[DataCap Application] FileDrive Labs - Datasets Landing Plan V2 - [5/5]

laurarenpanda commented 1 year ago

Data Owner Name

FileDrive Labs

Data Owner Country/Region

China

Data Owner Industry

Life Science / Healthcare

Website

https://filedrive.io/

Social Media

Twitter: https://twitter.com/FileDrive1
Medium: https://medium.com/@FileDrive1
WeChat Offical Account: FileDrive

Total amount of DataCap being requested

5PiB

Weekly allocation of DataCap requested

500TiB

On-chain address for first allocation

f146dbcnpkwoabe2zu5z67ti3cfltuxxxttvgoxwa

Custom multisig

[ ] Use Custom Multisig

Identifier

No response

Share a brief history of your project and organization

FileDrive Datasets Landing Plan is a project for onboarding more valuable public datasets onto the Filecoin network. Through several phases, we plan to bring 10 PiB data and promote 100 PiB storage power growth to Filecoin. 

About FileDrive Datasets

FileDrive Datasets is a platform to effectively connect the huge storage market that Filecoin has built with publishers of public datasets.
The Filecoin network provides reliable, secure, and affordable decentralized storage services, and FileDrive Labs wants to deliver these benefits to end-users by building a public dataset platform.
It is challenging to attract traditional Cloud Storage and Object-base Storage users to the Filecoin network and benefit from it. Developers in the Felicoin ecosystem, such as FileDrive Labs, need to face this challenge together.
As a member of the Filecoin ecosystem, FileDrive Labs has been insisting on developing useful tools to make it easier for users to store their data onto the Filecoin network. 

FileDrive Datasets has integrated a group of tools to provide storage service with the compatibility of both Cloud Storage and Object-base Storage and better user experience to attract more users.
Projects(ongoing) behind:
- Go-Graphsplit: https://github.com/filedrive-team/go-graphsplit
- DS-Cluster: https://github.com/filedrive-team/go-ds-cluster
- Filejoy: https://github.com/filedrive-team/filejoy

Article about FileDrive Datasets on Filecoin Blog:
- Large Datasets: FileDrive: https://filecoin.io/blog/posts/large-datasets-filedrive/

About FileDrive Labs

FileDrive Labs has always defined ourselves as tool developers and infrastructure builders in the Filecoin ecosystem. From 2019, we continuously focus on technical solutions and development based on IPFS protocol and the Filecoin network and do our best to contribute to the community.
Over 80% of our team are qualified engineers, and half of them have more than 10-year development experience in multiple industries, including Communication, the Internet, and blockchain.
Since 2020, we have participated in Slingshot Competition, become one of the top teams, and stored over 5 PiB useful data from public datasets to the Filecoin network.
To contribute to the Filecoin Community, we developed an open-source data prep tool Graphsplit, FIL+ project dashboard filplus.info and storage provider discovery platform filfind,info.
Besides, we have also hold weekly online virtual events named FileDrive Meetup from March 2022, which aims to provide a platform for community members to grasp the latest trends of the Filecoin network and our work and research.

Please check the following links for more details.
- GitHub: https://github.com/filedrive-team
- Twitter: https://twitter.com/FileDrive1
- Eventbrite: https://www.eventbrite.hk/o/filedrive-labs-42456337463
- YouTube Channel: https://www.youtube.com/channel/UCxcZC1dtBUlQvZY7DX13W1w
- Medium: https://medium.com/@FileDrive1

Is this project associated with other projects/ecosystem stakeholders?

