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.

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The mission of the Data-Enabled Life Sciences Alliance (DELSA Global) is to ''Accelerate the impact of data-enabled life science research on the pressing needs of the global society.'' In its first 18 months, DELSA has catalyzed connections and interactions for more effective and sustainable science by bringing stakeholders together through physical or virtual proximity to share ideas, discuss new insights, and form novel collaborations.During our most recent annual Washington, DC, meeting (May 16-17, 2013), DELSA brought together life and computer scientists, data analysts, research funding agency representatives, and many others to discuss and formulate plans for furthering the initiative of 21st-century collective innovation. In an exciting day of lightning talks and brainstorming, participants discussed the management and analysis of emerging datasets that hold such immense promise for understanding and improving the human condition and our relationship with the worlds around us and within us.A focus of this meeting was on the Quantified Human (QH) Initiative. QH takes our natural curiosity about self and combines multi-omics and clinical data to draw conclusions about our physical condition both current and future. Measures such as height, weight, and blood pressure have been used throughout medical history; however, it is now possible to track many other measures such as caloric/nutritional intake and output, blood components, and sleep patterns. These data can be viewed in the context of our body as an ecosystem by including measures of the commensal microorganisms, collectively referred to as the microbiome. All of these results, taken together and over a period of time, can lead to a detailed picture of our overall health and open up a whole new level of understanding about the microenvironment that exists inside us. However, the resulting datasets are complex and immense. While the potential exists to use these data to explore the depth and breadth of ourselves in new and unimagined ways, we need new paradigms and policies for organizing, managing, and sharing the data, combined with new publishing and citation models.The QH initiative issues were divided into four categories:Data and Meta-Data, Metrics and Evaluation, Research Outcomes, and Outcomes for the General Public

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