Initiatives
Open Science is a collaborative and transparent approach to scientific research. It promotes the sharing of information, computational resources, data, software, and physical tools. As a movement Open Science endeavours to make so-called research objects accessible to all levels of society. As a philosophical foundation, Open Science connects advanced technologies to foster innovation and accelerate scientific data-driven discovery.
Open Data Announcements from federal agencies require funded research projects to immediately publish and make openly available their data without embargo.
About
The term 'Digital Twin' has existed since the early 1960's when it was first used to describe simulation models for the Apollo space program.
Digital twins should integrate real-time data from the physical counterpart to simulate, predict, and optimize performance in a virtual environment. Digital twins are common in industrial applications, i.e., Industry 4.0 or Fourth Industrial Revolution (4IR), and in civil engineering. An open source digital twin for IoT is Eclipse Ditto and iTwin.js for infrastructure.
In the last five years, mentions of Digital Twins have grown exponentially in the literature. Semantically, terms like 'digital twin', 'simulation', 'prototype', or 'model' are used interchangeably in research applications. A digital twin is a virtual model that accurately represents a physical object, system, or process.
Highlighting ICDI support of Digital Twins research
Tyson Swetnam, ICDI's Director of Open Science Initiatives, is also a co-Principal Investigator of CyVerse.org which currently supports multiple awards on Digital Twins.
Digital Twin Projects @ University of Arizona
KMAP List of Faculty and Grants in Digital Twin Research
About
Open Data refer to data that are freely available for anyone to access, use, modify, and share without restrictions. Open Data promote transparency and collaboration which enhance our ability to collaborate, reproduce research results, and empowers decision-makers to make informed choices across society.
Guiding Principles
FAIR
The FAIR principles aim to make data:
- Findable: Data should be easy to locate for both humans and computers, with clear and rich metadata descriptions.
- Accessible: Once found, data should be retrievable through open and standardized communication protocols.
- Interoperable: Data should use shared standards and languages to enable integration with other datasets.
- Reusable: Data should be well-documented and licensed in a way that permits reuse and repurposing.
Source: Wilkinson et al., Scientific Data (2016)
CARE
The CARE principles focus on the governance of data relating to Indigenous Peoples:
- Collective Benefit: Data ecosystems should be designed to deliver benefits for Indigenous communities.
- Authority to Control: Indigenous Peoples have the right to govern the collection and use of their data.
- Responsibility: Those working with Indigenous data have a duty to support Indigenous data governance.
- Ethics: All data activities must be grounded in ethical practices that respect Indigenous rights.
Source: Global Indigenous Data Alliance (GIDA)
TRUST
The TRUST principles provide guidance for trustworthy data repositories:
- Transparency: Repositories should openly share information about their services and data holdings.
- Responsibility: Clear accountability mechanisms should be in place for data stewardship.
- User Focus: Services should meet the needs of the data community, including both providers and users.
- Sustainability: Repositories should have sustainable funding and governance models.
- Technology: Reliable and secure technical infrastructure is essential for data preservation and access.
Source: Lin et al., Scientific Data (2020)
By adhering to the FAIR, CARE, and TRUST principles, our Open Data initiative ensures data remains a valuable, accessible, and ethical resource.
University of Arizona Data Commons
University of Arizona faculty and staff have multiple resources for storing their internal and extramural data.
University Libraries Data Cooperative Data Management
University supported Storage, Back-ups & Security options (Box, Drive, HPC)
CyVerse Data Store supports research dataset at Petabyte scale, contact CyVerse staff for details.
- Local Contexts metadata are integrated into CyVerse Data Store, providing indigenous researchers with the ability to add Traditional Knowledge (TK) and Biocultural (BC) Labels.
Open Data Licenses
ICDI provides access to Planet Labs small satellite data sets (PlanetScope global mosaic product, SkySat <1m tasking). Sign up for access.
About
ICDI works with University of Arizona Health Sciences and RII to support research into precision health care and precision medicine.
We are partners with the Data Science Institute (DSI) and Center for Biomedical Informatics and Biostatistics (CB2).
Secure, Trusted, Private
Supported Projects
Digital Twins
By applying Open Science principles to digital twins researchers can openly share their models and simulation results. Openness enables reproducibility via collective validation and iteration. The creation of digital twins across various fields, will enhance the accuracy of forecasting while also fostering interdisciplinary collaboration.
Data Commons
Data commons are shared platforms where data, tools, and services are collectively managed and accessed. Under the Open Science framework, data commons become collaborative environments that encourage the sharing of large datasets and computational tools, supporting a culture of openness and mutual advancement.
Precision Health Care
Open Science plays a crucial role in advancing precision health care by promoting the open sharing of biomedical data, research findings, and analytical tools. By making genomic data, clinical trial results, and other health-related information accessible while ensuring patient privacy and ethical considerations, e.g., HIPAA privacy, researchers and clinicians can develop more personalized and effective treatments. This collaborative approach accelerates the understanding of individual variability in genes, environment, and lifestyle, which is essential for tailoring medical care to individual needs.
By intertwining these elements within the Open Science paradigm, the scientific community can achieve greater efficiency, inclusivity, and impact. Open Science not only democratizes access to scientific knowledge and resources but also enhances the collective ability to address complex global challenges through shared innovation.