BACKGROUND:Medical research increasingly requires the linkage of data from different sources. Conducting a requirements analysis for a new application is an established part of software engineering, but rarely reported in the biomedical literature; and no generic approaches have been published as to how to link heterogeneous health data.METHODS:Literature review, followed by a consensus process to define how requirements for research, using, multiple data sources might be modeled.RESULTS:We have developed a requirements analysis: i-ScheDULEs - The first components of the modeling process are indexing and create a rich picture of the research study. Secondly, we developed a series of reference models of progressive complexity: Data flow diagrams (DFD) to define data requirements; unified modeling language (UML) use case diagrams to capture study specific and governance requirements; and finally, business process models, using business process modeling notation (BPMN).DISCUSSION:These requirements and their associated models should become part of research study protocols.

The ever-increasing availability of online data and the advances of today's Web have enabled large-scale experimentation on data crowdsourcing and the effect of the individual on information extraction and knowledge generation. Tiger Nation, a project to promote preservation of the last remaining wild tigers in the world, utilises advanced technologies to unobtrusively track tigers and raise awareness as a participatory sensing exemplar. Through a tiger stripe recognition algorithm and gamification elements that complement the identification process, we have achieved higher levels of accuracy compared to the conventional means, as well as high levels of engagement from the community of users.

A new distributed model of health care management is being introduced in England. Family practitioners have new responsibilities for the management of health care budgets and commissioning of services. There are national datasets available about health care providers and the geographical areas they serve. These data could be better used to assist the family practitioner turned health service commissioners. Unfortunately these data are not in a form that is readily usable by these fledgling family commissioning groups.We therefore Web enabled all the national hospital dermatology treatment data in England combining it with locality data to provide a smart commissioning tool for local communities. We used open-source software including the Ruby on Rails Web framework and MySQL. The system has a Web front-end, which uses hypertext markup language cascading style sheets (HTML/CSS) and JavaScript to deliver and present data provided by the database. A combination of advanced caching and schema structures allows for faster data retrieval on every execution. The system provides an intuitive environment for data analysis and processing across a large health system dataset.Web-enablement has enabled data about in patients, day cases and outpatients to be readily grouped, viewed, and linked to other data. The combination of web-enablement, consistent data collection from all providers; readily available locality data; and a registration based primary system enables the creation of data, which can be used to commission dermatology services in small areas. Standardized datasets collected across large health enterprises when web enabled can readily benchmark local services and inform commissioning decisions.