Abstract

THE USE OF SOFTWARE TO MANAGE LABORATORY DATA AND WORKFLOWS

Ali Hassan Alhussain*, Waseem Ali Alquwayi, Yasser Abdrab Alameer Alkuwaiti and Ahmed Mohammed Almehainy

ABSTRACT

Background: Scientific research increasingly depends on intricate processes that amalgamate data processing, computing, and simulation across decentralized platforms. Efficient management of these processes requires specialized software that transcends basic dataflow models to include comprehensive error handling and resource management. The need for these systems is driven by the expansion of e-science and extensive initiatives such as Pan-STARRS and the USC Epigenome Center, which produce and manage terabytes of data. Current workflow management systems (WMS) provide many methods for workflow composition and execution, although they lack standardization and compatibility. Methods: This article examines the fundamental ideas of scientific processes, examining the enactment issues (efficiency, robustness) and structural complexity (linear, DAG, cyclic, hierarchical). It analyzes notable WMSs like Taverna, Pegasus, Triana, Askalon, Kepler, GWES, and Karajan, contrasting their programming interfaces (textual vs visual) and functionalities. The examination examines how these systems tackle the difficulties of handling data-intensive, prolonged operations in distributed computing settings. Results: The study emphasizes the necessity for standardized workflow languages to enhance interoperability while highlighting the variety of WMS designs and development approaches. The document delineates primary obstacles in process execution, including optimal resource distribution, resilient failure recovery, and proficient oversight. The research indicates a compromise between the adaptability of visual programming interfaces and the detailed control provided by text-based methods. Conclusion: To handle the complexity of contemporary data-intensive research, scientific procedures are crucial. Although current Warehouse Management Systems provide useful functionalities, many obstacles persist in standardization, compatibility, and effective implementation in decentralized settings. Additional research is required to tackle these problems and enhance the efficiency and reliability of scientific operations.

Keywords: Dataflow, Distributed Computing, e-Science, Scientific Workflow, and Workflow Management System (WMS).