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Journal articles on the topic 'Scientific Workflows Management Systems'

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1

Deelman, Ewa, Tom Peterka, Ilkay Altintas, et al. "The future of scientific workflows." International Journal of High Performance Computing Applications 32, no. 1 (2017): 159–75. http://dx.doi.org/10.1177/1094342017704893.

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Today’s computational, experimental, and observational sciences rely on computations that involve many related tasks. The success of a scientific mission often hinges on the computer automation of these workflows. In April 2015, the US Department of Energy (DOE) invited a diverse group of domain and computer scientists from national laboratories supported by the Office of Science, the National Nuclear Security Administration, from industry, and from academia to review the workflow requirements of DOE’s science and national security missions, to assess the current state of the art in science wo
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Talia, Domenico. "Workflow Systems for Science: Concepts and Tools." ISRN Software Engineering 2013 (January 8, 2013): 1–15. http://dx.doi.org/10.1155/2013/404525.

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The wide availability of high-performance computing systems, Grids and Clouds, allowed scientists and engineers to implement more and more complex applications to access and process large data repositories and run scientific experiments in silico on distributed computing platforms. Most of these applications are designed as workflows that include data analysis, scientific computation methods, and complex simulation techniques. Scientific applications require tools and high-level mechanisms for designing and executing complex workflows. For this reason, in the past years, many efforts have been
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Deelman, Ewa, Anirban Mandal, Ming Jiang, and Rizos Sakellariou. "The role of machine learning in scientific workflows." International Journal of High Performance Computing Applications 33, no. 6 (2019): 1128–39. http://dx.doi.org/10.1177/1094342019852127.

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Machine learning (ML) is being applied in a number of everyday contexts from image recognition, to natural language processing, to autonomous vehicles, to product recommendation. In the science realm, ML is being used for medical diagnosis, new materials development, smart agriculture, DNA classification, and many others. In this article, we describe the opportunities of using ML in the area of scientific workflow management. Scientific workflows are key to today’s computational science, enabling the definition and execution of complex applications in heterogeneous and often distributed enviro
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Littauer, Richard, Karthik Ram, Bertram Ludäscher, William Michener, and Rebecca Koskela. "Trends in Use of Scientific Workflows: Insights from a Public Repository and Recommendations for Best Practice." International Journal of Digital Curation 7, no. 2 (2012): 92–100. http://dx.doi.org/10.2218/ijdc.v7i2.232.

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Scientific workflows are typically used to automate the processing, analysis and management of scientific data. Most scientific workflow programs provide a user-friendly graphical user interface that enables scientists to more easily create and visualize complex workflows that may be comprised of dozens of processing and analytical steps. Furthermore, many workflows provide mechanisms for tracing provenance and methodologies that foster reproducible science. Despite their potential for enabling science, few studies have examined how the process of creating, executing, and sharing workflows can
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Bukhari, S. Sabahat H., and Yunni Xia. "A Novel Completion-Time-Minimization Scheduling Approach of Scientific Workflows Over Heterogeneous Cloud Computing Systems." International Journal of Web Services Research 16, no. 4 (2019): 1–20. http://dx.doi.org/10.4018/ijwsr.2019100101.

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The cloud computing paradigm provides an ideal platform for supporting large-scale scientific-workflow-based applications over the internet. However, the scheduling and execution of scientific workflows still face various challenges such as cost and response time management, which aim at handling acquisition delays of physical servers and minimizing the overall completion time of workflows. A careful investigation into existing methods shows that most existing approaches consider static performance of physical machines (PMs) and ignore the impact of resource acquisition delays in their schedul
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Deelman, Ewa, Christopher Carothers, Anirban Mandal, et al. "PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows." International Journal of High Performance Computing Applications 31, no. 1 (2016): 4–18. http://dx.doi.org/10.1177/1094342015594515.

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Computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Thus, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow managem
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Jackson, Michael, Kostas Kavoussanakis, and Edward W. J. Wallace. "Using prototyping to choose a bioinformatics workflow management system." PLOS Computational Biology 17, no. 2 (2021): e1008622. http://dx.doi.org/10.1371/journal.pcbi.1008622.

