feat: add initial YAML structure

datasets/3kricegenome.yaml

@@ -4,6 +4,10 @@ Documentation: https://github.com/awslabs/open-data-docs/tree/main/docs/3kricege
 Contact: http://iric.irri.org/contact-us
 ManagedBy: '[International Rice Research Institute](https://www.irri.org/)'
 UpdateFrequency: Not updated
+Collabs:
+  ASDI:
+    Tags:
+      - agriculture
 Tags:
   - agriculture
   - food security

datasets/aef-source.yaml

@@ -0,0 +1,24 @@
+Name: Google Satellite Embedding V1
+Description: COG (Cloud-Optimized GeoTIFF) files that together contain the AlphaEarth Foundations annual Satellite Embedding dataset. It contains the annual embeddings for the years from 2018 to 2024, inclusive.
+Documentation: https://source.coop/tge-labs/aef
+Contact: https://cloudnativegeo.org/join
+ManagedBy: "[Source Cooperative](https://source.coop/)"
+UpdateFrequency: As new data versions become available
+Tags:
+  - aws-pds
+  - machine learning
+  - satellite imagery
+  - aerial imagery
+  - earth observation
+  - imaging
+License: CC-BY 4.0
+Citation: "The AlphaEarth Foundations Satellite Embedding dataset is produced by Google and Google DeepMind."
+Resources:
+  - Description: Google Satellite Embedding V1
+    ARN: arn:aws:s3:::us-west-2.opendata.source.coop/tge-labs/aef
+    Region: us-west-2
+    Type: S3 Bucket
+    Explore:
+    - '[Browse Dataset](https://source.coop/tge-labs/aef/)'
+ADXCategories:
+  - Environmental Data 

datasets/africa-field-boundary-labels.yaml

@@ -13,6 +13,10 @@ Documentation: Information on the primary dataset can be found [here](https://gi
 Contact: airg@clarku.edu
 ManagedBy: "[The Agricultural Impacts Research Group](https://agroimpacts.info/)"
 UpdateFrequency: "Updated versions of the dataset are added as they are developed"
+Collabs:
+  ASDI:
+    Tags:
+      - agriculture
 Tags:
   - agriculture
   - machine learning

datasets/ag-loam.yaml

@@ -9,6 +9,10 @@ Documentation: https://github.com/UCR-Robotics/AG-LOAM
 Contact: Hanzhe Teng (hteng007@ucr.edu), Konstantinos Karydis (kkarydis@ece.ucr.edu)
 ManagedBy: "[Autonomous Robots and Control Systems Lab](https://sites.google.com/view/arcs-lab)"
 UpdateFrequency: NA
+Collabs:
+  ASDI:
+    Tags:
+      - agriculture
 Tags:
   - aws-pds
   - robotics

