European Union Project Promotes International Scientific Applications Using RapidMiner
Dortmund, Germany, Month, Day, 2012 – Rapid-I, a leading provider of open source solutions for predictive analytics, data mining and text mining, has pushed research in the virtual space with a successful participation in the European e-LICO-project. As the only industrial partner, Rapid-I made extensive data mining processes and services available for the project, with its RapidMiner and RapidAnalytics systems.
The goal of this project was to establish a foundation for interdisciplinary research cooperation in the area of data mining, and in the data-intensive scientific environment, supportinh global teams of non-analysts using complex data analysis processes. In this way, data mining experts, for example, can support biologists in searching data for undiscovered patterns. The result was the development of a recommendation system for non-experts in data analysis, in the style of “scientists with a similar problem tried out the following analysis process…” This gives users’ suggestions for optimal procedures when evaluating data, ensuring they can improve processes and results, step-by-step.
e-Lab consists of several layers:
· The e-Science and data mining layer form a generic research environment, which can be adapted to different scientific areas by adjusting the application layer.
· For the data mining layer, RapidMiner and RapidAnalytics are used, as the partners determined beforehand the two applications were the only suitable solutions.
“The active participation of Rapid-I was a substantial success factor in this multinational project financed by the European Union,” explained project coordinator Melanie Hilario, of the University of Geneva. “The employees of Rapid-I are highly qualified and committed, and this is also reflected in the outstanding quality of their data analysis solutions, which form the basis for the e-LICO data mining layer. At the same time, Rapid-I’s open source policy goes perfectly with the open nature of the e-Science platform and has significantly lowered the costs of the project.”
On the application level, applications in systems biology, among other things, were used during e-LICO for the discovery of biomarkers and for the creation of video recommendations for the VideoLectures.Net portal. Some further ranges of future applications could be drug discovery for predicting the effect of certain substances in newly discovered plants, or pharmacovigilance for the discovery of undesired drug effects. Developed as part of an EU project, the e-Lab can provide a template for all possible further application scenarios.
“Indicative data is the be-all and end-all in every business division. And in the scientific division, where varied research teams and sectors often have to work hand in hand, access to consistent data and its analysis are also essential,” said Dr. Ingo Mierswa, chairman of Rapid-I. “Solutions are therefore required which make cross-border cooperation possible. As we have shown with this project once more, RapidMiner is optimally suited for revealing underlying connections in data volumes.”
Partners from all over Europe are involved in the eLICO project and it is funded by the EU with 3.3 million euro. Apart from Rapid-I, the international partners of this project, which are coordinated by the University of Geneva, include: Institut National de la Santé et de la Recherche Médicale (France), Josef Stefan Institute (Slovenia), National Hellenic Research Foundation (Greece), Poznan University of Technology (Poland), Ruder Boskovic Institute (Croatia), University of Manchester (UK) as well as the University of Zurich (Switzerland). Further information at https://www.e-lico.eu
Rapid–I provides software, solutions,andservices inthefields of predictiveanalytics, datamining, andtextmining. Itsflagshipproduct, RapidMiner, istheworld-leading open–source systemforknowledgediscovery,data miningandsentiment analysis. RapidMiner is extremelyeasytouse,blazingfast, andsimpletointegratewithanyIT infrastructure,fromthesmallesttextfiles toBig DataHadoopclusters. For more information,visitwww.rapid-i.com.