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Workflow management systems represent, manage, and execute multistep computational analyses and offer many benefits to bioinformaticians. They provide a common language for describing analysis workflows, contributing to reproducibility and to building libraries of reusable components. They can support both incremental build and re-entrancy—the ability to selectively re-execute parts of a workflow in the presence of additional inputs or changes in configuration and to resume execution from where a workflow previously stopped. Many workflow management systems enhance portability by supporting th
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McPhillips, Timothy, Tianhong Song, Tyler Kolisnik, et al. "YesWorkflow: A User-Oriented, Language-Independent Tool for Recovering Workflow Information from Scripts." International Journal of Digital Curation 10, no. 1 (2015): 298–313. http://dx.doi.org/10.2218/ijdc.v10i1.370.

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Scientific workflow management systems offer features for composing complex computational pipelines from modular building blocks, executing the resulting automated workflows, and recording the provenance of data products resulting from workflow runs. Despite the advantages such features provide, many automated workflows continue to be implemented and executed outside of scientific workflow systems due to the convenience and familiarity of scripting languages (such as Perl, Python, R, and MATLAB), and to the high productivity many scientists experience when using these languages. YesWorkflow is
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Kukla, Tamas, Tamas Kiss, Peter Kacsuk, and Gabor Terstyanszky. "Integrating Open Grid Services Architecture Data Access and Integration with computational Grid workflows." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1897 (2009): 2521–32. http://dx.doi.org/10.1098/rsta.2009.0040.

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Although many scientific applications rely on data stored in databases, most workflow management systems are not capable of establishing database connections during workflow execution. For this reason, e-Scientists have to use different tools before workflow submission to access their datasets and gather the required data on which they want to carry out computational experiments. Open Grid Services Architecture Data Access and Integration (OGSA-DAI) is a good candidate to use as middleware providing access to several structured and semi-structured database products through Web/Grid services. T
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Butt, Anila Sahar, and Peter Fitch. "A provenance model for control-flow driven scientific workflows." Data & Knowledge Engineering 131-132 (January 2021): 101877. http://dx.doi.org/10.1016/j.datak.2021.101877.

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11

Shiroor, Amruta, John Springer, Thomas Hacker, Brandeis Marshall, and Jeffrey Brewer. "Scientific workflow management systems and workflow patterns." International Journal of Business Process Integration and Management 5, no. 1 (2010): 63. http://dx.doi.org/10.1504/ijbpim.2010.033175.

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Prakash, Vijay, Seema Bawa, and Lalit Garg. "Multi-Dependency and Time Based Resource Scheduling Algorithm for Scientific Applications in Cloud Computing." Electronics 10, no. 11 (2021): 1320. http://dx.doi.org/10.3390/electronics10111320.

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Workflow scheduling is one of the significant issues for scientific applications among virtual machine migration, database management, security, performance, fault tolerance, server consolidation, etc. In this paper, existing time-based scheduling algorithms, such as first come first serve (FCFS), min–min, max–min, and minimum completion time (MCT), along with dependency-based scheduling algorithm MaxChild have been considered. These time-based scheduling algorithms only compare the burst time of tasks. Based on the burst time, these schedulers, schedule the sub-tasks of the application on sui
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Kataraki, Kirankumar V., and Sumana Maradithaya. "Power-Aware Mechanism for Scheduling Scientific Workflows in Cloud Environment." International Journal of Information System Modeling and Design 12, no. 1 (2021): 22–38. http://dx.doi.org/10.4018/ijismd.2021010102.

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Cloud computing is a platform that hosts various services and applications for users and businesses to access computing as a service. Cloud provider offers two distinct types of plans: reserved service and on-demand service. Cloud resources need to be allocated efficiently, and task needs to be scheduled efficiently such that the performance can be enhanced. In this research work, the authors have proposed a novel mechanism named PAMP (performance aware mechanism for parallel computation) for scheduling scientific workflows. At first, the resources are allocated using the optimal resource allo
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Memon, Shahbaz, Dorothée Vallot, Thomas Zwinger, et al. "Scientific workflows applied to the coupling of a continuum (Elmer v8.3) and a discrete element (HiDEM v1.0) ice dynamic model." Geoscientific Model Development 12, no. 7 (2019): 3001–15. http://dx.doi.org/10.5194/gmd-12-3001-2019.