No

If answered yes, what are the other projects/ecosystem stakeholders

No response

Describe the data being stored onto Filecoin

FileDrive Datasets Landing Plan #2
- Datasets: 10

List of Datasets in #2:

1. Transiting Exoplanet Survey Satellite (TESS)
- The Transiting Exoplanet Survey Satellite (TESS) is a multi-year survey that will discover exoplanets in orbit around bright stars across the entire sky using high-precision photometry. The survey will also enable a wide variety of stellar astrophysics, solar system science, and extragalactic variability studies. More information about TESS is available at MAST and the TESS Science Support Center.
- https://registry.opendata.aws/tess/
- License: STScI herby grants the non-exclusive, royalty free, non-transferable, worldwide right and license to use, reproduce and publicly display in all media public data from the TESS mission.
- Size: 285.6 TiB

2. Oxford Nanopore Technologies Benchmark Datasets
- The ont-open-data registry provides reference sequencing data from Oxford Nanopore Technologies to support, 1) Exploration of the characteristics of nanopore sequence data. 2) Assessment and reproduction of performance benchmarks 3) Development of tools and methods. The data deposited showcases DNA sequences from a representative subset of sequencing chemistries. The datasets correspond to publicly-available reference samples (e.g. Genome In A Bottle reference cell lines). Raw data are provided with metadata and scripts to describe sample and data provenance.
- https://registry.opendata.aws/ont-open-data/
- License: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
- Size: 60.3 TiB

3. Community Earth System Model v2 ARISE (CESM2 ARISE)
- Data from ARISE-SAI Experiments with CESM2
- https://registry.opendata.aws/ncar-cesm2-arise/
- License: Creative Commons Attribution 4.0 International (CC BY 4.0)
- Size: 263.5 TiB

4. NOAA Wave Ensemble Reforecast
- This is a 20-year global wave reforecast generated by WAVEWATCH III model (https://github.com/NOAA-EMC/WW3) forced by GEFSv12 winds (https://noaa-gefs-retrospective.s3.amazonaws.com/index.html). The wave ensemble was run with one cycle per day (at 03Z), spatial resolution of 0.25°X0.25° and temporal resolution of 3 hours. There are five ensemble members (control plus four perturbed members) and, once a week (Wednesdays), the ensemble is expanded to eleven members. The forecast range is 16 days and, once a week (Wednesdays), it extends to 35 days. More information about the wave modeling, wave grids and calibration can be found in the WAVEWATCH III regtest ww3_ufs1.3 (https://github.com/NOAA-EMC/WW3/tree/develop/regtests/ww3_ufs1.3).
- https://registry.opendata.aws/noaa-wave-ensemble-reforecast/
- License: Open Data. There are no restrictions on the use of this data.
- Size: 114.3TiB

5.UCSC Genome Browser Sequence and Annotations
- The UCSC Genome Browser is an online graphical viewer for genomes, a genome browser, hosted by the University of California, Santa Cruz (UCSC). The interactive website offers access to genome sequence data from a variety of vertebrate and invertebrate species and major model organisms, integrated with a large collection of aligned annotations. This dataset is a copy of the MySQL tables in MyISAM binary and tab-sep format and all binary files in custom formats, sometimes referred as 'gbdb'-files. Data from the UCSC Genome Browser is free and open for use by anyone. However, every genome annotation track has been created by an academic research group, or, in a few cases, by commercial companies. Please acknowledge them by citing them. The information can be found by going to https://genome.ucsc.edu, selecting the respective genome assembly and clicking on the data track. At the end of the documentation, we provide a list of references and acknowledgements.
- https://registry.opendata.aws/ucsc-genome-browser/
- License: https://genome.ucsc.edu/license/
- Size:  81.7 TiB

6.Open Observatory of Network Interference (OONI)
- A free software, global observation network for detecting censorship, surveillance and traffic manipulation on the internet.
- https://registry.opendata.aws/ooni/
- License: Creative Commons Attribution 4.0 International (CC BY 4.0)
- Size: 135 TiB

