf, G. Berti, B. Chopard, J. Hegewald, M. Krafczyk, Dinan Wang, E. Lorenz, A. Hoekstra
{"title":"Towards Distributed Multiscale Simulation of Biological Processes","authors":"J. Bernsdorf, G. Berti, B. Chopard, J. Hegewald, M. Krafczyk, Dinan Wang, E. Lorenz, A. Hoekstra","doi":"10.1109/eScienceW.2011.19","DOIUrl":"https://doi.org/10.1109/eScienceW.2011.19","url":null,"abstract":"The understanding of biological processes, e.g. related to cardio-vascular disease and treatment, can significantly be improved by numerical simulation. In this paper, we present an approach for a multiscale simulation environment, applied for the prediction of in-stent re-stenos is. Our focus is on the coupling of distributed, heterogeneous hardware to take into account the different requirements of the coupled sub-systems concerning computing power. For such a concept, which is an extension of the standard multiscale computing approach, we want to apply the term Distributed Multiscale Computing.","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134263539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Hucka, Frank T. Bergmann, S. Keating, Lucian P. Smith
{"title":"A Profile of Today's SBML-Compatible Software","authors":"M. Hucka, Frank T. Bergmann, S. Keating, Lucian P. Smith","doi":"10.1109/ESCIENCEW.2011.28","DOIUrl":"https://doi.org/10.1109/ESCIENCEW.2011.28","url":null,"abstract":"Computational systems biologists today have a healthy selection of software resources to help them do research. Many software packages, especially those concerned with computational modeling, have adopted SBML (the Systems Biology Markup Language) as a machine-readable format to permit users to exchange models. Our group has a keen interest in understanding the landscape of SBML support. To help us ascertain the state of modern SBML-compatible software, in mid-2011 we initiated a survey of software packages that support SBML. Here we report the preliminary survey results. Based on 81 packages for which we have data so far, we summarize the trends in six areas: (1) What are the major types of functionality offered by the software systems? (2) What mathematical frameworks do they support? (3) What are their SBML-specific capabilities? (4) What other standards do they support besides SBML? (5) What are their characteristics with respect to run-time environments? And finally, (6) what are the availability and licensing terms?","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"265 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122079954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yong Liu, Pratch Piyawongwisal, Sahil Handa, Liang Yu, Yan Xu, Arjmand Samuel
{"title":"Going Beyond Citizen Data Collection with Mapster: A Mobile+Cloud Real-Time Citizen Science Experiment","authors":"Yong Liu, Pratch Piyawongwisal, Sahil Handa, Liang Yu, Yan Xu, Arjmand Samuel","doi":"10.1109/eScienceW.2011.23","DOIUrl":"https://doi.org/10.1109/eScienceW.2011.23","url":null,"abstract":"Citizens have always played an important role in emergency management such as urban flooding response. New information and communication technologies such as smart phones and computer-based social networks have great potential to transform the roles of citizens in emergency management. However, current digital citizen science projects are usually limited in three areas: 1) limited one-way citizen participation, 2) no processing and integration of citizens' reports with other existing infrastructure sensing data, 3) no personalized near-real-time spatiotemporal visualization tools for citizens to instantly view aggregated data to gain updated situational awareness. We developed a Mapster application that specifically addresses these issues. First, we leveraged Twitter's geo-referenced tweets functionality to design a customized smart phone application for citizens to report a set of events that have been identified in past urban flooding situations such as \"basement flooding\" and \"powerline down\" etc. Second, a Cloud-based semantic streaming data harvesting and processing tool was developed to fetch and process both the Twitter feeds and other infrastructure sensing data such as US National Weather Service's radar data. Third, a user can instantly explore the heterogeneous data processed and provided by the Cloud service through a map-based spatiotemporal animation tool on the smart phone to see how all the events evolve before, during, and after a storm. Such a two-way information flow significantly improves citizen participation and their sense of situational awareness. We present our architecture, implementation, and discussion of issues on citizen science data collection platforms, integration of heterogeneous data sources and future work plan.","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129018583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Katarzyna Rycerz, M. Nowak, P. Pierzchala, Eryk Ciepiela, D. Harezlak, M. Bubak
{"title":"Comparison of Cloud and Local HPC Approach for MUSCLE-based Multiscale Simulations","authors":"Katarzyna Rycerz, M. Nowak, P. Pierzchala, Eryk Ciepiela, D. Harezlak, M. Bubak","doi":"10.1109/eScienceW.2011.21","DOIUrl":"https://doi.org/10.1109/eScienceW.2011.21","url":null,"abstract":"In this paper we present and compare a support for setting up and execution of multiscale applications in the two types of infrastructures: local HPC cluster and Amazon AWS cloud solutions. We focus on applications based on the MUSCLE framework, where distributed single scale modules running concurrently form one multiscale application. We also integrate presented solution with Grid Space virtual laboratory that enables users to develop and execute virtual experiments on the underlying computational and storage resources through its website based interface. Last but not least, we present a design of a user friendly visual tool supporting application distribution.","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128584214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jeremy S. Logan, S. Klasky, J. Lofstead, H. Abbasi, S. Ethier, R. Grout, S. Ku, Qing Liu, Xiaosong Ma, M. Parashar, N. Podhorszki, K. Schwan, M. Wolf