datasets/ai3.yaml

@@ -0,0 +1,37 @@
+Name: AI3 Protein-Ligand Binding Affinity Dataset
+Description: >
+  The rapid advancement of computing technologies, particularly artificial intelligence (AI), has revolutionized various domains, including drug discovery. Curated datasets are crucial for developing reliable, generalizable, and accurate models for practical applications. Generating experimental data on a large scale is an expensive and arduous process. In domains such as medical diagnostics where real-life data is hard to obtain, synthetic data has been shown to be extremely valuable. We, teams from IIIT Hyderabad, Intel, AWS, and Insilico Medicine, have performed physics-based calculations (molecular dynamics simulations) on about 20,000 protein-ligand complexes. The dataset comprises molecular dynamics snapshots, binding affinities calculated using the MM-PBSA method, and individual energy components, including electrostatic and van der Waals interactions. DatasetFileFormats essentially incorporate i. 3D coordinates of the protein-ligand complexes (pdb) in tar.gz files, and ii. CSV files containing the energy data. DatasetUsages are on i. ML scoring function for predicting binding affinities of given protein-ligand complexes, ii. Classification models for predicting correct binding poses of ligands, iii. identification of cryptic binding pockets, and iv. optimization of binding features by exploiting the individual components of the energy (experimental data has only the total binding affinity). Further, the novelty of the dataset highlights the fact that existing AI/ML training datasets lack dynamic data and are inherently biased. Further, binding affinity data existing in the literature are obtained from different experimental protocols. Therefore, this dataset has been uniquely created (from the same computational protocols) followed by free energy calculations with molecular dynamics (MD) simulations. The dynamic data-enriched protein-ligand coordinates can be used to effectively train convolutional neural network-based regression models for more accurate binding affinity prediction.
+Documentation: https://github.com/devalab/AI3
+Contact: devalab@iiit.ac.in
+ManagedBy: International Institute of Information Technology Hyderabad
+UpdateFrequency: Not updated
+Tags:
+  - pharmaceutical
+  - simulations
+  - health
+  - life sciences
+  - machine learning
+  - protein
+  - molecular dynamics
+  - aws-pds
+License: https://devalab.in/AI3.html
+Resources:
+  - Description: ai3data bucket includes coordinates and the energetics of ~20,000 protein-ligand binding affinity datasets. The subfolders of ai3data bucket consist of Version 1, Version2 and Version 3. Version1 contains the total Size of 10.4 GiB (Initial structure of the protein-ligand complex and the average binding affinities along with average energy components). Version2 contains the total Size of 1.2 TiB (Five trajectories of protein-ligand complex (200 snapshots in all) and the closest two water molecules for each of the protein-ligand complex, and the time series of the binding affinities along with average energy components). Version3 contains the total Size of 10.7 TiB (Five trajectories of completely solvated protein-ligand complex (200 snapshots in all), and the time series of binding affinities along with average energy components).
+    ARN: arn:aws:s3:::ai3data
+    Region: us-east-1
+    Type: S3 Bucket
+DataAtWork:
+  Tutorials:
+    - Title: "AI3: Protein-Ligand Binding Affinity Dataset"
+      URL: https://github.com/devalab/AI3
+      AuthorName: Deva Priyakumar Lab
+      AuthorURL: https://github.com/devalab  
+  Publications:
+    - Title: "PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications"
+      URL: https://www.nature.com/articles/s41597-022-01631-9
+      AuthorName: U. Deva Priyakumar
+      AuthorURL: https://devalab.in/
+    - Title: "PLAS-20k: Extended Dataset of Protein-Ligand Affinities from MD Simulations for Machine Learning Applications"
+      URL: https://www.nature.com/articles/s41597-023-02872-y
+      AuthorName: U. Deva Priyakumar
+      AuthorURL: https://devalab.in

datasets/allen-hmba-releases.yaml

@@ -0,0 +1,46 @@
+Name: Human and Mammalian Brain Atlas
+Description:
+  Human and Mammalian Brain Atlas (HMBA) is a major atlas of the BRAIN Initiative Cell Atlas Network (BICAN) that proposes to establish a comprehensive, 
+  highly granular cell atlas in complete adult human, macaque, and marmoset brains that links brain structure, function and cellular architecture.
+  Release artifacts have been made available in this OpenData bucket to enable utilization along with their paper publications by the neuroscience community.  
+Documentation: https://portal.brain-map.org/explore/hmba
+Contact: awspds@alleninstitute.org
+ManagedBy: "[Allen Institute](http://www.alleninstitute.org/)"
+UpdateFrequency: Never
+Tags:
+  - aws-pds
+  - biology
+  - gene expression
+  - neurobiology
+  - life sciences
+  - single-cell transcriptomics
+  - Mus musculus
+  - Homo sapiens
+  - non-human primate
+License: http://www.alleninstitute.org/legal/terms-use/
+Citation:
+Resources:
+  - Description: Project data files in a public bucket
+    ARN: arn:aws:s3:::allen-hmba-releases
+    Region: us-west-2
+    Type: S3 Bucket
+DataAtWork:
+  Tutorials:
+    - Title: Human-Mammalian Brain - Basal Ganglia - Data
+      URL: https://alleninstitute.github.io/abc_atlas_access/descriptions/HMBA-BG_dataset.html
+      AuthorName: Allen Institute for Brain Science
+      AuthorURL: www.alleninstitute.org
+    - Title: Human-Mammalian Brain - CCF Book
+      URL: https://alleninstitute.github.io/CCF-MAP/
+      AuthorName: Allen Institute for Brain Science
+      AuthorURL: www.alleninstitute.org
+  Tools & Applications:
+    - Title: HMBA Basal Ganglia resources in Brain Knowledge Platform's Data Catalog
+      URL: https://knowledge.brain-map.org/data/POZ2HCPBT60DSDJ8UA7
+      AuthorName: Allen Institute for Brain Science
+      AuthorURL: www.alleninstitute.org
+
+
+
+
+

