BackgroundDespite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data.ResultsA user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package.ConclusionThe new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.

Efficient development of questionnaires for longitudinal surveys and cohort studies as computerassisted survey instruments usually entails close collaboration between scientific and fieldwork teams. We describe a system based on the use of a Structured Query Language (SQL) database established to maximise efficiency, minimise error and ensure clear communication of requirements across teams for 'Life Study', a UK-wide cohort study designed to recruit mothers, their babies, partners and non-resident fathers, with whom further contacts were planned at the outset. The use of the SQL database enabled construction and integration of different elements of the study, initially through creating a master copy of each variable. This supported swift and accurate creation of a range of outputs enabling, for example, review and approval of successive drafts and final specifications of questionnaires, efficient implementation of changes to variables, re-use of metadata specified at the outset, reduction of ambiguities for survey programmers, and efficient and accurate automation of questionnaire scripting. The SQL database was also used to generate the syntax to transform pilot data into formats specified for data archiving and for associated publication quality questionnaires. This innovative use of an SQL database for questionnaire development and scripting, and subsequent data processing and documentation, highlights the value of this approach in improving the quality and efficiency of longitudinal surveys.