{"title":"Skel: Generative Software for Producing Skeletal I/O Applications","authors":"Jeremy S. Logan, S. Klasky, J. Lofstead, H. Abbasi, S. Ethier, R. Grout, S. Ku, Qing Liu, Xiaosong Ma, M. Parashar, N. Podhorszki, K. Schwan, M. Wolf","doi":"10.1109/eScienceW.2011.26","DOIUrl":"https://doi.org/10.1109/eScienceW.2011.26","url":null,"abstract":"Massively parallel computations consist of a mixture of computation, communication, and I/O. Of these three components, implementing an effective parallel I/O solution has often been overlooked by application scientists and has typically been added to large scale simulations only when existing serial techniques have failed. As scientists' teams scaled their codes to run on hundreds of processors, it was common to call on an I/O expert to implement a set of more scalable I/O routines. These routines were easily separated from the calculations and communication, and in many cases, an I/O kernel was derived from the application which could be used for testing I/O performance independent of the application. These I/O kernels developed a life of their own used as a broad measure for comparing different I/O techniques. Unfortunately, as years passed and computation and communication changes required changes to the I/O, the separate I/O kernel used for benchmarking remained static, no longer providing an accurate indicator of the I/O performance of the simulation, and making I/O research less relevant for the application scientists. In this paper we describe a new approach to this problem where I/O kernels are replaced with skeletal I/O applications that are automatically generated from an abstract set of simulation I/O parameters. We realize this abstraction by leveraging the ADIOS [1] middleware's XML I/O specification with additional runtime parameters. Skeletal applications offer all of the benefits of I/O kernels including allowing I/O optimizations to focus on useful I/O patterns. Moreover, since they are automatically generated, it is easy to produce an updated I/O skeleton whenever the simulation's I/O changes. In this paper we analyze the performance of automatically generated I/O skeletal applications for the S3D and GTS codes. We show that these skeletal applications achieve performance comparable to that of the production applications. We wrap up the paper with a discussion of future changes to make the skeletal application better approximate the actual I/O performed in the simulation.","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121180643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Kelling, Jun Yu, Jeff Gerbracht, Weng-Keen Wong
{"title":"Emergent Filters: Automated Data Verification in a Large-Scale Citizen Science Project","authors":"S. Kelling, Jun Yu, Jeff Gerbracht, Weng-Keen Wong","doi":"10.1109/eScienceW.2011.13","DOIUrl":"https://doi.org/10.1109/eScienceW.2011.13","url":null,"abstract":"Research projects that use the efforts of volunteers (“citizen scientistsâ€) to collect data on organism occurrence must address issues of observer variability and species misidentification. While citizen science projects can engage a very large number of volunteers to collect volumes of data, they are prone to contain reporting errors. Our experience with eBird, a citizen science project that engages tens of thousands of volunteers to collect bird observations, has shown that a massive effort by volunteer experts is needed to screen data, identify outliers and flag them in the database. But the increasing volume of data being collected by eBird places a huge burden on these volunteer experts. In order to minimize this human effort, we explored whether previously collected eBird data can be used to create automated quality filters that emerge from the data. We do this through a two-step process. First a data-based method detects outliers (i.e., observations that are unusual for a given region and week of the year). Next, a novel machine learning method that estimates observer expertise is used to decide if the unusual observation should be flagged or not. Our preliminary findings indicate that this automated process reliably identifies outliers and accurately classifies them as either an error or represents a potentially valuable observation.","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123608715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"National Geographic FieldScope: A Collaboratory Geospatial Platform for Citizen Science","authors":"Eric Russell, Anna Switzer, Daniel C. Edelson","doi":"10.1109/eScienceW.2011.24","DOIUrl":"https://doi.org/10.1109/eScienceW.2011.24","url":null,"abstract":"We describe National Geographic Field Scope, an online platform for Citizen Science projects. The platform is designed to overcome several obstacles to the wider adoption of Citizen Science in science education, by providing technical infrastructure to Citizen Science projects at little to no cost, and by enabling learners to participate in the full scientific process by analyzing the data they collect. We describe the current state of the software and our plans for future development.","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121223726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yang Li, Matteo Harutunian, Nitesh Narayan, B. Brügge, G. Buse
