Challenges, Opportunities, and Myths in Data Science
This plenary session serves as the introduction to the Summit. As nutrition is a diverse and complex discipline, it should be met with equally as diverse review of possible data science methodologies to solve its problems. Efforts by Boston area universities to address this complexity across various subdisciplines in nutrition will be highlighted. Speakers from various institution and disciplines will offer insights into interdisciplinary collaborations and highlight the need for interdisciplinary connection, coordination, collaboration, and creativity.
Nutrition Data Sharing
Though NGOs, government agencies, and academia can have differing goals and interests, they often utilize the same types of data to perform their work. As such, collaborations and partnerships between these sectors can provide outstanding opportunities to share information and establish open source information repositories. Each of these sectors also upholds different standards for data collection techniques, data transparency, and overall nutrition communication. This session comprises a panel discussion to provide an overview of the complexities that arise in data collection, management, and sharing processes through researchers' personal experiences. In addition, participants will also have the opportunity to discuss solutions and improvements in data collection and communication techniques to formulate suggestions and goals for future data sharing agreements. Overall, this session helps discuss those issues related to coordinating research and field studies as a means of improving greater collaboration and standardization of information sharing processes.
Standardization of Anthropometric Measurements
Anthropometry is the basis of our present understanding of nutrition. However, questions remain about the utility, reliability, and consistency of anthropometric measurements such as mid-upper arm circumference (MUAC) and body mass index (BMI). Beyond anthropometry, the relationship between populations and their nutritional status is often summarized by various nutritional markers and proportional estimates, all of which lead to questions about the generalizability and efficacy of such measures.
Big Data Challenges in Molecular Nutrition
This session discusses the opportunities for utilizing a diverse array of big data to establish precision nutrition health interventions. As chronic diseases become evermore present worldwide, effective prevention and management strategies have targeted the leading risk factor: poor nutrition. Precision nutrition, also known as personalized nutrition, considers a set of factors pertinent to the individual and responses to his/her environment. These include areas of biochemical and molecular sciences focused on human genetics, nutritional genetics (nutrigenomics), microbiome, and metabolome studies. We seek to highlight the complexities in data management for these big data challenges and discuss the complex adaptive statistical systems used to describe their behaviors. Despite assessing the challenges of manipulating and analyzing these data, the session aims to address the incredible opportunities of this information in the health system. We further hope to address how such individualized information can be generalized for wider application at the population level.
Challenges in Applied Nutrition Sciences
This plenary session will be rooted in data sciences to provide an assessment of the efficacy of certain data science methodologies commonly found in nutrition research. An effort will be taken to highlight some of the differences in choices when performing data analytics and shed light on the consequences/benefits of each. As most attendees will be more rehearsed in nutrition rather than data sciences, this discussion hopes to provide participants with some of the issues that arise in the common practices taken during nutrition research. Furthermore, as the summit centers upon data sciences, this session provides greater understanding of debates in the data sciences in isolation from its role in nutrition sciences.
Harnessing the Power of Geospatial Data in Nutrition
This session discusses important advancements in data science technologies to record, manage, and evaluate nutritional information changing over both time and space. Much nutrition research is intervention or program specific: the same geographic area receives treatments at varying intervals of time. However, research related to agriculture, the environment, and even food- or waterborne disease must account for variations of nutrition outcomes over space as well. These studies utilize more complex statistical techniques to capture and model spatial statistics such as geographic information systems, remote sensing, agent-based modeling, random walk probabilistic networks, and Marchov Chains. We seek to highlight three aspects of harnessing geospatial data: i) the technologies available to collect information; ii) the resources to access such information; and iii) the statistical procedures to analyze spatial relationships. This session will urge participants to integrate geospatial data more frequently into their analyses to capture the spatiotemporal complexity of system-based research.
Nutrition in Humanitarian Emergencies
The simulation exercise will focus on the theories, strategies, and nutrition data sciences occurring during nutrition emergencies, namely famine situations. To provide a holistic understanding of these event's complexities, the simulation will be broken into three parts. First, an in-depth discussion of humanitarian emergency theory will be provided to review those issues related to determining, declaring, and delivering famine response efforts. Next, working groups will be presented with information and visualizations to identify what conclusions can be made from this information according to how data was collected, recorded, organized, and communicated. The final component of this session will consist of an on-the-ground narrative by a researcher working in these conditions and the difficulty of forming a response in the moment of the crisis.
The Future of Nutrition Technology
This plenary session will provide perspectives on the changing nature of the nutrition field. The panel will consist of nutrition technology entrepreneurs primarily from the Greater Boston area. Panelists will discuss present and upcoming advances in the nutrition field, and provide guidance for aspiring researchers and entrepreneurs on how to shape this future. This session will be followed by a professional networking event featuring startups, consultancies, and research opportunities in nutrition data sciences.
Professional Networking Session
The competitive nature of entrepreneurship creates an essential iterative process of developing and advancing nutrition technologies. Validating these new designs, processes, systems, and products depends upon exceptional utilization of data sciences. Even further, many of these technologies may help to better process, manage, and comprehend big data for nutrition-based applications. We host this luncheon event to foster connections, collaborations, and creative thinking between academics and entrepreneurs with both skills and experiences in data sciences.
All session participants are expected to adhere to the Tufts University Code of Conduct