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Abstract. Scientific computing applications involving complex simulations and data-intensive processing are often composed of multiple tasks forming a workflow of computing jobs. Scientific communities running such applications on computing resources often find it cumbersome to manage and monitor the execution of these tasks and their associated data. These workflow implementations usually add overhead by introducing unnecessary input/output (I/O) for coupling the models and can lead to sub-optimal CPU utilization. Furthermore, running these workflow implementations in different environments r
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Ngu, Anne H. H., Arwa Jamnagarwala, George Chin Jr., Chandrika Sivaramakrishnan, and Terence Critchlow. "Context-aware scientific workflow systems using KEPLER." International Journal of Business Process Integration and Management 5, no. 1 (2010): 18. http://dx.doi.org/10.1504/ijbpim.2010.033172.

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Holl, Sonja, Olav Zimmermann, Magnus Palmblad, Yassene Mohammed, and Martin Hofmann-Apitius. "A new optimization phase for scientific workflow management systems." Future Generation Computer Systems 36 (July 2014): 352–62. http://dx.doi.org/10.1016/j.future.2013.09.005.

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Khouri, Adilson Lopes, and Luciano Antonio Digiampietri. "Combining Artificial Intelligence, Ontology, and Frequency-based Approaches to Recommend Activities in Scientific Workflows." Revista de Informática Teórica e Aplicada 25, no. 1 (2018): 39. http://dx.doi.org/10.22456/2175-2745.75048.

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The number of activities provided by scientific workflow management systems is large, which requires scientists to know many of them to take advantage of the reusability of these systems. To minimize this problem, the literature presents some techniques to recommend activities during the scientific workflow construction. In this paper we specified and developed a hybrid activity recommendation system considering information on frequency, input and outputs of activities and ontological annotations. Additionally, this paper presents a modeling of activities recommendation as a classification pro
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Stanstrup, Jan, Corey Broeckling, Rick Helmus, et al. "The metaRbolomics Toolbox in Bioconductor and beyond." Metabolites 9, no. 10 (2019): 200. http://dx.doi.org/10.3390/metabo9100200.

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Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The progr
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Li, Zhongjin, Victor Chang, Haiyang Hu, Hua Hu, Chuanyi Li, and Jidong Ge. "Real-time and dynamic fault-tolerant scheduling for scientific workflows in clouds." Information Sciences 568 (August 2021): 13–39. http://dx.doi.org/10.1016/j.ins.2021.03.003.

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20

Austin, Timothy, Kyriaki Bei, Theodoros Efthymiadis, and Elias P. Koumoulos. "Lessons Learnt from Engineering Science Projects Participating in the Horizon 2020 Open Research Data Pilot." Data 6, no. 9 (2021): 96. http://dx.doi.org/10.3390/data6090096.

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Trends in the sciences are indicative of data management becoming established as a feature of the mainstream research process. In this context, the European Commission introduced an Open Research Data pilot at the start of the Horizon 2020 research programme. This initiative followed the success of the Open Access pilot implemented in the prior (FP7) research programme, which thereafter became an integral component of Horizon 2020. While the Open Access phenomenon can reasonably be argued to be one of many instances of web technologies disrupting established business models (namely publication
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Assimakopoulos, Nikitas A. "Workflow management with systems approach: anticipated and ad-hoc workflow for scientific applications." ISA Transactions 39, no. 2 (2000): 153–67. http://dx.doi.org/10.1016/s0019-0578(00)00014-8.

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22

Liu, Xiao, Zhiwei Ni, Jinjun Chen, and Yun Yang. "A probabilistic strategy for temporal constraint management in scientific workflow systems." Concurrency and Computation: Practice and Experience 23, no. 16 (2011): 1893–919. http://dx.doi.org/10.1002/cpe.1739.

