Abstract
Workflow systems by it’s nature can help bioin-formaticians to plan for their experiments, store, capture and analysis of the runtime generated data. On the other hand, the life science research usually produces new knowledge at an increasing speed; Knowledge such as papers, databases and other systems knowledge that a researcher needs to deal with is actually a complex task that needs much of efforts and time. Thus the management of knowledge is therefore an important issue for life scientists. Approaches has been developed to organize biological knowledge sources and to record provenance knowledge of an experiment into a readily resource are presently being carried out. This article focuses on the knowledge management of in silico experimentation in bioinformatics workflow systems.
Highlights
Scientific experimentation in science domains contains all required aspects of the experimentation process including data analysis, modeling, and testing [1].A workflow is a well-defined organization of activities or patterns designed to achieve a certain data transformation [2]
Biomedical ontologies are playing an important role in life sciences semantic web since they help in capturing the semantics of entities and their interrelationships within biology domain, thereby reducing conceptual ambiguity, increasing reusability and computational automation that aids in knowledge gathering and discovery [15]
Having scientific workflow means to have a wide range of methods, algorithms, and tools that can perform a given workflow task at different level of granularity; in addition to that, the architecture at the symbol level describes the capabilities of workflow systems and how to execute the workflow identified tasks [2]
Summary
Scientific experimentation in science domains contains all required aspects of the experimentation process including data analysis, modeling, and testing [1]. Complex workflow systems that integrate programs, methods, agents, and services coming from diverse organizations or sites requires a more flexible framework that can execute such complex scenario [3] In such a way, the execution sequence and the scheduling of algorithms, data, services, and other software components are orchestrated in a single virtual framework [3]. With the vast amount of the available bioinformatics tools, services and algorithms that can execute the biologists tasks; it’s a must to have certain technology that allow automation and discovery of such resources, in addition to that the bioinformaticians need to create complex workflows from a wide range of available web services knowledge base. The rest of the paper is organized as follows: Section II, presents how semantic Web technology is an effective knowledge management technology in life science domain.
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