As the National Library of Medicine seeks to serve as a platform for biomedical discovery and data-powered health, NLM in Focus asked seven staff members to tell us how they fit into data science. Their answers are encouraging.

Dwight Clarke
IT Specialist (Information Security)

Very briefly, what do you do at NLM?

In my role as the federal team lead for the NLM Network Security Team, I am responsible for the architectural design and the implementation of controls that actively secure NLM data resources and adhere to the Federal Information Security Management Act.

How do you see yourself supporting data science at NLM?

I am willing to support data science at NLM to the capacity allowed by my role in network security and afforded by the knowledge and experience acquired from independent research conducted in applying machine learning methodologies to predictive analysis.

What are you looking forward to learning through the NLM Data Science @NLM Training Program?

I look forward to filling any gaps in my current understanding of data science, particularly in operationalizing data science for public consumption.

What excites you most about data science at NLM?

What excites me most about data science at NLM is the additional opportunity to directly contribute to a mission-supporting activity that is also of personal interest.

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Linda Collins
Program Assistant

Very briefly, what do you do at NLM?

I am an administrative assistant with the Cognitive Science Branch at Lister Hill. I do travel, ITAS, supplies, and administrative functions for my branch.

How do you see yourself supporting data science at NLM?

I really didn’t think that I was supporting data science until I went to the lecture and realized I do, quite a bit.

What are you looking forward to learning through the NLM Data Science @NLM Training Program?

How to make it more user friendly and incorporate it in my daily tasks to make them easier and more efficient.

What excites you most about data science at NLM?

Learning that even though I am not a scientist, my contributions do matter and fit into the bigger picture.

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Victor Cid
Senior Computer Scientist

Very briefly, what do you do at NLM?

I create engineering solutions for information, education, and communications problems. My current projects involve virtual reality and machine learning technologies. I also support institutional outreach activities in Latin America and the Caribbean. In DIMRC (the Disaster Information Management Research Center), I focus on solutions for disaster health and emergency management professionals.

How do you see yourself supporting data science at NLM?

For many years, I have been using data analytics, virtual reality simulations and, more recently, deep learning, as well as managerial skills, to address complex engineering problems. I envision myself supporting a variety of data science tasks in disaster health and other areas, such as identifying candidate problems and resources for data science interventions; designing / modeling / developing solutions; creating visualizations and simulations; and promoting our products, methods, and services to targeted audiences via publications, presentations, and other ways.

What are you looking forward to learning through the NLM Data Science @NLM Training Program?

Data Science is a vast and complex universe, and computer science is advancing at a very fast pace, especially in topics such as machine learning and immersive simulations. I hope the Data Science @NLM Training Program can help me expand my professional skills in my areas of interest, but also stimulate synergies in the organization and with outside collaborators, and provide inspiration for new innovations.

What excites you most about data science at NLM?

NLM has been making important contributions in many aspects of data science for a long time. The current impetus for data science can expand NLM’s traditional biomedical informatics roles, help NLM conquer significant challenges inherent to our data-driven times, and help position NLM as a world-class data science organization. I find all of that quite exciting.

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Jennifer Diffin
Head, Library Technology Services Section

Very briefly, what do you do at NLM?

I coordinate the maintenance and development for bibliographic and digital library systems. This includes, but is not limited to, the integrated library system (Voyager) and associated online catalog (LocatorPlus), the digital repository (NLM Digital Collections), an electronic resource management system, reporting and statistical software, and systems to support MEDLINE selection. My section also delivers first-level hardware and software support for the Technical Services Division of Library Operations.

How do you see yourself supporting data science at NLM?

Recently, I have used data gathered from Google Analytics, online surveys, and usability studies to make data-driven decisions to improve the NLM Digital Collections website. We are now conducting another usability study to test the changes. Soon, I hope to work with colleagues to explore new ways to provide data mining opportunities on the full-text resources available in NLM Digital Collections. Also, I have encouraged and supported one of my staff in her exploration of the Tableau software to investigate ways data visualization may provide new insights in the data we collect.

What are you looking forward to learning through the NLM Data Science @NLM Training Program?

