The increasing need for dealing with large amounts of data and the potential automation of processes for decision making, defining and deploying complex workflows for a broad range of both enterprise processes and multi-step or repetitive scientific and engineering tasks, as well as developing on advanced technological platforms (grids, cloud computing, mobile devices, etc.), pose a challenge to many companies and organizations around the world. In both business and scientific domains, the development of intelligent systems and workflow applications is becoming an important investment focus in order to satisfactorily meet the business requirements. At the same time, efforts in research are providing significant results and benefits with regard to the analysis and modelling of the involved processes and other information handling tasks.
Building this sort of systems for a given domain makes it necessary to properly abstract the definition of the specific data workflow components from their intrinsic computational logic to efficiently execute them. The modelling and management of data workflows is becoming a reality successfully established in the scientific field, where computationally intensive experiments need to be refined and optimised on platforms that allow exploiting all the resources available. Furthermore, the management of these processes has to be done in a transparent manner, automating their invocation (locally or remotely) and pipelining processing of data with no need for user intervention, excepting for some initial and intermediate setup and collecting results.
WorkGenesis consists in a three layered meta-framework that supports developers to quickly develop and deploy customized data-intensive Workflow Management Systems (WfMS) to your customer.
WG Studio is a customizable WfMS that perfectly adapts to the specific domain of the end user in a transparent way for the developer. WG Meta is a meta-tool that allows the developer to define the specific features of the target domain and how the final tools will be deployed.