This page describes a Research Object for my PhD thesis (written in PDF). The Research Object includes the inputs, outputs and material used in the experiments and evaluation of the thesis, including other Research Objects referencing past publications. All the contents are semantically described (i.e., they can be retrieved automatically by machines), linked to each other and have a DOI in order to facilitate their accessibility.
If you want to get an RDF description of the contents presented in this document, just parse it with your favourite RDF parser. Alternatively, you can use content negotiation on its id (http://w3id.org/dgarijo/ro/mining-abstractions-in-scientific-wfs) to retrieve it on TTL (link), RDF/XML (link) or JSON-LD (link) formats.
(Abstract extracted from the thesis document) "Scientific workflows have been adopted in the last decade to represent the computational methods used in in silico scientific experiments and their associated research products. Scientific workflows have demonstrated to be useful for sharing and reproducing scientific experiments, allowing scientists to visualize, debug and save time when re-executing previous work. However, scientific workflows may be difficult to understand and reuse. The large amount of available workflows in repositories, together with their heterogeneity and lack of documentation and usage examples may become an obstacle for a scientist aiming to reuse the work from other scientists. Furthermore, given that it is often possible to implement a method using different algorithms or techniques, seemingly disparate workflows may be related at a higher level of abstraction, based on their common functionality. In this thesis we address the issue of reusability and abstraction by exploring how workflows relate to one another in a workflow repository, mining abstractions that may be helpful for workflow reuse. In order to do so, we propose a simple model for representing and relating workflows and their executions, we analyze the typical common abstractions that can be found in workflow repositories, we explore the current practices of users regarding workflow reuse and we describe a method for discovering useful abstractions for workflows based on existing graph mining techniques. Our results expose the common abstractions and practices of users in terms of workflow reuse, and show how our proposed abstractions have potential to become useful for users designing new workflows".
The work described in this thesis is an aggregation and refinement of previous work, which has also been published as Research Objects. In this section we explain briefly some of the contributions of the thesis, pointing to the aggregated resources and Research Objects related to them.
|Daniel Garijo Verdejo (Author)||Daniel Garijo is a PhD student in the Ontology Engineering Group at the Artificial Intelligence Department of the Computer Science Faculty of Universidad Politécnica de Madrid. His research activities focus on e-Science and the Semantic web, specifically on how to increase the understandability of scientific workflows using provenance, metadata, intermediate results and Linked Data.|
|Oscar Corcho (Supervisor)||Oscar Corcho is an Associate Professor at Departamento de Inteligencia Artificial (Facultad de Informática , Universidad Politécnica de Madrid) , and he belongs to the Ontology Engineering Group. His research activities are focused on Semantic e-Science and Real World Internet. In these areas, he has participated in a number of EU projects (Wf4Ever, PlanetData, SemsorGrid4Env, ADMIRE, OntoGrid, Esperonto, Knowledge Web and OntoWeb), Spanish Research and Development projects (CENITS mIO!, España Virtual and Buscamedia, myBigData, GeoBuddies), and has also participated in privately-funded projects like ICPS (International Classification of Patient Safety), funded by the World Health Organisation, and HALO, funded by Vulcan Inc.|
|Yolanda Gil (Supervisor)||Yolanda Gil is Director of Knowledge Technologies and at the Information Sciences Institute of the University of Southern California, and Research Professor in the Computer Science Department. Her research interests include intelligent user interfaces, social knowledge collection, provenance and assessment of trust, and knowledge management in science. Her most recent work focuses on intelligent workflow systems to support collaborative data analytics at scale.|