A Provenance-Based Infrastructure to Support the Life Cycle of Executable Papers

Koop, David; Santos, Emanuele; Mates, Phillip; Vo, Huy T.; Bonnet, Philippe; Bauer, Bela; Surer, Brigitte; Troyer, Matthias; Williams, D. N.; Tohline, J. E.; Freire, Juliana; Silva, Cláudio T.

doi:10.1016/j.procs.2011.04.068

Cited by 40 publications

(25 citation statements)

References 11 publications

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“…However, little has been done to integrate provenance into the field of executable documents. The authors in [13] propose a provenance based infrastructure to support the executable document's life cycle, while in [14] the authors attempt to create paper publications with provenance embedded in them to describe appropriate data and results. However, in both these papers, the proposed designs depend strongly on a specific workflow system for executions and content reading.…”

Section: Related Workmentioning

confidence: 99%

DEEP: A Provenance-Aware Executable Document System

Yang

Michaelides

Charlton

et al. 2012

Lecture Notes in Computer Science

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Section: Related Workmentioning

confidence: 99%

DEEP: A Provenance-Aware Executable Document System

Yang

Michaelides

Charlton

et al. 2012

Lecture Notes in Computer Science

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“…While document preservation is a long standing research theme [21], computation (and therefore workflow) preservation 11 http://www.genome.jp/kegg/ is a relatively new topic, which has been gaining interest in the last few years. For example, the ACM SIGMOD repeatability effort which has been organized twice since 2008 set up as a goal to verify that the experiments published in the paper accepted at the conference are repeatable [12].…”

Section: Related Workmentioning

confidence: 99%

“…As a result, few systems have emerged for capturing computation in the form of workflows that can be shared and preserved. For example, Koop et al [11] have developed an infrastructure for capturing computations and experiments in the form of workflows that are managed using the VisTrails workflow systems. Frew et al [9] developed a system for collecting provenance that enable the specification of experiments and computations in the form of workflows.…”

Section: Related Workmentioning

confidence: 99%

Fostering Scientific Workflow Preservation through Discovery of Substitute Services

Belhajjame

Goble

Soiland‐Reyes

et al. 2011

2011 IEEE Seventh International Conference on eScience

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Abstract-Scientific workflows are increasingly gaining momentum as the new paradigm for modeling and enacting scientific experiments. The value of a workflow specification does not end once it is enacted. Indeed, workflow specifications encapsulate knowledge that documents scientific experiments, and are, therefore, worth preserving.Our experience suggests that workflow preservation is frequently hampered by the volatility of the constituent service operations when these operations are supplied by third-party providers. To deal with this issue, we propose a heuristic for locating substitutes that are able to replace unavailable service operations within workflows. The proposed method uses the data links connecting inputs and outputs of service operations in existing workflow specifications to locate operations with parameters compatible with those of the missing operations. Furthermore, it exploits provenance traces collected from past executions of workflows to ensure that candidate substitutes perform tasks similar to those of the missing operations. The effectiveness of the proposed method has been empirically assessed.

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“…In this approach the failures do not mean the failures of the Scientific Workflow Management System (SWfMS) but the correctness and the availability of the inputs, libraries, variables etc. Different users for different purposes may be interested in reproducing the workflow, for example the authors of the workflow(s) in order to prove their results, readers or other scientists in order to reuse the results or reviewers in order to verify the correctness of the results [1]. Additionally, nowadays scientific workflow repositories are already available and in this way the scientists can share their results with each other and even they can reuse the existing workflows to create new ones.…”

Section: Introductionmentioning

confidence: 99%

Classification of scientific workflows based on reproducibility analysis

Bánáti

Kacsuk

Kozlovszky

2016

2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

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-In the scientist's community one of the most vital challenges is the reproducibility of a workflow execution. The necessary parameters of the execution (we call them descriptors) can be external which depend on for example the computing infrastructure (grids, clusters and clouds), on third party resources or it can be internal which belong to the code of the workflow such as variables. Consequently, during the process of re-execution these parameters may change or become unavailable and finally they can prevent to reproduce the workflow. However in most cases the lack of the original parameters can be compensated by replacing, evaluating or simulating the value of the descriptors with some extra cost in order to make it reproducible. Our goal in this paper is to classify the scientific workflows based on the method and cost how they can become reproducible.

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A Provenance-Based Infrastructure to Support the Life Cycle of Executable Papers

Cited by 40 publications

References 11 publications

DEEP: A Provenance-Aware Executable Document System

DEEP: A Provenance-Aware Executable Document System

Fostering Scientific Workflow Preservation through Discovery of Substitute Services

Classification of scientific workflows based on reproducibility analysis

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