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23

McClatchey, R., and G. Vossen. "Workshop on workflow management in scientific and engineering applications—report." ACM SIGMOD Record 26, no. 4 (1997): 49–53. http://dx.doi.org/10.1145/271074.271087.

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24

Liu, Ji, Esther Pacitti, Patrick Valduriez, and Marta Mattoso. "A Survey of Data-Intensive Scientific Workflow Management." Journal of Grid Computing 13, no. 4 (2015): 457–93. http://dx.doi.org/10.1007/s10723-015-9329-8.

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25

Yung, Kai Leung, Ming Gao, An Liu, Wai Hung Ip, and Shancheng Jiang. "Colored Petri Net-Based Verification and Improvement of Time-Sensitive Single-Unit Manufacturing for the Soil Preparation Instrument of Space Missions." Discrete Dynamics in Nature and Society 2020 (August 25, 2020): 1–18. http://dx.doi.org/10.1155/2020/2162869.

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Various space missions, including the Russian and Chinese interplanetary exploration collaboration in 2011 and the Phobos-Grunt space project to be relaunched by the Chinese in 2025, carry a soil preparation system (SOPSYS), which is an instrument used for scientific experiments. The design and manufacture of this precision instrument require stringent manufacturing processes and workflow of the highest quality, with every process in the project carefully monitored and controlled. All processes should be completed within the deadline so that the space project can be launched at the scheduled t
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Li, Zhongjin, Jidong Ge, Haiyang Hu, Wei Song, Hao Hu, and Bin Luo. "Cost and Energy Aware Scheduling Algorithm for Scientific Workflows with Deadline Constraint in Clouds." IEEE Transactions on Services Computing 11, no. 4 (2018): 713–26. http://dx.doi.org/10.1109/tsc.2015.2466545.

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Cui Lin, Shiyong Lu, Xubo Fei, et al. "A Reference Architecture for Scientific Workflow Management Systems and the VIEW SOA Solution." IEEE Transactions on Services Computing 2, no. 1 (2009): 79–92. http://dx.doi.org/10.1109/tsc.2009.4.

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28

Lim, Chunhyeok, Shiyong Lu, Artem Chebotko, Farshad Fotouhi, and Andrey Kashlev. "OPQL: Querying scientific workflow provenance at the graph level." Data & Knowledge Engineering 88 (November 2013): 37–59. http://dx.doi.org/10.1016/j.datak.2013.08.008.

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Igor, Mandrichenko. "MetaCat - metadata catalog for data management systems." EPJ Web of Conferences 251 (2021): 02048. http://dx.doi.org/10.1051/epjconf/202125102048.

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Metadata management is one of three major areas of scientific data management along with replica management and workflow management. Metadata is the information describing the data stored in a data item, a file or an object. It includes the data item provenance, recording conditions, format and other attributes. MetaCat is a metadata management database designed and developed for High Energy Physics experiments. As a component of a data management system, it’s main objectives are to provide efficient metadata storage and management and fast data selection functionality. MetaCat is required to
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Olsson, Tjelvar S. G., and Matthew Hartley. "Lightweight data management with dtool." PeerJ 7 (March 7, 2019): e6562. http://dx.doi.org/10.7717/peerj.6562.

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The explosion in volumes and types of data has led to substantial challenges in data management. These challenges are often faced by front-line researchers who are already dealing with rapidly changing technologies and have limited time to devote to data management. There are good high-level guidelines for managing and processing scientific data. However, there is a lack of simple, practical tools to implement these guidelines. This is particularly problematic in a highly distributed research environment where needs differ substantially from group to group and centralised solutions are difficu
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Assimakopoulos, N. A. "Erratum: Workflow management with systems approach: anticipated and ad-hoc workflow for scientific applications [ISA Trans. 39, 153-167 (2000)]." ISA Transactions 41, no. 2 (2002): 271. http://dx.doi.org/10.1016/s0019-0578(07)60086-x.

