Enhancing Workflow with a Semantic Description of Scientific Intent

Abstract

Scientists are becoming increasingly dependent upon resources available through the Internet including, for example, datasets and computational modelling services, which are changing the way they conduct their research activities. This paper investigates the use of workflow tools enhanced with semantics to facilitate the design, execution, analysis and interpretation of workflow experiments and exploratory studies. Current workflow technologies do not incorporate any representation of experimental constraints and goals, which we refer to in this paper as scientist's intent. This paper proposes an abstract model of intent based on the Open Provenance Model (OPM) specification. To realise this model a framework based upon a number of Semantic Web technologies has been developed, including the OWL ontology language and the Semantic Web Rule Language (SWRL). Through the use of social simulation case studies the paper illustrates the benefits of using this framework in terms of workflow monitoring, workflow provenance and annotation of experimental results.

Technical Perspectives on Knowledge Management in Bioinformatics Workflow Systems

“…It promises to meet the challenge of integrating and querying highly diverse and distributed resources [13].…”

“…With knowledge of what workflow components do, and experiment design; workflow systems can assist scientists by using those knowledge to make automatically decisions concerned about specific domain [19]. Figure 5 is a schematic representation of the workflow in SSB [13]. Firstly, biological knowledge is extracted from disparate resources and integrated into a knowledge base.…”

“…The authors in [13] have utilized several semantic technologies to identify the scientists intent, and then to facilitate the control of workflow execution and enrichment of workflow provenance of new tasks, The Magallanes [23] is a library that can develop effective workflow discovery engines that can help to collect webservices which will be used to execute workflow tasks and it's datatypes. The discovery of Web services can be based on syntax description of services or objects that is it's name which is often unsatisfactory in bioinformatics because it presumes knowledge of objects names or semantics services discovery by specifying a general descriptions about services or objects which allow to have a more accurate discovery mechanism.…”

A Novel Approach for Bioinformatics Workflow Discovery

“…The authors in [12] have utilized several semantic technologies to identify the scientists intent, and then to facilitate the control of workflow execution and enrichment of workflow provenance. While the integration of semantic components with the original system improved the usability of the workflow system, users still have to be familiar with those workflow design systems in order to accomplish a data analysis task.…”

“…This feature considers the fact that currently there exist potentially large number of services from different service providers that can functionality overlap we believe that the non-functional properties of services, especially those related to Quality of Service (QoS), such as reliability, performance, and sensitivity, should be considered when several services provide similar function or information. A service selection algorithm is used to help users identify the "best" service [12]. The rest of the paper is organized as follows: Section II, presents background, related work, and motivates the problem.…”