Converting scripts into reproducible workflow research objects
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1) The document presents a methodology to convert script-based experiments into reproducible workflow research objects (WROs). This addresses issues of understanding, reusing, and reproducing experiments conducted through scripts. 2) The methodology involves 5 steps: generate an abstract workflow, create an executable workflow, refine the workflow, record provenance data, and annotate and check the quality of the conversion. 3) Applying the methodology to a molecular dynamics simulation case study, the authors demonstrate how scripts can be transformed into WROs containing workflows, annotations, provenance data, and other resources needed for reproducibility.
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Van de boetes die door Brussel Fiscaliteit werden betekend in 2016, werden er datzelfde jaar 2 geïnd: 1 bij de maatschappij El Al (945 euro) en 1 bij Air Canada (4.170 euro).
Verder werden er volgens de Brusselse regering 12 boetes geïnd die in voorgaande jaren werden betekend: 1 bij Aerologic (1.570 euro) ; 1 bij Air Canada (5.580 euro) ; 1 bij Alitalia (785 euro) ; 2 bij DHL Bahrain (1.605 euro) ; 3 bij Sun Express (17.126 euro) ; 4 bij Tailwind (28.602 euro), hetzij 55.268 euro in totaal.
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Provenance witha purpose
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Privacy-Preserving Data Analysis Workflows for eScienceKhalid Belhajjame This document discusses an approach for preserving privacy in scientific workflows that use large datasets. It proposes using k-anonymity to anonymize sensitive workflow data. Parameter dependencies are leveraged to identify sensitive parameters and infer appropriate anonymity degrees. The approach was tested on 20 workflows, with overhead less than 1 millisecond. This preliminary work aims to assist scientists in anonymizing workflow data while enabling exploration of provenance and data products.
Irpb workshop
Irpb workshopKhalid Belhajjame - The document discusses evaluating "why-not" queries against scientific workflow provenance. Why-not queries help understand why a data item was not returned by a workflow execution.
- It proposes a solution for evaluating why-not queries in workflows with black-box modules that do not preserve attribute information from inputs. The solution explores workflow modules from sink to source to identify "picky" modules responsible for a data item not appearing in results.
- To identify picky modules, it harvests information from the web by searching for traces of scientific module invocations to find valid candidate inputs and determine if a module accepts them or is likely picky. It conducts an experiment using real workflows to test the effectiveness of
Aussois bda-mdd-2018
Aussois bda-mdd-2018Khalid Belhajjame The document discusses the significance of computational reproducibility in scientific research, emphasizing the limitations of traditional scholarly articles to convey the full spectrum of scientific knowledge, which extends beyond just findings to include data, protocols, and tools. It outlines a seminar that focuses on reproducibility within scientific workflows, defining key concepts such as repeatability, replicability, and reusability in both wet-lab and computational contexts. The document also highlights the challenges of maintaining reproducibility due to workflow decay and identifies potential solutions, like utilizing research objects and checklists to ensure comprehensive documentation and resource accessibility.
Anr cair meeting feb 2016
Anr cair meeting feb 2016Khalid Belhajjame The document discusses assisting designers in composing workflows through the reuse of frequent workflow fragments mined from repositories. It proposes an approach that involves mining fragments, representing workflows as graphs, homogenizing activity labels, and allowing users to search for fragments using keywords and activities from their initial workflow. Fragments are retrieved based on relevance to keywords and compatibility to specified activities, then ranked and presented to users for composition. Experiments assess different graph representations for mining fragments in terms of effectiveness, size and runtime. The approach aims to help designers reuse best practices from repositories when specifying new workflows.
Ikc 2015
Ikc 2015Khalid Belhajjame This document proposes a method to improve the reuse of workflow fragments by mining workflow repositories. It evaluates different graph representations of workflows and uses the SUBDUE algorithm to identify recurrent fragments. An experiment compares representations on precision, recall, memory usage, and time. Representation D1, which labels edges and nodes, performed best. A second experiment assesses how filtering workflows by keywords impacts finding relevant fragments for a user query. The method aims to incorporate workflow fragment search capabilities into the design lifecycle to promote reuse.
Linking the prospective and retrospective provenance of scripts
Linking the prospective and retrospective provenance of scriptsKhalid Belhajjame The document discusses the need for abstraction techniques to manage the complexity of provenance information generated during script execution in scientific data analysis. It presents various proposals and tools for integrating retrospective and prospective provenance, highlighting the limitations of existing systems like yesworkflow and noworkflow. The authors propose a method that links retrospective provenance to a more abstracted and user-defined prospective provenance while addressing identified issues in current tools.
