HEAL Data Ecosystem Events and Outreach
About HEAL Data Ecosystem Events
HEAL occasionally holds events and conducts outreach. Summaries and reports are posted on this page.
Upcoming HEAL Data Ecosystem Events
- Increase Your Impact Factor: Study Registration on the HEAL Data Platform
- Data Curation 101: Maximizing the Impact of Your Data
- Open House for HEAL Data: Discussions With HEAL-Recommended Repositories
- Metadata 102: Empowering Search on the HEAL Platform
- Demystifying Data Sharing
- Following the HEAL Blueprint for Managing and Sharing Data
Creating a Community: HEAL Data Ecosystem Virtual Workshop
The NIH HEAL Initiative® hosted the “Creating a Community: HEAL Data Ecosystem Virtual Workshop” on April 20, 2021. HEAL-funded investigators and NIH program staff had the opportunity to learn more about the HEAL Data Ecosystem. They also met the awardees (University of Chicago and Renaissance Computing Institute and RTI International), and asked questions during panel discussions. Workshop speakers presented important information to help inform HEAL-funded investigators about central data-related efforts and resources. They also learned how to connect their data to the HEAL Platform. The presenters discussed making data findable and accessible and identified key data-related issues. Watch videos from the workshop:
Part 1: Benefits and Possibilities – Discover how data from current HEAL Initiative programs can serve as a launch pad for future studies, collaborations, and new programs.
Part 2: Data Security – Learn about the HEAL Platform, which is designed to provide the necessary security and compliance to help researchers explore the full breadth of data being generated within the HEAL Initiative.
Part 3: Available Support – Learn about the specialized data management consulting available to HEAL studies to aid in achieving data-sharing objectives in a coordinated and efficient manner.
HEAL Data Management: Gathering Input from a Sample of Awardees
The NIH HEAL Initiative is building a foundation for the HEAL Data Ecosystem to help researchers, communities, and people on the front line of the pain and opioid crises, through multiple assessments and data-gathering efforts. These analyses have illuminated how HEAL researchers create data and what data standards they use. These inquiries also informed how researchers might collaborate with others to maximize the value of HEAL data.
To begin to understand data needs and related issues, HEAL first interviewed 37 current HEAL awardees about knowledge of and use of scientific data standards, data sharing, and reuse of research data. These initial interviews revealed that the HEAL research community will generate diverse amounts and types of data and are generally supportive of open science – but also showed varying levels of awareness and use of data standards, databases, and public repositories.
- Most HEAL clinical awardees (90%) stated that they are aware of data standards in general and would use them as part of their HEAL research. By contrast, only 12% of the preclinical researchers stated that they would use some data standard as part of their HEAL research.
- “Metadata” is a novel term to most HEAL researchers, even though they may routinely use metadata in practice.
- HEAL clinical researchers are highly reliant on databases for data storage. However, preclinical researchers generally store data in formatted files created by lab instruments or analysis tools.
- Some clinical and preclinical HEAL researchers will produce “big data” as part of their HEAL research. Roughly one-third of the researchers expect to create data on the petabyte or terabyte scale:
- 1 petabyte is 1 million gigabytes
- 1 terabyte is 1,000 gigabytes
- All HEAL researchers surveyed rely on statistical and graphing tools for their analysis:
- Clinical researchers were more reliant on relational platforms
- Preclinical researchers used many instrument-specific analysis tools
- HEAL respondents were generally enthusiastic about HEAL’s efforts to promote open science through its cloud-based platform, for both collaboration and hosting of analysis tools.
- HEAL researchers are generally aware of the HEAL Public Access and Data Sharing Policy but are looking for additional guidance about its implementation.
- Roughly one-third of HEAL respondents will be using an existing public repository as an archive for their research data; for clinical researchers, this may be a condition of their award.
View the Full Report pdf 354.43 KB.
HEAL Initiative Data Asset Inventory Report
Data Asset Inventories (DAIs) contain records describing the data assets maintained by an organization, and allow companies to collect metadata on their data assets and data types. They can also include information about volume, storage, and sharing practices. The HEAL DAI was deployed to collect such information on HEAL awards. The inventory generated considerable engagement between the NIH HEAL Stewards and HEAL investigators and their teams, with approximately 18% of all HEAL awards (as of 07/26/2021) submitting responses. The distribution of the various scientific Research Focus Areas among DAI respondents roughly mirrored that of all HEAL awardees. The inventory revealed existing gaps in the HEAL ecosystem’s data processing and management efforts. Additionally, the resulting analysis clarified several general areas where researchers need assistance, including repository selection, metadata collection, and public access and data sharing plans. The key findings of the DAI are summarized in the NIH HEAL DAI report.
View the Full Report pdf 1.84 MB.
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About the HEAL Data Ecosystem
The HEAL Data Ecosystem aims to transform research data, findings, and publications into a virtual, annotated, searchable catalog in which datasets and findings from different studies can be analyzed, compared, and combined.
Preparing HEAL-Generated Data for Sharing
Learn about the group funded to work with research teams throughout the HEAL Initiative to provide guidance in implementing FAIR data management and sharing practices.
Common Data Elements (CDEs) Program
To facilitate cross-study comparisons and improve the interpretability of findings, clinical pain research grantees collaborate and agree to use common data elements for patient-reported outcomes (PROs).