datasets/alliance-genome-resources.yaml

@@ -0,0 +1,85 @@
+Name: Alliance of Genome Resources
+Description: The Alliance of Genome Resources is a consortium that integrates genomic, genetic, and molecular data from leading model organism databases including Drosophila melanogaster, Caenorhabditis elegans, Danio rerio (zebrafish), Mus musculus (mouse), Rattus norvegicus (rat), Saccharomyces cerevisiae (yeast), Xenopus laevis and Xenopus tropicalis (frogs), and human reference data. The Alliance provides comprehensive datasets including gene annotations, disease associations, expression data (bulk and single-cell RNA-Seq), protein and genetic interactions, orthology relationships, variants and alleles, and complete genome sequences with annotations. Data is organized into Alliance-wide integrated datasets and organism-specific collections, supporting comparative genomics, disease modeling, and functional genomics research.
+Documentation: https://github.com/alliance-genome/agr_open_data
+Contact: help@alliancegenome.org
+ManagedBy: Alliance of Genome Resources Consortium
+UpdateFrequency: Quarterly releases (every ~3 months)
+Tags:
+  - aws-pds
+  - genomic
+  - bioinformatics
+  - biology
+  - gene expression
+  - life sciences
+  - genetic
+  - genome
+  - Drosophila melanogaster
+  - Caenorhabditis elegans
+  - Danio rerio
+  - Mus musculus
+  - Rattus norvegicus
+  - Homo sapiens
+  - transcriptomics
+  - protein
+  - vcf
+  - fasta
+License: Most Alliance data is available under CC0 1.0 Universal (Public Domain Dedication). Some datasets may use CC-BY 4.0 (attribution required). Full details at https://www.alliancegenome.org/terms-of-use
+Citation: Alliance of Genome Resources Consortium. Alliance of Genome Resources Portal - unified model organism research platform. Nucleic Acids Research (2023). https://doi.org/10.1093/nar/gkac1003
+Resources:
+  - Description: Alliance-wide integrated datasets including disease associations, gene expression, molecular and genetic interactions, orthology relationships, gene descriptions, and variants across all Alliance organisms. Data is organized by release version (8.3.0/, 8.2.0/, etc.), then by data type, with organism-specific collections for FB (FlyBase/Drosophila), MGI (Mouse), RGD (Rat), SGD (Yeast), WB (Worm), XBXL/XBXT (Xenopus), ZFIN (Zebrafish), and HUMAN reference data. Available in TSV, JSON, and VCF formats.
+    ARN: arn:aws:s3:::alliance-genome-downloads
+    Region: us-east-1
+    Type: S3 Bucket
+    Explore:
+      - '[Browse Bucket](https://alliance-genome-downloads.s3.amazonaws.com/)'
+  - Description: FlyBase-specific data for Drosophila melanogaster and related species, including gene annotations, GO annotations, expression data (bulk RNA-Seq, single-cell RNA-Seq), disease associations, phenotypes, interactions, orthologs, genome sequences (FASTA), and genome annotations (GFF3/GTF). Data organized by release (current/, FB2025_04/, etc.) with precomputed analysis files and complete Chado XML database dumps. Publicly accessible via HTTPS for direct download without AWS credentials.
+    ARN: arn:aws:s3:::s3ftp.flybase.org
+    Region: us-east-1
+    Type: S3 Bucket
+    Explore:
+      - '[Browse via HTTPS](https://s3ftp.flybase.org/releases/current/)'
+DataAtWork:
+  Tutorials:
+    - Title: Alliance of Genome Resources AWS Data Access Tutorials
+      URL: https://github.com/alliance-genome/agr_open_data/blob/main/TUTORIAL.md
+      AuthorName: Alliance of Genome Resources Consortium
+      AuthorURL: https://www.alliancegenome.org
+  Tools & Applications:
+    - Title: Alliance of Genome Resources Portal
+      URL: https://www.alliancegenome.org
+      AuthorName: Alliance of Genome Resources Consortium
+      AuthorURL: https://www.alliancegenome.org
+    - Title: FlyBase - Drosophila Database
+      URL: https://flybase.org
+      AuthorName: FlyBase Consortium
+      AuthorURL: https://flybase.org
+    - Title: WormBase - C. elegans Database
+      URL: https://www.wormbase.org
+      AuthorName: WormBase Consortium
+      AuthorURL: https://www.wormbase.org
+    - Title: ZFIN - