Leone lacked the resources for serological surveys and accurate census data in the past. 19 Significant problems with the operation of HDX and Ebola GeoNode were the initial collection of data by real human beings who entered incomplete, inaccurate, or altogether false data. That data in turn was sent to WHO for validation, so that information that was supposed to be available in “real-time” actually reflected a two-month or more delay because of this validation process. Standardization of databases is important to ensure that data are accurate and not repeated within the database. 36 Standardization requires commitment to procedure and training to ensure procedure is followed properly.14 Forms and barcodes should be standardized throughout the database, and data should be cleaned to ensure no data is repeated in the database. 19 Maintaining databases can be costly, and there must be consistent capital to maintain these databases.14 Control of databases should be distributed among stakeholder so that transparency and trust are secure. 36 To address these shortcomings, Médecins Sans Frontières (MSF), in collaboration with the World Health Organization (WHO), has called upon stakeholders to establish a coordinated network of Ebola biobanks. Additionally, MSF has joined Oxford University’s Infectious Diseases Data Observatory to establish a data-sharing platform for existing and future clinical, biological and epidemiological data, with the aim of making this information accessible to stakeholders and researchers with relevant scientific questions. Data sharing through biobank is an established practice in many health research fields, from the Global Burden of Disease collaboration to surveillance and response to influenza, drugresistant malaria and severe acute respiratory syndrome (SARS). Biobanks are wellestablished resources for disease research, for example on human immunodeficiency virus (HIV), malaria, and rare diseases. c. Means to identify preliminary data as opposed to confirmed data: The use of channels for posting preliminary results for use by others has increased unevenly over disciplines relevant to response. Epidemiologists and modelers, for example, have made more significant use of these platforms than have geneticists. Over the Ebola outbreak, 80% of epidemiological studies used data from an open source, while genetic sequencing data was largely hoarded by researchers. d. The need for standardized data sharing protocols: “Researchers working on outbreaks — from Ebola to West Nile virus — must agree on standards and practices that promote and reward cooperation. If these protocols are endorsed internationally, the global research community will be able to share crucial information immediately wherever and whenever an outbreak occurs.”24 24 A minimum standard – what information should be included for reporting cases etc. and identifying what is desirable information. A number of organizations including the Royal Institute of International Affairs, the Wellcome Trust, and the World Economic Forum have begun to develop template forms that parties may use for surveillance data sharing, data management plans, sharing benefits, and managing intellectual property rights. e. The current academic reward system should be restructured: There was overwhelming consensus among stakeholders that research data are generally considered proprietary, with potentially lucrative benefits that researchers hesitate to freely share. WHO has suggested that researchers treat data sharing as a free trade market, where one researcher must exchange intellectual property for another researcher’s intellectual property.