Author: Seonyoung Kim

https://orcid.org/0000-0002-8854-287X

Contact me about:

  1. Data Management and Sharing Planning and Practices
  2. Repository Selection
  3. Digital Commons Data@Becker (Institutional Data Repository)
  4. DMPTool
  5. Data Interview
Science and Informatics

Best Practices for Reproducible AI Research in Life Sciences – Introducing DOME

By — May 21, 2025

In recent years, there has been exponential growth in the use of machine learning (ML) in the life sciences, fueled by increased access to powerful hardware (e.g., GPUs) and high-quality FAIR biodata enabled by the open science movement. One standout example is AlphaFold, which uses ML to predict protein structure from genetic sequences, a breakthrough  [Read more]

Mastering Information, Science and Informatics

Tips for Writing NIH Data Management and Sharing Plans

By — June 18, 2024

The National Institutes of Health (NIH) requires a Data Management and Sharing Plan (DMSP) in all competing applications that generate scientific data. A DMSP should cover six key elements as outlined in NOT-OD-21-014.  While not required, using a DMSP template helps researchers address all six elements and sub-elements required by the NIH DMS policy. The  [Read more]

Mastering Information, Science and Informatics

How to Make Your Protocols Complete, Interactive, and Citable

By — December 8, 2023

Are you frustrated by incomplete methods in publications that lack critical details? Are you seeking a simple solution to document comprehensive step-by-step protocols, complete with information on reagents and equipment, and a dedicated space to note any protocol deviations? In research settings, reproducible experimental methods are of utmost importance. Fortunately, protocols.io offers a solution where  [Read more]

Mastering Information

Preparing for Upcoming Federal Public Access Policies: What Does it Mean for School of Medicine Researchers?

By , , , , and — October 18, 2023

In August 2022, the White House Office of Science & Technology Policy (OSTP) issued a memo: Ensuring Free, Immediate, and Equitable Access to Federally Funded Research (OSTP 2022 Nelson Memo), that directs federal agencies to update their public access policies per OSTP 2013 Holdren Memo. The policies pertain to publications, scientific data underlying publications, and  [Read more]

Mastering Information, Science and Informatics

Introducing the FDP NIH Data Management and Sharing Pilot

By — August 5, 2023

Are you working on a Data Management and Sharing (DMS) Plan for your NIH grant application under the 2023 NIH DMS policy (NOT-OD-21-013) and curious about the evaluation metric? Check out NIH’s ongoing pilot with DMS Plan templates Alpha and Bravo. The Federal Demonstration Partnership (FDP) NIH DMS Pilot, launched on March 1, 2023, is  [Read more]

Mastering Information, Science and Informatics

Introduction to PIDs: What They Are and How to Use Them

By — April 13, 2023

Persistent Unique Identifiers (PIDs), also known as Digital Persistent Identifiers (DPIs), are globally unique, persistent, machine-resolvable digital identifiers with an associated metadata schema. A PID identifies and locates an entity regardless of where it is hosted or published and enables its unambiguous and long-term identification. PIDs are an essential component of the research ecosystem, linking  [Read more]

Mastering Information, Science and Informatics

FAIR data principles: The keys to data sharing – part 3 of 4: Interoperable

By — November 9, 2022

This is part 3 of a four-part blog series on FAIR data principles (Part 1: Findable, part2: Accessible, part3: Interoperable, part4: Reusable). We reviewed making data findable using metadata in the part 1 blog and making data accessible in the part 2 blog.  In this blog, we will discuss how to make data interoperable. Part  [Read more]

Mastering Information, Science and Informatics

FAIR data principles: The keys to data sharing – part 2 of 4: Accessible

By — November 1, 2022

This is part 2 of a four-part blog series on FAIR data principles (part 1: Findable, part2: Accessible, part3: Interoperable, part4: Reusable). We reviewed making data findable using metadata in part 1, so now we will discuss how to make data accessible. Part 2: Accessible There are three principles: Selecting a suitable data repository with  [Read more]

Mastering Information, Science and Informatics

FAIR data principles: The keys to data sharing — part 1 of 4: Findable

By — October 26, 2022

Here, we will break down the details of the FAIR data principles in a four-part blog series: Part 1: Findable, Part 2: Accessible, Part 3: Interoperable, Part 4: Reusable. So what are the FAIR data principles, and why are they important? The FAIR data principles emphasize machine-actionability to ensure that computational systems can find, access,  [Read more]