I am looking forward to expanding my knowledge of and skills in data science. Ideally, I would like to be able to use the knowledge and skills gained through the training to improve the products and services that I support here at NLM. While I feel I have a basic knowledge of some of the tools available, I know I am not using them to the fullest extent possible. I hope some of the classes offered through the course catalog will expand my knowledge of these tools and data science in general.

What excites you most about data science at NLM?

I am excited that NLM is committed to professional development and training of its workforce. It directly supports Goal 3 (build a data-ready workforce for the future) of the new strategic plan. I also believe a strong commitment to Goal 3 is needed to achieve Goals 1 (accelerate data-driven discovery and advance human health) and 2 (maximize NLM’s impact through enhance engagement). It will be exciting to see what new products and services will be created or transformed due to staff’s increased knowledge of data science. While this will take a lot of hard work, it is stimulating to explore new possibilities.

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Sameer Antani
Staff Scientist & Acting Chief
Communications Engineering Branch and
Computer Science Branch

Very briefly, what do you do at NLM?

I lead medical imaging analytics and data science research applying machine learning, image processing, and informatics toward improved diagnostics and information retrieval.

How do you see yourself supporting data science at NLM?

I see data science as a collective of gathering, organizing, annotating, analyzing, and visualizing data. These would support biomedical research through automation of traditionally manual / semi-automated techniques, enabling improved collaboration through better findability, accessibility, and sharing, and enhancing value through discovery. My research has contributed to several elements above. I look forward to improved collaboration across NLM toward addressing goals of the strategic plan.

What are you looking forward to learning through the NLM Data Science @NLM Training Program?

I believe there is untapped talent within NLM that could support the goals outlined in the strategic plan. I look forward to discovering opportunities for greater collaboration across NLM divisions. These collaborations could be in organizing and annotating data, analyzing them, developing improved retrieval strategies, or establishing advanced computing and data access mechanisms. I expect the Data Science @NLM Training Program will rejuvenate and highlight some of this latent talent.

What excites you most about data science at NLM?

I see it enabling novel solutions for significant biomedical challenges through new techniques; making new connections within data as well as across collaborating teams; providing opportunities for advancing the significance of analyzing and visualizing information in biomedicine and leading to improved health care.

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Deborah Lockett-Jordan
Administrative Officer

Very briefly, what do you do at NLM?

As an Administrative Officer, I am responsible for overseeing and managing the budget for the Division of Specialized Information Services. In addition, I oversee all of the services necessary to keep the Division running and to ensure that it continues to be productive and efficient.

How do you see yourself supporting data science at NLM?

I see myself supporting data science by going paperless. Most services are paper to computer and that has made it possible to manage and analyze data that wasn’t possible before visualization.

What are you looking forward to learning through the NLM Data Science @NLM Training Program?

I’m looking forward to clearly understanding how to benefit from data science. I’m also looking forward to acquiring the skills necessary to be proficient in data science as well as using data science skills and tools in my job.

What excites you most about data science at NLM?

Becoming knowledgeable about a field that is expanding faster than almost anything else.

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Zhiyong Lu
Senior Investigator

Very briefly, what do you do at NLM?

I direct research and development in the areas of natural language processing, machine learning, and information retrieval. Some examples of our recent projects—developed by working closely with our students, postdoctoral fellows, research/engineering staff, and collaborators—include (1) the Best Match algorithm in PubMed; (2) the newly developed PubMed Labs system; and (3) DeepSeeNet: a deep learning model for automated age-related macular degeneration diagnosis and risk prediction.

How do you see yourself supporting data science at NLM?

Given our research and expertise in this area, we can help support the initiative in a few areas:

• Demonstrate use cases of data science in both research and practical applications that are highly related to the NLM mission and service.
• Engage and support our trainees in the training program.
• Help provide technical training in our research areas, e.g., natural language processing and machine learning.

What are you looking forward to learning through the NLM Data Science @NLM Training Program?

I look forward to learning about the diverse aspects of biomedical data sciences and their applications across the NLM.

What excites you most about data science at NLM?

I am grateful and excited about the unique opportunities that NLM provides to researchers like ourselves because we can not only use data science to drive biomedical discovery but also apply data science in real-life applications, in support of the NLM’s mission and strategic planning. For example, we are currently investigating novel computer methods to assist MeSH indexing in a collaborative effort.