Understanding the utility and fitness of Workflow Provenance for Experiment Reporting Pınar Alper, Supervisor: Carole A. Goble 1.

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Scientific Workflows Lecture 15
Presentation transcript:

Understanding the utility and fitness of Workflow Provenance for Experiment Reporting Pınar Alper, Supervisor: Carole A. Goble 1

Local Data Local Data Local Tool Local Tool Results Data Research  Reporting Results Tool Analysis Results Data select recollect share package publish Build a citation string Package results by origin Document important run parameteres C. Tenopir, S. Allard, et al. Data sharing by scientists: Practices and perceptions. PLoS ONE, 6(6):e21101,

Provenance we have WF descriptionExecution provenance Prospective Retrospective Generic information: Data artefacts, consumption/production relations Execution times/status 3

Provenance that is reported – Origin – Methodological context – Scientific Context Scientific Data Provenance 4

Motifs D Garijo, P Alper, K Belhajjame, O Corcho, Y Gil, C Goble, Common motifs in scientific workflows: An empirical analysis, Future Generation Computer Systems. ISSN X. Minority (~30%) Data-creation Majority (~70%) Data-preparation (value-copying) Workflows as implementation artefacts: 240 Workflows, 4 Systems 10 domains A domain independent characterization of activities ~90% characterizable 5

Research Framework WF Summaries Labeling WF II III WF Motifs I Minimal additional design-time information High-level categorization, as Semantic Annotations Based on empirical evidence Process Model for labeling Motifs inform when to collect when to propagate labels Novelty: Dynamic, domain specific Novelty: Partial transparency Graph Re-write primitives Configurable filters More informed abstraction wMotifs Novelty: Declarative abstraction and contextual grouping 6 Grey-box Groundtruth –user behavior P Alper, K Belhajjame, C Goble, P Karagoz, Small Is Beautiful: Summarizing Scientific Workflows Using Semantic Annotations, IEEE Big Data, July P Alper, C Goble, and K Belhajjame On assisting scientific data curation in collection-based dataflows using labels. In Proceedings of the 8th Workshop on Workflows in Support of Large-Scale Science (WORKS '13). ACM, New York, NY, USA, DOI= /

How do I use Taverna Workbench scufl2-api make a wf Inquire about details Scufl2-wfdesc we operate on abstract wf description Issues Additional characteristics (port depths, itertion config) Annotation w key-value pairs List handling representation Resource uniqueness 7

Thank you! Carole A. GOBLE University of Manchester Khalid BELHAJJAME Université Paris Dauphine Pinar KARAGOZ Middle East Technical University Pinar ALPER University of Manchester 8