Biomedical research has and will continue to generate large amounts of data (termed 'big data') in many formats and at all levels. Consequently, there is an increasing need to better understand and ...mine the data to further knowledge and foster new discovery. The National Institutes of Health (NIH) has initiated a Big Data to Knowledge (BD2K) initiative to maximize the use of biomedical big data. BD2K seeks to better define how to extract value from the data, both for the individual investigator and the overall research community, create the analytic tools needed to enhance utility of the data, provide the next generation of trained personnel, and develop data science concepts and tools that can be made available to all stakeholders.
Objective: Understand barriers to the use of personal health data (PHD) in research from the perspective of three stakeholder groups: early adopter individuals who track data about their health, ...researchers who may use PHD as part of their research, and companies that market self-tracking devices, apps or services, and aggregate and manage the data that are generated.
Materials and Methods: A targeted convenience sample of 465 individuals and 134 researchers completed an extensive online survey. Thirty-five hour-long semi-structured qualitative interviews were conducted with a subset of 11 individuals and 9 researchers, as well as 15 company/key informants.
Results: Challenges to the use of PHD for research were identified in six areas: data ownership; data access for research; privacy; informed consent and ethics; research methods and data quality; and the unpredictable nature of the rapidly evolving ecosystem of devices, apps, and other services that leave “digital footprints.” Individuals reported willingness to anonymously share PHD if it would be used to advance research for the good of the public. Researchers were enthusiastic about using PHD for research, but noted barriers related to intellectual property, licensing, and the need for legal agreements with companies. Companies were interested in research but stressed that their first priority was maintaining customer relationships.
Conclusion: Although challenges exist in leveraging PHD for research, there are many opportunities for stakeholder engagement, and experimentation with these data is already taking place. These early examples foreshadow a much larger set of activities with the potential to positively transform how health research is conducted.
The use of Common Data Elements can facilitate cross-study comparisons, data aggregation, and meta-analyses; simplify training and operations; improve overall efficiency; promote interoperability ...between different systems; and improve the quality of data collection. A Common Data Element is a combination of a precisely defined question (variable) paired with a specified set of responses to the question that is common to multiple datasets or used across different studies. Common Data Elements, especially when they conform to accepted standards, are identified by research communities from variable sets currently in use or are newly developed to address a designated data need. There are no formal international specifications governing the construction or use of Common Data Elements. Consequently, Common Data Elements tend to be made available by research communities on an empiric basis. Some limitations of Common Data Elements are that there may still be differences across studies in the interpretation and implementation of the Common Data Elements, variable validity in different populations, and inhibition by some existing research practices and the use of legacy data systems. Current National Institutes of Health efforts to support Common Data Element use are linked to the strengthening of National Institutes of Health Data Sharing policies and the investments in data repositories. Initiatives include cross-domain and domain-specific resources, construction of a Common Data Element Portal, and establishment of trans-National Institutes of Health working groups to address technical and implementation topics. The National Institutes of Health is seeking to lower the barriers to Common Data Element use through greater awareness and encourage the culture change necessary for their uptake and use. As National Institutes of Health, other agencies, professional societies, patient registries, and advocacy groups continue efforts to develop and promote the responsible use of Common Data Elements, particularly if linked to accepted data standards and terminologies, continued engagement with and feedback from the research community will remain important.
Biological processes are fundamentally driven by complex interactions between biomolecules. Integrated high-throughput omics studies enable multifaceted views of cells, organisms, or their ...communities. With the advent of new post-genomics technologies, omics studies are becoming increasingly prevalent; yet the full impact of these studies can only be realized through data harmonization, sharing, meta-analysis, and integrated research. These essential steps require consistent generation, capture, and distribution of metadata. To ensure transparency, facilitate data harmonization, and maximize reproducibility and usability of life sciences studies, we propose a simple common omics metadata checklist. The proposed checklist is built on the rich ontologies and standards already in use by the life sciences community. The checklist will serve as a common denominator to guide experimental design, capture important parameters, and be used as a standard format for stand-alone data publications. The omics metadata checklist and data publications will create efficient linkages between omics data and knowledge-based life sciences innovation and, importantly, allow for appropriate attribution to data generators and infrastructure science builders in the post-genomics era. We ask that the life sciences community test the proposed omics metadata checklist and data publications and provide feedback for their use and improvement.
Computing technology is nothing if not fast moving. Generations of products and their underlying electronics are introduced every 18 to 24 months. These developments are driven largely by competition ...and commercial reward, but many have their roots firmly in research funded by both the government and private sector. New products, processes, and services typically stem from the complex interaction of government, industry, and academia, but are there specific patterns in past successes? Over the years, a particular blend of government, industry, and academia has been the foundation of computing innovation. If the US is to sustain its past growth in computing, researchers, business leaders, and policy makers need to understand the elements of this synergy. One way to gain insight is to analyze past successes in significant areas. The Computer Science and Telecommunications Board (CSTB) produced a report that overviews the innovations since World War II in five critical areas of computing technology: relational databases, the Internet, theoretical computer science, artificial intelligence, and virtual reality. The studies demonstrate significant interaction among industry, universities, and government in developing and commercializing computing technology.
REAL NUMBERS Sheehan, Jerry
Issues in science and technology,
04/2005, Letnik:
21, Številka:
3
Journal Article
Recenzirano
With prospects for economic growth improving across the Organization for Economic Co-operation and Development region, renewed attention is being directed to ways of tapping into science, technology, ...and innovation to achieve economic and societal objectives. Statistical data on business research and development, patents, and other information are presented.
Real numbers Sheehan, Jerry
Issues in science and technology,
12/2002, Letnik:
19, Številka:
2
Journal Article
Recenzirano
Despite the economic slowdown that spread across the Organization for Economic Cooperation and Development area in 2001, investment in and exploitation of knowledge remain key drivers of innovation ...economic performance, and social well-being. Over the past decade, investments in knowledge--as measured by expenditures on research and development, higher education, and software--grew more rapidly than did gross fixed capital formation and played an important role in driving economic growth.
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