The document discusses workflows in computational contexts, defining them as task sets with dependencies, and differentiating them from standard computer programs. It highlights tools like YesWorkflow and Parsl for modeling and sharing workflows, along with platforms like GitHub and MyExperiment for collaboration and resource sharing. The paper emphasizes the importance of structured representation of workflows to facilitate understanding and reuse in scientific and computational environments.

1. National Center for Supercomputing Applications
University of Illinois at Urbana–Champaign
Expressing and sharing workflows
Daniel S. Katz
Assistant Director for Scientific Software & Applications, NCSA
Research Associate Professor, CS
Research Associate Professor, ECE
Research Associate Professor, iSchool
dskatz@illinois.edu, d.katz@ieee.org
@danielskatz

2. What’s a workflow?
• A set of tasks and dependencies between them
• Perhaps expressed as data structure, e.g. graph (DAG or cyclic)
• How is this different than a computer program?
• The tasks as more well-defined (inputs, outputs)
• The tasks are longer (running time O(sec) – O(hr))
• Why express it differently?
• Program (script) is a natural way of expressing a workflow
• Examples: shell scripts, programs in Swift/Parsl
• YesWorkflow annotations to help in understanding scripts
• Swift/Parsl: functions used to identify components
• Expressing it as data corresponds to the compiled (assembly)
version of the workflow
• Useful for a lot of things, but not understanding
http://swift-lang.org, http://parsl-project.org

3. YesWorkflow (YW)
• Name: “Yes, scripts are (can be) workflows, too!”
• But, workflow (dataflow) usually hidden in the script
• Idea: let the script author reveal the structure by
declaring tasks (steps) and dataflow between tasks.
• This is a modeling step
• very coarse (workflow: one big black box w/ inputs & outputs)
• or rather fine (workflow has many steps, linked by dataflow)
• => language to explain (graphically) what the concepts
(relevant steps, relevant data) you want to share
• => this conceptual YW model can itself be queried; linked
with runtime observables, provenance
Credit: Bertram Ludäscher

4. Parsl
• A python-based parallel scripting library (http://parsl-project.org),
based on ideas in Swift (http://swift-lang.org)
• Tasks exposed as functions (python or bash)
@App('bash', data_flow_kernel)
def echo(message, outputs=[]):
return 'echo {0} &> {outputs[0]}’
@App('python', data_flow_kernel)
def cat(inputs=[]):
with open(inputs[0]) as f:
return f.readlines()
• Return values are futures
• Other tasks can be called that depend on these futures
• Will not run until futures are satisfied/filled
• Main code used to glue functions together
hello = echo("Hello World!", outputs=['hello1.txt'])
message = cat(inputs=[hello.outputs[0]])
• Fairly easy to understand

5. How to promote/share workflows
• How do we share general software?
• Libraries (units of execution with well-defined APIs)
• Source code (fork model)
• Source code repositories (GitHub), packaging
systems/repositories (PyPI, CRAN)
• How do we share data?
• Repositories (Dryad)
• For workflows
• Libraries -> sub-workflows, defined to provide well-specified
functionality
• Source code -> source code (scripts), may still be hard to
understand
• Data -> data repository for workflows (MyExperiment)

6. www.myexperiment.org
De Roure, D., Goble, C. Stevens, R. (2009) The Design
and Realisation of the myExperiment Virtual Research
Environment for Social Sharing of Workflows. Future
Generation Computer Systems 25, pp. 561-7.
• A workflow commons for workflow sharing,
designed using Web 2.0 principles
• Launched open beta in November 2007, still
actively used
• Largest public collection of workflows, for
multiple workflow systems
• 2400+ entries in Google Scholar refer to
myExperiment
• Open source, REST API, part of Open Linked
Data cloud (66k triples) - lod-cloud.net
• Introduced “packs” which led to Research
Objects – www.researchobject.org
• Workflow collection studied in scientific
workflow and e-Science communities
• Service maintained by Manchester and Oxford
universities. Informs design of other workflow
sharing systems.
• Content stats: 10591 members, 393 groups,
3876 workflows, 1233 files, 477 packs
Credit: Carole Goble

7. GitHub
• Widely used for sharing software, and socially working
on/with software (and many other types of documents)
• GitHub is used for sharing workflows today
• Both scripts and data
• Borrowing from “Software vs. data in the context of
citation”
• A workflow as a program or a script is code, a creative work
• Appropriate license: OSI-approved open source (e.g., BSD)
• A workflow as a DAG is data?
• Appropriate license: Creative Commons (e.g., CC-BY)?
• So, let’s keep workflows as programs/scripts
• Use YesWorkflow with scripts
• Use GitHub to share
Katz DS, Niemeyer KE, et al. (2016) Software vs. data in the context of citation.
PeerJ Preprints 4:e2630v1 doi: 10.7287/peerj.preprints.2630v1