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Work Package 4: Data Platform

 

WP4 will establish a data-sharing platform that will effectively exploit the data that has been pulled from multiple sources. This platform will provide descriptive and predictive information on seven types of HMs, thus improving decision-making and the treatment of patients.  The creation of statistical models will identify the best practices that will enable the best evidence to be generated. WP4 will use the most innovative methods of data analysis and the most advanced algorithms in order to achieve the optimum management and mining of the data that has been collected.  


Objectives


WP4 Partners

Bayer, Celgene, EBMT, ELN, EORTC, GMV, HULAFE, IBSAL, Janssen, LeukaNET, MediUni Wien, Menarini, Novartis, Takeda, Ulm University, UNIBO, University of York.


Achievements WP4

Considerable progress has been made in terms of establishing the Big Data platform and the methodology for analyzing data:

Achievements 2018:

1. The HARMONY data platform is now fully operational

  • Our hosting facility at CNAF (CNAF national center of Italian Institute for Nuclear Physics) became fully operational and became ISO 27001 certified;
  • All software components of the platform are now in place, tested and operational;
  • The Quality Assessment process for the evaluation of data sources is now fully supported through analytics and visualization;
  • HARMONY partners can now easier identify relevant datasets through the first release of a data discovery tool
  • The first three AML datasets from our public partners as well as from the pharma partners have been uploaded to the HARMONY platform

2. The governance process for the intake of data became also fully operational

  • The legal requirements for the data platform were established and the rules for data governance were written:   
  • Data security measures became operational; and    
  • A trusted third party is now engaged supporting the ‘de-facto’ anonymization and secure upload to the Harmony platform
  • The standard operation procedure for data anonymization was established.


Achievements 2017:

  • HARMONY's Big Data platform has been established;
  • A common data model that adheres to the FAIR (findable, accessible, interoperable, and reusable) data-sharing principles has been created;
  • HARMONY has begun developing and testing models based on available data on AML (TCGA public data, UNIBO internal data and Sanger Institute data);
  • HARMONY has started analyzing the description of datasets;

Outlook 2019

WP3 will expand the recently established Harmony big data platform in 2018 with an initial focus on AML, followed by MDS and CLL structures and data.

  • Industrialize the process for intake and upload of data to the HARMONY big data platform.
  • Expand the intake of data sources to the other indications
  • In conjunction with WP2 and others, implement a systematic approach for the management of taxonomies across the different indications
  • Pilot the process and technical infrastructure for answering research questions
  • Complete the first research question for acute myeloid leukemia (AML)