{"title":"Requirements Engineering for Scientific Computing: A Model-Based Approach","authors":"Yang Li, Matteo Harutunian, Nitesh Narayan, B. Brügge, G. Buse","doi":"10.1109/eScienceW.2011.30","DOIUrl":"https://doi.org/10.1109/eScienceW.2011.30","url":null,"abstract":"Requirements engineering is crucial to the success of software development. However, in many scientific computing projects, traditional requirements engineering practices are ignored. We claim that there is a need for methodologies, which help capturing and managing requirements for these projects, to collaboratively develop scientific software with greater interoperability. We propose a model-based approach to elicit and manage requirements in scientific computing projects. The proposed approach is based on a meta-model in order to deal with the high complexity and frequent change in scientific software development. The meta-model also provides abstractions and notations targeted at scientific computing projects. The approach supports requirements engineering in these projects with the flexibility of easily managing requirements versioning, trace ability and communication across the boundary of disciplines. A tool prototype is implemented. To evaluate the proposed approach, we applied it in scientific computing projects. The approach has showed its advantages in the application and promotes software engineering in these projects.","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131064030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
W. Funika, Michal Janczykowski, Maciej Dudek, Arkadiusz Kuboszek, Konrad Jopek, Maciej Grzegorczyk
{"title":"Performance Monitoring and Analysis System for MUSCLE-based Applications in PL-Grid","authors":"W. Funika, Michal Janczykowski, Maciej Dudek, Arkadiusz Kuboszek, Konrad Jopek, Maciej Grzegorczyk","doi":"10.1109/eScienceW.2011.33","DOIUrl":"https://doi.org/10.1109/eScienceW.2011.33","url":null,"abstract":"In this paper we present a system for the monitoring of data flow and resources usage in applications running in the MUSCLE environment. While MUSCLE provides the ability of running complex experiments, it does not support any monitoring features. By combining the monitoring functionality supported by Sem Mon and Nagios, we are able to design and implement a system for gathering and visualizing important run-time data relating to application performance. Fluent experiment execution is highly dependable on real-time collecting and presenting essential information connected to task processing. Of particular importance for monitoring system users is that the use of the system should be as easy as possible with regard to storing, observing and interpreting the monitoring data. These features are enabled by introducing ontologies into the operation of the monitoring system. In addition to the conventional monitoring activities, using ontologies makes it possible to automate the process of reasoning on performance flaws and to easily change the focus of monitoring. In the paper we will focus on the concept and some implementation details of our monitoring system, assuming that an infrastructure to support the transport and storage of performance data on the usage of resources in MUSCLE-based applications should be transparent and lightweight.","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129782746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Towards Automatic Discovery of co-authorship Networks in the Brazilian Academic Areas","authors":"J. Mena-Chalco, R. M. C. Junior","doi":"10.1109/eScienceW.2011.31","DOIUrl":"https://doi.org/10.1109/eScienceW.2011.31","url":null,"abstract":"In Brazil, individual curricula vitae of academic researchers, that are mainly composed of professional information and scientific productions, are managed into a single software platform called Lattes. Currently, the information gathered from this platform is typically used to evaluate, analyze and document the scientific productions of Brazilian research groups. Despite the fact that the Lattes curricula has semi-structured information, the analysis procedure for medium and large groups becomes a time consuming and highly error-prone task. In this paper, we describe an extension of the script Lattés (an open-source knowledge extraction system from the Lattes platform), for analysing individuals Lattes curricula and automatically discover large-scale co-authorship networks for any academic area. Given some knowledge domain (academic area), the system automatically allows to identify researchers associated with the academic area, extract every list of scientific productions of the researchers, discretized by type and publication year, and for each paper, identify the co-authors registered in the Lattes Platform. The system also allows the generation of different types of networks which may be used to study the characteristics of academic areas at large scale. In particular, we explored the node's degree and Author Rank measures for each identified researcher. Finally, we confirm through experiments that the system facilitates a simple way to generate different co-authorship networks. To the best of our knowledge, this is the first study to examine large-scale co-authorship networks for any Brazilian academic area.","PeriodicalId":267737,"journal":{"name":"2011 IEEE Seventh International Conference on e-Science Workshops","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124045598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}