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Stefanelli, M. "Knowledge Management In Health Care Organizations." Yearbook of Medical Informatics 13, no. 01 (2004): 144–55. http://dx.doi.org/10.1055/s-0038-1638198.

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Abstract:This review article analyzes theories, methods, and technologies that can be effective in building a socio-technical environment within a health care organization that is able to facilitate the collaboration between individuals in the management of patient care and in expanding scientific and professional knowledge. The article is organized as follows. In section 2, I discuss the nature of knowledge in general and with a particular attention to medical knowledge. The future of health information systems (HIS) is discussed in section 3, which provides also an overview of theories for d
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Fitzgerald, Gerry, and Jim Swanson. "Measuring the effects of laboratory automation: The power of empirically derived models." Journal of Automatic Chemistry 14, no. 2 (1992): 55–57. http://dx.doi.org/10.1155/s1463924692000130.

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Laboratory data systems are automated for a variety of scientific and management reasons. A key part to maintaining these systems is to regularly assess the impact that automation has had on the laboratory and the organization as a whole. Smith Kline Beecham R&D is using a number of different types of measurement, as well as a number of different tools, for measuring how automated laboratory systems are affecting the workflow and information flow in the laboratory. This targeted programme of metrics has increased management confidence in laboratory automation efforts, helped anticipate dat
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Borsuk, N. A., V. A. Fedorova, and A. D. Minina. "Efficiency of documentation flow at scientific and engineering enterprises." Radio industry 28, no. 3 (2018): 99–106. http://dx.doi.org/10.21778/2413-9599-2018-28-3-99-106.

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A choice of a suitable document management automation system often becomes a highly complicated task. Such systems are currently available in big variety. Apart from that, each enterprise has its own specifics, while small and medium-sized scientific & engineering enterprises have also a wide range of small-scale orders. The purpose of the article is to demonstrate a reasonable approach to the choice of a document management system to be efficient for a particular enterprise. The expediency is showed for creating a uniform information space for data exchange at a scientific & engineeri
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Pinnick, Jaana. "Exploring digital preservation requirements." Records Management Journal 27, no. 2 (2017): 175–91. http://dx.doi.org/10.1108/rmj-04-2017-0009.

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Purpose The aim of this paper was to explore digital preservation requirements within the wider National Geoscience Data Centre (NGDC) organisational framework in preparation for developing a preservation policy and integrating associated preservation workflows throughout the existing research data management processes. This case study is based on an MSc dissertation research undertaken at Northumbria University. Design/methodology/approach This mixed methods case study used quantitative and qualitative data to explore the preservation requirements and triangulation to strengthen the design va
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Mkrtchyan, Tigran, Olufemi Adeyemi, Vincent Garonne, et al. "dCache - Keeping up With the Evolution of Science." EPJ Web of Conferences 245 (2020): 04039. http://dx.doi.org/10.1051/epjconf/202024504039.

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The dCache project provides open-source software deployed internationally to satisfy ever more demanding storage requirements of various scientific communities. Its multifaceted approach provides an integrated way of supporting different use-cases with the same storage, from high throughput data ingest, through wide access and easy integration with existing systems, including event driven workflow management. With this presentation, we will show some of the recent developments that optimize data management and access to maximise the gain from stored data.
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Korkhov, Vladimir, Dmitry Vasyunin, Adianto Wibisono, et al. "VLAM-G: Interactive Data Driven Workflow Engine for Grid-Enabled Resources." Scientific Programming 15, no. 3 (2007): 173–88. http://dx.doi.org/10.1155/2007/812036.

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Grid brings the power of many computers to scientists. However, the development of Grid-enabled applications requires knowledge about Grid infrastructure and low-level API to Grid services. In turn, workflow management systems provide a high-level environment for rapid prototyping of experimental computing systems. Coupling Grid and workflow paradigms is important for the scientific community: it makes the power of the Grid easily available to the end user. The paradigm of data driven workflow execution is one of the ways to enable distributed workflow on the Grid. The work presented in this p
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Tikhonova, Irina. "Problems of Electronic Workflow Application in Accounting." Известия Байкальского государственного университета 28, no. 3 (2018): 452–60. http://dx.doi.org/10.17150/2500-2759.2018.28(3).452-460.

