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Enabling scientific workflow reuse through structured composition of dataflow and control-flow

Figure for Thought: River Systems are People Systems Too

Figure for Thought: River Systems are People Systems Too

A model for user-oriented data provenance in pipelined scientific workflows

Provenance in collection-oriented workflows

We describe a provenance model tailored to scientific workflows based on the collection-oriented modeling and design paradigm. Our implementation within the Kepler scientific workflow system captures the dependencies of data and collection creation events on preexisting data and collections, and embeds these provenance records within the data stream. A provenance query engine operates on self-contained workflow traces representing serializations of the output data stream for particular workflow runs. We demonstrate this approach in our response to the first provenance challenge.

Project histories: Managing data provenance across collection-oriented scientific workflow runs

While a number of scientific workflow systems support data provenance, they primarily focus on collecting and querying provenance for single workflow runs. Scientific research projects, however, typically involve (1) many interrelated workflows (where data from one or more workflow runs are selected and used as input to subsequent runs) and (2) tasks between workflow runs that cannot be fully automated. This paper addresses the need for recording data dependencies across multiple workflow runs and accommodating data management activities performed between runs.

Kepler/ppod: Scientific workflow and provenance support for assembling the tree of life

The complexity of scientific workflows for analyzing biological data creates a number of challenges for current workflow and provenance systems. This complexity is due in part to the nature of scientific data (e.g., heterogeneous, nested data collections) and the programming constructs required for automation (e.g., nested workflows, looping, pipeline parallelism). We present an extended version of the Kepler scientific workflow system to address these challenges, tailored for the systematics community.

A conceptual modeling framework for expressing observational data semantics

Observational data (i.e., data that records observations and measurements) plays a key role in many scientific disciplines. Observational data, however, are typically structured and described in ad hoc ways, making its discovery and integration difficult. The wide range of data collected, the variety of ways the data are used, and the needs of existing analysis applications make it impractical to define “one-size-fits-all” schemas for most observational data sets. Instead, new approaches are needed to flexibly describe observational data for effective discovery and integration.

The role of visual tools in a web application design and verification framework: A visual notation for LTL formulae

As the Web becomes a platform for implementing complex B2C and B2B applications, there is a need to extend Web conceptual modeling to process-centric applications. In this context, new problems about process safety and verification arise. Recent work has investigated high-level specification and verification of Web applications. This relies on a formal data-driven model of the application, which can access an underlying database as well as state information updated as the interaction progresses, and a set of user inputs.

Concept relationship editor: A visual interface to support the assertion of synonymy relationships between taxonomic classifications

NSF long term ecological research sites praxis et theoria - LTER information management and CS research