7.OpenProteinSet
- Multiple sequence alignments (MSAs) for 132,000 unique Protein Data Bank (PDB) chains, covering 640,000 PDB chains in total, and 4,850,000 UniClust30 clusters. Template hits are also provided for the PDB chains and 270,000 UniClust30 clusters chosen for maximal diversity and MSA depth. MSAs were generated with HHBlits (-n3) and JackHMMER against MGnify, BFD, UniRef90, and UniClust30 while templates were identified from PDB70 with HHSearch, all according to procedures outlined in the supplement to the AlphaFold 2 Nature paper, Jumper et al. 2021. We expect the database to be broadly useful to structural biologists training or validating deep learning models for protein structure prediction and related tasks.
- https://registry.opendata.aws/openfold/
- License: Creative Commons Attribution 4.0 International (CC BY 4.0)
- Size: 4.9 TiB

8.AI2 Diagram Dataset (AI2D)
- 4,817 illustrative diagrams for research on diagram understanding and associated question answering.
- https://registry.opendata.aws/allenai-diagrams/
- License: Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
- Size: 6.4 TiB

9. Legal Entity Identifier (LEI) and Legal Entity Reference Data (LE-RD)
- The Legal Entity Identifier (LEI) is a 20-character, alpha-numeric code based on the ISO 17442 standard developed by the International Organization for Standardization (ISO). It connects to key reference information that enables clear and unique identification of legal entities participating in financial transactions. Each LEI contains information about an entity’s ownership structure and thus answers the questions of 'who is who’ and ‘who owns whom’. Simply put, the publicly available LEI data pool can be regarded as a global directory, which greatly enhances transparency in the global marketplace. The Financial Stability Board (FSB) has reiterated that global LEI adoption underpins “multiple financial stability objectives” such as improved risk management in firms as well as better assessment of micro and macro prudential risks. As a result, it promotes market integrity while containing market abuse and financial fraud. Last but not least, LEI rollout “supports higher quality and accuracy of financial data overall”. The publicly available LEI data pool is a unique key to standardized information on legal entities globally. The data is registered and regularly verified according to protocols and procedures established by the Regulatory Oversight Committee. In cooperation with its partners in the Global LEI System, the Global Legal Entity Identifier Foundation (GLEIF) continues to focus on further optimizing the quality, reliability and usability of LEI data, empowering market participants to benefit from the wealth of information available with the LEI population. The drivers of the LEI initiative, i.e. the Group of 20, the FSB and many regulators around the world, have emphasized the need to make the LEI a broad public good. The Global LEI Index, made available by GLEIF, greatly contributes to meeting this objective. It puts the complete LEI data at the disposal of any interested party, conveniently and free of charge. The benefits for the wider business community to be generated with the Global LEI Index grow in line with the rate of LEI adoption. To maximize the benefits of entity identification across financial markets and beyond, firms are therefore encouraged to engage in the process and get their own LEI. Obtaining an LEI is easy. Registrants simply contact their preferred business partner from the list of LEI issuing organizations available on the GLEIF website.
- https://registry.opendata.aws/lei/
- License: Creative Commons (CC0) license
- Size: 6.0 TiB

10. COVID-19 Genome Sequence Dataset
- A centralized sequence repository for all records containing sequence associated with the novel corona virus (SARS-CoV-2) submitted to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). Included are both the original sequences submitted by the principal investigator as well as SRA-processed sequences that require the SRA Toolkit for analysis. Additionally, submitter provided metadata included in associated BioSample and BioProject records is available alongside NCBI calculated data, such k-mer based taxonomy analysis results, contiguous assemblies (contigs) and associated statistics such as contig length, blast results for the assembled contigs, contig annotation, blast databases of contigs and their annotated peptides, and VCF files generated for each record relative to the SARS-CoV-2 RefSeq record. Finally, metadata is additionally made available in parquet format to facilitate search and filtering using the AWS Athena Service.
- https://registry.opendata.aws/ncbi-covid-19/
- License: NIH Genomic Data Sharing Policy
- Size: 1.2 PiB

Where was the data currently stored in this dataset sourced from

My Own Storage Infra

If you answered "Other" in the previous question, enter the details here

No response

How do you plan to prepare the dataset

IPFS, graphsplit

If you answered "other/custom tool" in the previous question, enter the details here

