

Context and issues
Hot vs warm vs cold vs ice storage
Carbon impact
Resources





| Aspect | Hot Data | Cold Data |
|---|---|---|
| Access Frequency | Frequently accessed | Infrequently accessed |
| Storage Type | High-performance storage (SSDs, in-memory databases) |
Cost-effective storage (HDDs, magnetic tapes, cloud archives) |
| Retrieval Speed | Fast retrieval required | Slower retrieval acceptable |
| Use Case | Real-time transactions, active user sessions, real-time analytics | Historical records, backups, archived files |
| Cost | Generally higher due to performance requirements | Generally lower due to slower access speeds |
| Data management | Requires optimization for speed and efficiency | Focused on long-term storage and cost-efficiency |

Hot data and Cold data serve different purposes in data management. Hot data is important for applications requiring fast access and real time processing, but it comes at a higher cost. Cold data, on the other hand, is used for long-term storage and is less costly but slower to access2.
| Repository | Supporting by | Type | Disciplinary fields | Accepted data (keywords) | Embargo | Persistent identifier | Volume limit |
|---|---|---|---|---|---|---|---|
| InDoRES | CNRS-Ecology, MNHN | Thematic & Institutional | Ecology, Environment, Bio-archaeology | Environmental, ecological and geographical data | Yes | DOI | 2 GB per data set |
| EaSy Data | Data Terra, BRGM | Thematic | Earth and Environmental Sciences | Long tail data from the earth system and environment (example: project issues) | Yes (< 2 yr) |
DOI | 5 GB per file, 100 GB per deposit |
| SEANOE | Ifremer | Thematic & Institutional | Oceanography | Georeferenced marine data | Yes (< 2 yr) |
DOI | 100 GB |
| Data SUD | IRD | Institutional | All fields covered by IRD agents | ??? | ??? | DOI | ??? |
| GBIF | International GBIF community | Thematic | Life sciences, Biodiversity, Animal biology, Plant biology, Ecology, Environment; Ecosystems | Taxa, occurrence data, sampling data, all standardized according to Darwin core or ABCD standards. | Yes | DOI | no |
| Recherche Data Gouv | Recherche Data Gouv | Generic | All fields | All | Yes | DOI | ??? |

The GAIA Data project aims to develop and implement an integrated and distributed platform of services and data for the observation, modeling and understanding of the Earth system, biodiversity and the environment


Carbon footprint: ideally, bring the calculation closer to the {meta}data and not the other way around
How much energy is used in saving to the cloud? That’s a complicated question. It takes energy to get the data to the data center—miles of fiber optic cables, studded with other fixtures of internet infrastructure that all require power along the way. At the center, your data is stored multiple times on hard disks, and the constant activity of all those disks creates a lot of heat, which necessitates energy-intensive air conditioners to protect the equipment from overheating1.
Various studies estimate them to be between 2.3 and 3.7% of global CO₂ emissions, which is equivalent to the emissions of the entire aviation industry2.
The ecological dynamics we find ourselves in are not entirely a consequence of design limits, but of human practices and choices — among individuals, communities, corporations, and governments — combined with a deficit of will and imagination to bring about a sustainable Cloud. The Cloud is both cultural and technological. Like any aspect of culture, the Cloud’s trajectory — and its ecological impacts — are not predetermined or unchangeable. Like any aspect of culture, they are mutable3.
When a highly dangerous fungus escapes from a secret laboratory, a former bioterrorism agent is called back into action. Alongside two young employees, he must confront an invisible and out-of-control threat1

