@conference {DBLP:conf/kcap/TsafaraTSZ15,
	title = {Cloud-Based Data and Knowledge Management for Multi-Centre Biomedical Studies},
	booktitle = {Proceedings of the 8th International Conference on Knowledge Capture, K-CAP 2015, Palisades, NY, USA, October 7-10, 2015},
	year = {2015},
	pages = {24:1{\textendash}24:4},
	doi = {10.1145/2815833.2816949},
	url = {https://doi.org/10.1145/2815833.2816949},
	author = {Amalia Tsafara and Christos Tryfonopoulos and Spiros Skiadopoulos and Lefteris Zervakis}
}
@conference {563,
	title = {Cloud-Based Data and Knowledge Management for Multi-Centre Biomedical Studies},
	booktitle = {Proceedings of the International Conference on Knowledge Capture (K-CAP)},
	year = {2015},
	month = {October 7-10},
	address = {Palisades NY, USA},
	abstract = {Among the basic research tools for (bio)medical science are epidemiological studies that typically involve a number of hospitals, clinics, and research centres scattered around the world, and are often referred to as multi-centre studies. Clearly, the effectiveness and importance of a multi-centre study increases with the number of participating centres and enrolled patients, but at the same time this natural distribution in the production of research data requires sophisticated data management infrastructures to support the participating units. This kind of infrastructure is not only expensive to build and maintain, but also cannot be reused as it is often tailored to a specific study. In this work, we present a cloud-based system, coined CLOUDSTUDY, that allows users without any computer science background to design, deploy, and administer platforms aimed for managing, sharing, and analysing clinical data from multi-centre studies. The CLOUDSTUDY system provides a zero-administration, zero-cost online tool for creating multi- centre studies that (i) enhances re-usability by introducing study templates, (ii) supports (bio)medical needs through specialised data types, and (iii) emphasises data filtering/export through an expressive yet simple graphical query engine.},
	doi = {10.1145/2815833.2816949},
	url = {https://doi.org/10.1145/2815833.2816949},
	author = {Amalia Tsafara and Christos Tryfonopoulos and Spiros Skiadopoulos and Lefteris Zervakis}
}