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Information technologies in accounting are widely used inside the company and also when dealing with other companies and regulatory bodies. Switch to paperless workflow in accounting is promising and profitable for all the participants. Whereas analysis of contemporary scientific publications shows absence of basic terms of electronic document management, gaps in legislation, inconsistency of legal definitions. The article considers the evolution of the information accounting systems introduction, the definition and properties of an electronic document are analyzed, the criteria that allow equ
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Mondelli, Maria Luiza, Thiago Magalhães, Guilherme Loss, et al. "BioWorkbench: a high-performance framework for managing and analyzing bioinformatics experiments." PeerJ 6 (August 29, 2018): e5551. http://dx.doi.org/10.7717/peerj.5551.

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Advances in sequencing techniques have led to exponential growth in biological data, demanding the development of large-scale bioinformatics experiments. Because these experiments are computation- and data-intensive, they require high-performance computing techniques and can benefit from specialized technologies such as Scientific Workflow Management Systems and databases. In this work, we present BioWorkbench, a framework for managing and analyzing bioinformatics experiments. This framework automatically collects provenance data, including both performance data from workflow execution and dat
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Han, Ning, and Kun Huang. "DSEM-SW: a data-service enhanced scientific workflow middleware for cloud computing." International Journal of Networking and Virtual Organisations 24, no. 2 (2021): 126. http://dx.doi.org/10.1504/ijnvo.2021.10037254.

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Huang, Kun, and Ning Han. "DSEM-SW: a data-service enhanced scientific workflow middleware for cloud computing." International Journal of Networking and Virtual Organisations 24, no. 2 (2021): 126. http://dx.doi.org/10.1504/ijnvo.2021.114729.

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Zhang, Longxin, Liqian Zhou, and Ahmad Salah. "Efficient scientific workflow scheduling for deadline-constrained parallel tasks in cloud computing environments." Information Sciences 531 (August 2020): 31–46. http://dx.doi.org/10.1016/j.ins.2020.04.039.

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Wong, Ambrose H., Jessica M. Ray, Marc A. Auerbach, et al. "Study protocol for the ACT response pilot intervention: development, implementation and evaluation of a systems-based Agitation Code Team (ACT) in the emergency department." BMJ Open 10, no. 6 (2020): e036982. http://dx.doi.org/10.1136/bmjopen-2020-036982.

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IntroductionEmergency department (ED) visits for behavioural conditions are rising, with 1.7 million associated episodes of patient agitation occurring annually in acute care settings. When de-escalation techniques fail during agitation management, patients are subject to use of physical restraints and sedatives, which are associated with up to 37% risk of hypotension, apnoea and physical injuries. At the same time, ED staff report workplace violence due to physical assaults during agitation events. We recently developed a theoretical framework to characterise ED agitation, which identified te
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Araujo, Sabrina Magalhaes, Paulino Sousa, and Inês Dutra. "Clinical Decision Support Systems for Pressure Ulcer Management: Systematic Review." JMIR Medical Informatics 8, no. 10 (2020): e21621. http://dx.doi.org/10.2196/21621.

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Background The clinical decision-making process in pressure ulcer management is complex, and its quality depends on both the nurse's experience and the availability of scientific knowledge. This process should follow evidence-based practices incorporating health information technologies to assist health care professionals, such as the use of clinical decision support systems. These systems, in addition to increasing the quality of care provided, can reduce errors and costs in health care. However, the widespread use of clinical decision support systems still has limited evidence, indicating th
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Codarin, Sara. "Additive Manufacturing Technologies in Restoration: An Innovative Workflow for Interventions on Cultural Heritage." Cubic Journal, no. 3 (November 2020): 32–53. http://dx.doi.org/10.31182/cubic.2020.3.023.

