The integration of workflows with data mining services significantly improves data analysis.
openBIS is designed to allow extensions and integration of workflows with minimal effort and provides interfaces for the integration of relevant community tools.
WINGS accomplishes this through two features not found in other workflow platforms: 1) the integration of individual workflow components and their datasets; and 2) the semantic enforcement of user-defined rules and constraints.
The integration of individual workflow components and their datasets within WINGS is achieved through the use of individual ontologies used to define and organize all datasets and workflow components, respectively.
The seamless integration of computing, workflow, data, and metadata management with an easy-to-use user interface optimally supports the users in solving their highly complex and data-intensive research questions.
In a time where user interfaces become more accessible, software becomes increasingly open-source, and recording technologies more affordable, the outlook for the future is the integration of the workflows towards an automated acquisition and analysis of numismatic collections to make them more accessible for education and research via digital repositories.
This framework aims to simultaneously support the integration of: legacy code, workflow management, parallel computing and fault tolerance.
With text mining workflows simplified, users would naturally seek integration of text mining workflows with other bioinformatics resources.
Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand.
Many of our results, including the importance of workflow integration, well designed user interfaces, ongoing knowledge management and intentional interaction among stakeholders, confirm statements made by others based on their experience and expert opinion [ 6, 36- 41].
