Table 1.

Questions that arise for the DWFS for large-scale data analytics for bioinformatics research

Questions	Objective	Do DWFSs reach state of the art?	How important is the answering?
Q1	Do the current solutions enable large-scale data analysis in a cloud environment?	Yes	Important and need some special care too, for large-scale data analytics using DWFSs
Q2	Do existing solutions align well with the Semantic Web technologies for large-scale data analytics in bioinformatics research?	Mostly not	Bioinformatics research is now dependent on more data-intensive computing; therefore, existing solutions need to be aligned using the benefits of the Semantic Web technologies
Q3	Is reproducibility of a computational analysis ensured over a long period using computational resources?	Mostly not	Reproducibility is one of the most important requirements for a DWFS, so that scientific experiments are more repeatable and transparent to others based on the given infrastructures and associated technologies
Q4	Are current DWFS efficient and lightweight (workflow management and execution) enough for data analytics for bioinformatics research over the Web?	Mostly not	We need to deploy an efficient and lightweight data analytics approach on the cloud or data server without moving the data location
Q5	Can we design a next-generation DWFS with Semantic Web and cloud computing technologies based on existing DWFS?	Yes	Important and our primary objective. However, this mostly depends on the right consideration, research and technical expertise