No response

Please share a sample of the data

FileDrive Datasets: 
https://datasets.filedrive.io/

Original Source:
1. Transiting Exoplanet Survey Satellite (TESS)
- https://registry.opendata.aws/tess/

2. Oxford Nanopore Technologies Benchmark Datasets
- https://registry.opendata.aws/ont-open-data/

3. Community Earth System Model v2 ARISE (CESM2 ARISE)
- https://registry.opendata.aws/ncar-cesm2-arise/

4. NOAA Wave Ensemble Reforecast
- https://registry.opendata.aws/noaa-wave-ensemble-reforecast/

5.UCSC Genome Browser Sequence and Annotations
- https://registry.opendata.aws/ucsc-genome-browser/

6.Open Observatory of Network Interference (OONI)
- https://registry.opendata.aws/ooni/

7.OpenProteinSet
- https://registry.opendata.aws/openfold/

8.AI2 Diagram Dataset (AI2D)
- https://registry.opendata.aws/allenai-diagrams/

9. Legal Entity Identifier (LEI) and Legal Entity Reference Data (LE-RD)
- https://registry.opendata.aws/lei/

10. COVID-19 Genome Sequence Dataset
- https://registry.opendata.aws/ncbi-covid-19/

Confirm that this is a public dataset that can be retrieved by anyone on the Network

[X] I confirm

If you chose not to confirm, what was the reason

No response

What is the expected retrieval frequency for this data

Weekly

For how long do you plan to keep this dataset stored on Filecoin

More than 3 years

In which geographies do you plan on making storage deals

Greater China, Asia other than Greater China, North America, Europe, Australia (continent)

How will you be distributing your data to storage providers

HTTP or FTP server, IPFS, Shipping hard drives

How do you plan to choose storage providers

Slack, Filmine

If you answered "Others" in the previous question, what is the tool or platform you plan to use

No response

If you already have a list of storage providers to work with, fill out their names and provider IDs below

Please check the Checker Reports of our previous LDN applications:
- https://github.com/filecoin-project/filecoin-plus-large-datasets/issues/1266
- https://github.com/filecoin-project/filecoin-plus-large-datasets/issues/1267
- https://github.com/filecoin-project/filecoin-plus-large-datasets/issues/1268

How do you plan to make deals to your storage providers

Lotus client

If you answered "Others/custom tool" in the previous question, enter the details here

No response

Can you confirm that you will follow the Fil+ guideline

Yes

kevzak commented 1 year ago

checker:manualTrigger

filplus-checker-app[bot] commented 1 year ago

DataCap and CID Checker Report Summary[^1]

Retrieval Statistics

⚠️ All retrieval success ratios are below 1%.

Overall Graphsync retrieval success rate: 0.08%
Overall HTTP retrieval success rate: 0.00%
Overall Bitswap retrieval success rate: 0.00%

Storage Provider Distribution

✔️ Storage provider distribution looks healthy.

Deal Data Replication

⚠️ 52.21% of deals are for data replicated across less than 4 storage providers.

Deal Data Shared with other Clients[^3]

⚠️ CID sharing has been observed. (Top 3)

2.12 PiB - f1w7oommwezzhsyfh4ax7tbtd7zgl6i4m6hvnvd4i - FileDriveLabs
1.25 PiB - f1bycr5r3ymkgqvkuxoemgsmnuawyawptwj44mqdi - FileDrive Labs
1.17 PiB - f1mnahpxpyrazryxuh24rcyelb4ksgwaztvskjzcq - FileDriveLabs

[^1]: To manually trigger this report, add a comment with text checker:manualTrigger

[^2]: Deals from those addresses are combined into this report as they are specified with checker:manualTrigger

[^3]: To manually trigger this report with deals from other related addresses, add a comment with text checker:manualTrigger <other_address_1> <other_address_2> ...

Full report

Click here to view the CID Checker report. Click here to view the Retrieval report.

data-programs commented 1 year ago

This user’s identity has been verified through filplus.storage

filecoin-project / filecoin-plus-large-datasets