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Sharing the Learning from CARDI's Data Mining Research Grants Programme



Type: Report
Region: Republic of Ireland
Northern Ireland

Overview CARDI was pleased to see a large level of interest in the Data Mining Call. Applications for Data Mining grants closed on 1 October 2010 and projects that are being offered funding have been informed. This short article makes some general comments on what distinguished successful applications from those that were not successful. CARDI will not be giving individual feedback on applications but gives some notes below to assist researchers in making further applications.  Data Mining Grant Programme In the Data Mining Grant Programme the highest scoring applicants were careful to show how they met each of the criteria. Data mining criteria 1.         Quality of the application. This refers to the rigour, originality and significance of the proposed study and the extent to which it will add to the body of knowledge in ageing research; clear aims and objectives; sound methodology; feasibility within the timescale and budget; and explicit deliverables from the project. Applications should show evidence of serious preliminary planning. 2.         Data - extent and depth of cross-border and interdisciplinary analysis. Will the project produce comparative information for all of the island of Ireland?  Will it be of benefit to interdisciplinary analysis?  The contribution that will be made to the project by each co-applicant should be clearly explained. 3.         Relevance to policy and/or practice affecting older people. The research should focus on a priority need and deal with a significant issue that affects older people and adds new knowledge and understanding. The application for data mining should be set in the context of existing policy or services and focus on improving the lives of older people.  To score well on the quality criterion, applications needed to be clear and precise about what they were trying to achieve and how they were planning to achieve it. They were required to set out one or more research question, combined with a rigorous methodology that was capable of delivering the results desired. An important part of the terms of reference was that the programme was intended to: “support research involving the extraction, collation and analysis of existing data from an all-Ireland perspective and summarising it into information relevant for policy or practice”. The data mining programme was not to fund the evaluation, assessment or quality testing of data sets.  Furthermore the terms of reference specified that applicants should identify the data sources they intended to use; applicants unable to identify a specific, robust and appropriate data set were unlikely to provide evidence that was relevant to the research question.  Likewise some unsuccessful applications set out data sources in one part of Ireland but did not meet the north-south condition by identifying a specific and relevant data source in the other part of the country. Successful applications had a coherent thread beginning with a research question, specific data sets, the extraction of useful data in which Northern Ireland and the Republic of Ireland could be compared and contrasted, leading to conclusions that could be relevant to policy and practice. In some cases applications with quite high quality and specific data sets were less strong on this latter score. They could explain why and how they wanted to explore data but were less explicit about the implications for “a significant issue that affects older people” or about how the proposal might add new knowledge and understanding. In summary as we have emphasised in comments on earlier grant calls, the most important part of a grant application is to study the terms of reference. You may have a burning wish to conduct the research and your application may be of high quality but, apart from open calls, that is not sufficient: you must also meet the conditions set out in the terms of reference.



Rights: Public
Suggested citation:

CARDI. (2011) Sharing the Learning from CARDI's Data Mining Research Grants Programme [Online]. Available from: [Accessed: 21st February 2019].


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