  With the advances in e-Sciences and the growing complexity of scientific
analyses, more and more scientists and researchers are relying on workflow
systems for process coordination, derivation automation, provenance tracking,
and bookkeeping. While workflow systems have been in use for decades, it is
unclear whether scientific workflows can or even should build on existing
workflow technologies, or they require fundamentally new approaches. In this
paper, we analyze the status and challenges of scientific workflows,
investigate both existing technologies and emerging languages, platforms and
systems, and identify the key challenges that must be addressed by workflow
systems for e-science in the 21st century.