Reproducibility 1
Reproducibility 1Khalid Belhajjame Khalid Belhajjame discusses the critical need for reproducibility in scientific research, particularly in computational studies, emphasizing that lack of proper documentation and reproducibility can lead to unreliable results. He outlines that replicability involves independent validation through clear reporting of methods and data, which is often hindered by high costs and the complexity of computational environments. The document presents various tools and workflows designed to enhance reproducibility in scientific practices, while also identifying common causes of workflow failure and the importance of maintaining accessible, clear metadata.
Introduction to ProvBench @ Provenance Week 2014
Introduction to ProvBench @ Provenance Week 2014Khalid Belhajjame ProvBench is an initiative aimed at publishing provenance information openly to create a reference corpus of provenance traces, with two editions held in 2013 and 2014. The 2014 edition included additional requirements for submissions and featured contributions on various provenance datasets and social networks. The document also discusses future tasks and maintenance for ProvBench.
Tapp 2014 (belhajjame)
Tapp 2014 (belhajjame)Khalid Belhajjame The document discusses a framework developed to enhance the precision of provenance in scientific workflows by generating possible data dependency models. It captures workflow execution events and employs techniques like workflow specifications and actor probing to infer dependencies between input and output ports. The framework addresses limitations in understanding dynamic dependencies and identifying input port dependencies, suggesting a need for further refinement in these areas.
Edbt2014 talk
Edbt2014 talkKhalid Belhajjame The document discusses a method for annotating the behavior of scientific modules using data examples, aiming to enhance understanding and comparison of these modules without relying on their specifications. By generating data examples based on the modules' input and output parameters utilizing domain ontologies, the method captures various behaviors of modules, allowing for effective evaluation and analysis. The study concludes that while the approach provides insights into module behavior, future work should focus on improving the conciseness of data examples and facilitating module composition based solely on these annotations.
Why Workflows Break
Why Workflows BreakKhalid Belhajjame The document discusses the issue of workflow decay in scientific research, emphasizing the importance of reproducibility and documenting workflows to preserve scientific methods. It identifies causes of decay, such as missing datasets and changes in execution environments, and proposes solutions like checklists and research objects to mitigate these issues. The authors highlight lessons learned for improving reproducibility in computational experiments and suggest future work focused on decay detection and collaboration with scientists.
D-prov use-case
D-prov use-caseKhalid Belhajjame The document discusses d-prov, a model designed to query and combine provenance traces from workflows executed in different systems like Taverna and VisTrails. It outlines a four-step approach for enacting workflows, exporting provenance traces, mapping them to d-prov, and then querying them. This use case demonstrates how users can effectively access and analyze results from equivalent workflows across distinct workflow systems.
Detecting Duplicate Records in Scientific Workflow Results
Detecting Duplicate Records in Scientific Workflow ResultsKhalid Belhajjame The document discusses a method for detecting duplicate records in datasets obtained from scientific workflows, highlighting the increase in data volume and complexity due to duplicates. It focuses on using provenance traces from workflow executions to guide duplicate detection, validating the approach with real-world bioinformatics workflows. The study identifies the importance of monitoring operation determinism to ensure effective duplicate detection across workflows.
Research Object Model in Sepublica
Research Object Model in SepublicaKhalid Belhajjame This document proposes representing scientific workflows as first-class citizens called research objects. It presents a model for workflow research objects that aggregates all necessary elements to understand an investigation. These include experiments, annotations, results, datasets and provenance. Research objects are encoded using semantic technologies like RDF and follow standards such as the Object Exchange model. The lifecycle of research objects is also described.
Case studyworkshoponprovenance
Case studyworkshoponprovenanceKhalid Belhajjame The document discusses the importance of research objects, which are comprehensive units encompassing data sets, tools, and results used in scientific investigations. It highlights the challenges in creating and publishing research objects, specifically addressing the need for effective provenance tracking to log scientific activities. The objective is to improve the process of capturing provenance, understanding its granularity, and defining the scope of research objects.