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The current advancement of this research within the construction sector is the missing link for bridging the gap between the digitisation of building processes and the fabrication of architectural components. Renewed market needs and contemporary design languages require increasingly in-depth digital proficiency for the management of representation and production. The primary challenge of turning digital data into matter in the building design field must be overcome in order to demonstrate a possible transfer of benefits for new constructions, or interventions on existing buildings. The scient
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Mihalache, Marius Andrei, Gheorghe Nagit, and Marius Ionut Ripanu. "Integration of Modern Tools as Part of Concurrent Engineering in Mechanical Designs." Applied Mechanics and Materials 809-810 (November 2015): 1541–46. http://dx.doi.org/10.4028/www.scientific.net/amm.809-810.1541.

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The modern tools of today's concurrent engineering (CE) based management are a wide array of instruments, plans, software, technical skills, human capabilities and resources. This paper aims to emphasize the benefits of such a system implementation in a business environment based on case studies retrieved from scientific literature and author's personal experience in a private working environment. Constant team sessions, briefs, workshops and brainstorming sessions proved to be very powerful tools for the management teams subjected to these studies in order for them to develop fully stable con
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Manghi, Paolo, Michele Artini, Claudio Atzori, et al. "The D-NET software toolkit." Program 48, no. 4 (2014): 322–54. http://dx.doi.org/10.1108/prog-08-2013-0045.

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Purpose – The purpose of this paper is to present the architectural principles and the services of the D-NET software toolkit. D-NET is a framework where designers and developers find the tools for constructing and operating aggregative infrastructures (systems for aggregating data sources with heterogeneous data models and technologies) in a cost-effective way. Designers and developers can select from a variety of D-NET data management services, can configure them to handle data according to given data models, and can construct autonomic workflows to obtain personalized aggregative infrastruc
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48

Barisits, Martin, Fernando Barreiro, Thomas Beermann, et al. "The Data Ocean Project." EPJ Web of Conferences 214 (2019): 04020. http://dx.doi.org/10.1051/epjconf/201921404020.

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Transparent use of commercial cloud resources for scientific experiments is a hard problem. In this article, we describe the first steps of the Data Ocean R&D collaboration between the high-energy physics experiment ATLAS together with Google Cloud Platform, to allow seamless use of Google Compute Engine and Google Cloud Storage for physics analysis. We start by describing the three preliminary use cases that were identified at the beginning of the project. The following sections then detail the work done in the data management system Rucio and the workflow management systems PanDA and Har
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Дегтярьова, О. В. "ОРГАНІЗАЦІЙНО-ЕКОНОМІЧНИЙ МЕХАНІЗМ ПОБУДОВИ ПРОГНОЗІВ ВИРОБНИЧО-ГОСПОДАРСЬКОЇ ДІЯЛЬНОСТІ ПІДПРИЄМСТВ". TIME DESCRIPTION OF ECONOMIC REFORMS, № 3 (18 жовтня 2019): 6–14. http://dx.doi.org/10.32620/cher.2019.3.01.

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Formulation of the problem. For many decades, forecasting has been a debating issue, explained by the economic-historical context that defines the organizational and economic mechanism of forecasting. The purpose of the article is to develop an organizational and economic mechanism for making forecasts of production and economic activity of enterprises and to evaluate its effectiveness. The subject of the research is the organizational and economic mechanism for the construction of prognosis of industrial enterprises. The working hypothesis of the research includes the idea that the requiremen
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Ehrhardt, J., and H. Handels. "Medical Image Computing for Computer-supported Diagnostics and Therapy." Methods of Information in Medicine 48, no. 01 (2009): 11–17. http://dx.doi.org/10.3414/me9131.

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Summary Objectives: Medical image computing has become one of the most challenging fields in medical informatics. In image-based diagnostics of the future software assistance will become more and more important, and image analysis systems integrating advanced image computing methods are needed to extract quantitative image parameters to characterize the state and changes of image structures of interest (e.g. tumors, organs, vessels, bones etc.) in a reproducible and objective way. Furthermore, in the field of software-assisted and navigated surgery medical image computing methods play a key ro
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