Related Experiment Video
Updated: Nov 29, 2025
11:21
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
8.5K
Recommendations for Services in a FAIR Data Ecosystem
Hylke Koers1, Daniel Bangert2, Emilie Hermans3
1SURFsara, 1098 XG Amsterdam, the Netherlands.
Patterns (New York, N.Y.)
|November 18, 2020
Summary
Implementing FAIR data principles requires evolving research data services. This involves addressing challenges and prioritizing recommendations for data infrastructures to support the European Open Science Cloud (EOSC) and foster a FAIR data ecosystem.
Area of Science:
- Data Science
- Research Infrastructure
- Open Science
Background:
- Growing adoption of FAIR data principles necessitates new research data services.
- Existing policies and practices create novel demands on data infrastructures.
- The European Open Science Cloud (EOSC) initiative requires robust data support.
Purpose of the Study:
- To identify common challenges and priorities in implementing FAIR data principles.
- To propose recommendations for evolving data infrastructures to support FAIR data.
- To inform the development of the European Open Science Cloud (EOSC).
Main Methods:
- Workshops involving stakeholders from FAIRsFAIR, RDA Europe, OpenAIRE, EOSC-hub, and FREYA projects.
- Exploration, discussion, and formulation of recommendations among the scientific community.
- Prioritization of recommendations based on perceived urgency by different stakeholder groups.
Main Results:
- A comprehensive overview of current challenges and priorities in FAIR data implementation.
- A set of actionable recommendations covering certification, infrastructure, stewardship, costs, rewards, collaboration, training, support, and data management.
- Identification of action owners and suggested actions for improving FAIR data ecosystems.
Conclusions:
- Data infrastructures must evolve and collaborate to effectively support FAIR data principles.
- Community-driven recommendations are crucial for sharpening the roadmap toward a FAIR data ecosystem.
- Addressing identified challenges will accelerate the development and adoption of FAIR data practices within EOSC.
Related Concept Videos
01:25Ethical Standards I
1.3K
The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
1.3K
01:26Equity Theory
136
Equity theory explains how our sense of fairness influences the dynamics of close relationships. Rooted in social psychology, the theory posits that individuals evaluate fairness by comparing the ratio of their contributions to the rewards they receive. Relationship satisfaction is highest when these ratios are perceived as balanced between partners, promoting mutual reciprocity and a sense of justice.Equity vs. Equality in RelationshipsEquity is distinct from equality. Fairness does not...
136
01:29Issues And Trends In Healthcare Delivery System
6.0K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
6.0K
01:24Data Reporting and Recording
5.2K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
5.2K
01:30Health Information Technology and Healthcare Information System
1.1K
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
1.1K
01:03Data Validation
6.2K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Nursing assessment guides are generally based on holistic models rather than medical...
6.2K