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Intégration incrémentale de données (Valenciennes juin 2010)Khalid Belhajjame Le document traite de l'intégration incrémentale de données en se concentrant sur l'importance des retours utilisateurs pour l'annotation, la sélection et le raffinement des mappings de données. Il propose un cadre pour améliorer la qualité des mappings en collectant des retours utilisateurs et en appliquant des techniques de raffinement, tout en soulignant que plus de retours utilisateurs augmentent la précision des annotations. Enfin, il met en avant la rentabilité du raffinement durant les premières itérations du processus.
Edbt 2010, Belhajjame
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Topic: Thoreau’s Influence on Gandhi: The Evolution of Civil Disobedience
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Converting scripts into reproducible workflow research objects
- 1. Converting Scripts into Reproducible Workflow Research Objects Lucas A. M. C. Carvalho, Khalid Belhajjame, Claudia Bauzer Medeiros [email protected] Baltimore, Maryland, USA October 23-26, 2016
- 2. 2 Background and Motivation ● Data-Intensive Experiments – Collection of scripts, programs and (big) data Papers
- 3. 3 Background and Motivation ● Data-Intensive Experiments – Collection of scripts, programs and (big) data Papers How to understand, reproduce or reuse data and models of experiments?
- 4. 4 Background and Motivation ● Data-Intensive Experiments – Collection of scripts, programs and (big) data Manual collection and organization of data provenance Papers How to understand, reproduce or reuse data and models of experiments?
- 5. 5 Background and Motivation ● Script-based experiments What are the inputs and outputs? How to change this local program for a similar web service? Example of script code. Difficult to understand, to reuse, and to reproduce.
- 6. 6 Background and Motivation ● Scientific Workflows Example of Scientific Workflow Management System.
- 9. 9 Create Understand Reuse Reproduce Overview + Step 2 Step 1 Step 3 Step 4 Step 5 Methodology
- 10. 10 Related Work ● Script-language specific. ● Workflow-engine specific. ● A new language is needed. ● Outcome is not an executable workflow. ● Do not collect provenance data of the conversion process.
- 11. 11 Two Kind of Experts ● Scientists – Domain experts who understand the experiment, and the script (sometimes called user); ● Curators: – Scientists who are also familiar with workflow and script programming or; – Computer scientists who are familiar enough with the domain to be able to implement our methodology; – Responsible for authoring, documenting and publishing workflows and associated resources.
- 12. 12 Requirements ● Produce workflow-like view of the script. ● Create an executable workflow and compare execution of workflow and script. ● Modify the workflow resources. ● Record provenance data. ● Aggregate all resources to support Reproducibility and Reuse. 1 2 3 4 5
- 13. 13 Requirements ● Produce workflow-like view of the script.1 Activity 1 Port 1 Port 2 Port 3 Port 1 Port 2 Activity 2 Port 3 Port 3 Activity n Port n Script-based experiment. Abstract workflow.
- 14. 14 Requirements ● Create executable workflow and compare execution of workflow and script. 2 Executable workflow. Script-based experiment.
- 15. 15 Requirements ● Modify the workflow resources.3 Local (a) (b) Algorithm A Algorithm B
- 16. 16 Requirements ● Record provenance data4 Activity 1 Output 1 Output 2 wasGeneratedBy wasGeneratedBy Sample used “2012-06-01” wasStartedAt Activity 2 used LucasWorkflow Run wasAssociatedWith used
- 17. 17 Requirements ● Aggregate all resources to support Reproducibility and Reuse. 5 Abstract workflows Concrete workflows Annotations Papers and Reports Provenance Authors Scripts Data
- 18. 18 Script Generate Abstract Workflow Generate Abstract Workflow Create an executable workflow Create an executable workflow Refine workflowRefine workflow Bundle Resources into a Research Object Bundle Resources into a Research Object Annotate and check quality Annotate and check quality Abstract workflow Concrete workflow 2 1 3 4 5 Methodology
- 19. 19 Workflow Research Object (WRO) ● Research Objects are semantically rich aggregations of resources that bring together data, methods and people in scientific investigations. ● WROs encapsulate scientific workflows and additional information regarding their context and resources. Research Object Model
- 20. 20 Running Example ● Molecular Dynamics Simulations – Many branches of material sciences, computational engineering, physics and chemistry. – Scripts (shell script), programs (NAMD, VMD, Fortran) – Phases: set up, simulation and analysis of trajectories. – Inputs: protein structure, simulation parameters and force field files. – Output: trajectories and analysis results.
- 22. 22 Step Generate Abstract Workflow 1 Manually annotate Script code. Annotated script code.
