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Social Dialogue and Scientific Production on Big and Open Data in Health: From Facilitating Surveillance and Preventing Disease to Fostering Behavioral Changes
Current Issue
Volume 4, 2016
Issue 3 (June)
Pages: 14-22   |   Vol. 4, No. 3, June 2016   |   Follow on         
Paper in PDF Downloads: 146   Since May 21, 2016 Views: 5846   Since May 21, 2016
Marcelo D´Agostino, Health Information and Analysis Unit, Department of Communicable Diseases, Health Analysis, Pan American Health Organization (PAHO), Washington D. C., United States of America.
Felipe Mejía, The Pan American Health Organization (PAHO), Bogotá, Colombia.
Myrna Marti, Department of Knowledge Management, Bioethics and Research, Pan American Health Organization (PAHO), Buenos Aires, Argentina.
David Novillo, Department of Knowledge Management, Bioethics and Research, Pan American Health Organization (PAHO), Washington D. C., United States of America.
Federico G. de Cosio, Health Information and Analysis Unit, Department of Communicable Diseases, Health Analysis, Pan American Health Organization (PAHO), Washington D. C., United States of America.
Nasim Farach, International Public Health Consultant, Tegucigalpa, Honduras.
Background: Big Data and Open Data are concepts that have evolved over the years and have different applications in health, from facilitating surveillance and preventing disease to fostering behavioral changes. Objectives: This exploratory study has two objectives: 1) To provide understanding about the use of Big Data and Open Data in the health arena and 2) to characterize the discussion, social behavior, interest and information shared in social networks and other online sources about Big Data and Open Data in health. Methods: Keywords related to “Health Big Data” and “Health Open Data” were used to gather data from social networks and from scientific databases. A qualitative based analysis was conducted upon a randomly selected subset of tweets, a list of comments in selected Facebook posts, a group of Instagram photographs and a list of selected LinkedIn posts. Trends in searches and publications were determined for Google Trends and the three scientific paper databases. Results: Majority of tweets are apps, the Cloud, consumers, costs, hackers, homecare, interoperability, mining, mobile, monitoring, openness, physicians, privacy, quality, research, safety, sensors, social media, startups, storage and wearables. Comments in selected Facebook posts showed mistrust toward any social network site involved in health. Users blamed companies for health security problems. On Instagram highly visual graphs and charts are the most common types of posts, followed by photographs of events related to data and health. LinkedIn posts including both Big Data and health count for more than 50,000 for “all time periods” and more than 3,000 for a period of “one week to one month”. The most common topics for the first 20 results sorted by relevance were: partnerships, use of Big Data in health, health Big Data analytics, and Big Data trends. Google Trends showed that searches including health Big Data and health Open Data have increased steadily since 2012. For the three scientific paper databases, there seemed to be a greater increase in publications regarding Big Data than for Open Data. Conclusions: An integrated analysis of social tools and scientific databases can provide valuable insights into people’s perceptions on innovative applications in health. Our results suggest that while interest in Big Data is increasing rapidly, there are growing concerns about data leakage and the ability of providers and governments to assure privacy. For Open Data in health, the increase in interest is not as large as that of Big Data in health.
Big Data, Open Data, Open Governmental Data, Social Media, Qualitative Research
Hu, J., Yang, K., Warty, C., & Xu, K. (2015). Special issue on big data inspired data sensing, processing and networking technologies. Ad Hoc Networks, 35, 1–2. http://doi.org/10.1016/j.adhoc.2015.07.014
Kacfah Emani, C., Cullot, N., & Nicolle, C. (2015). Understandable Big Data: A survey. Computer Science Review, 17, 70–81. http://doi.org/10.1016/j.cosrev.2015.05.002
Jin, X., Wah, B. W., Cheng, X., & Wang, Y. (2015). Significance and Challenges of Big Data Research. Big Data Research, 2(2), 59–64. http://doi.org/10.1016/j.bdr.2015.01.006
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144. http://doi.org/10.1016/j.ijinfomgt.2014.10.007
Asokan, G. V, & Asokan, V. (2015). Leveraging “big data” to enhance the effectiveness of “one health” in an era of health informatics. Journal of Epidemiology and Global Health, 311–314. http://doi.org/10.1016/j.jegh.2015.02.001
Hansen, M. M., Miron-Shatz, T., Lau, a Y. S., & Paton, C. (2014). Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives. Contribution of the IMIA Social Media Working Group. Yearbook of Medical Informatics, 9(1), 21–6. http://doi.org/10.15265/IY-2014-0004
Luna, D. R., Mayan, J. C., García, M. J., Almerares, A. A., & Househ, M. (2014). Challenges and Potential Solutions for Big Data Implementations in Developing Countries. IMIA Yearbook of Medical Informatics, 36–41. http://doi.org/10.15265/IY-2014-0012
Camacho, D., & Jung, J. J. (2016). Guest Editorial : Social big data with information fusion. Information Fusion, 28(August 2015), 44. http://doi.org/10.1016/j.inffus.2015.07.008
Bello-Orgaz, G., Jung, J. J., & Camacho, D. (2015). Social big data: Recent achievements and new challenges. Information Fusion, 28, 45–59. http://doi.org/10.1016/j.inffus.2015.08.005
Kassen, M. (2013). A promising phenomenon of open data: A case study of the Chicago open data project. Government Information Quarterly, 30(4), 508–513. http://doi.org/10.1016/j.giq.2013.05.012
Zuiderwijk, A., & Janssen, M. (2014). Open data policies, their implementation and impact: A framework for comparison. Government Information Quarterly, 31(1), 17–29. http://doi.org/10.1016/j.giq.2013.04.003
Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, Adoption Barriers and Myths of Open Data and Open Government. Information Systems Management, 29(4), 258–268.
Turbelin, C., & Boëlle, P.-Y. (2013). Open data in public health surveillance systems: A case study using the French Sentinelles network. International Journal of Medical Informatics, 82(10), 1012–1021. http://doi.org/10.1016/j.ijmedinf.2013.06.009
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