- 23. 23 Step Generate Abstract Workflow 1 Manually annotate Create workflow-like view Script code. Annotated script code. Abstract workflow.
- 24. 24 Step Generate Abstract Workflow 1 code blocks Input/ouput YesWorkflow McPhillips et. al, 2015 - Code comments - Tags: ● @begin ● @end ● @desc ● @in ● @out ● ... T. McPhillips et al. (2015), “Yesworkflow: A user-oriented, language- independent tool for recovering workflow information from scripts,” International Journal of Digital Curation, vol. 10, no. 1, pp. 298–313, 2015. Create Workflow-like view Abstract workflow. Annotated script code.
- 25. 25 Step Generate Abstract Workflow 1 Create Workflow-like view Abstract workflow. Annotated script code.
- 26. 26 Step Create an executable workflow 2 Abstract workflow.
- 27. 27 Step Create an executable workflow 2 Create implementation of activities Copy code blocks from the script. Abstract workflow. Executable workflow.
- 28. 28 Step Create an executable workflow 2 Create implementation of activities Copy code blocks from the script. Abstract workflow. Executable workflow.
- 29. 29 Step Create an executable workflow 2 Create implementation of activities Copy code blocks from the script. Abstract workflow. Executable workflow. Script code.
- 30. 30 Step Refine executable workflow 3 Modify resources: ● Algorithms ● Data Sets ● Parallelization ● Web Services ● ... Executable workflow. New workflow version.
- 31. 31 Step Refine executable workflow 3 Create new version Modify resources: ● Algorithms ● Data Sets ● Parallelization ● Web Services ● ... Executable workflow. New workflow version.
- 32. 32 Steps Record provenance data: execution traces. 2 3 wasEnactedBy split Output 1 Output 2 wasGeneratedBy wasGeneratedBy Sample used “2012-06-01” wasStartedAt psgen used LucasWorkflow Run wasAssociatedWith used hasSpecification W3C PROV Executable workflow.
- 33. 33 Steps Record provenance data: conversion process. 2 3 wasDerivedFrom wasDerivedFrom wasDerivedFrom wasAssociatedWith CuratorCurator W3C PROV Executable workflow. New workflow version. Script code.
- 34. 34 Step Annotate and check quality ● Annotations describing the workflow. ● Use provenance data – To check the quality of the conversion process. ● Run checks to verify the soundness of the workflow. 4
- 35. 35 Step Annotate and check quality 4 Script code. Executable workflow.
- 36. 36 Step Annotate and check quality 4 Workflow version. Initial Executable workflow.
- 37. 37 Step Annotate and check quality ● Common mistakes during the conversion: – not clearly identified the main logical processing units in the script; – a mistake when migrating script code into the corresponding activity; – not provided the correct input files and parameters; – the coding of the workflow itself contained errors. 4
- 38. 38 Step Bundle Resources into a Research Object 5 Script Abstract workflow Concrete workflow(s) Annotations Paper Provenance Data Attributions
- 39. 39 Contributions ● A methodology that guides curators in a principled manner to transform scripts into reproducible and reusable WRO; ● This addresses an important issue in the area of script provenance;
- 40. 40 Conclusions ● We addressed issues wrt understanding, reuse and reproducibility of script-based experiments. ● The methodology created was: – elaborated based on requirements; – showcased via a real world use case from the field of Molecular Dynamics; ● We exploited tools and standards from the scientific community: – Scientific Workflows, YesWorkflow, Research Objects, the W3C PROV recommendations and the Web Annotation Data Model. ● The bundle is available at http://w3id.org/w2share/s2rwro/
- 41. 41 Next Steps ● Evaluation using other case studies; ● Evaluation of the cost of the effectiveness of our methodology; ● Extension of YesWorkflow to support the semantic annotation of blocks; ● Implementation of tools.
- 42. 42 Acknowledgments ● FAPESP (grant # 2014/23861-4) ● CCES/CEPID (grant # 2013/08293-7) – Center for Computational Engineering & Sciences ● LIS (Laboratory of Information Systems) ● Prof. Munir Skaf and his group from Institute of Chemistry - Unicamp.
- 43. Converting Scripts into Reproducible Workflow Research Objects Lucas A. M. C. Carvalho, Khalid Belhajjame, Claudia Bauzer Medeiros [email protected] Baltimore, Maryland, USA October 23-26, 2016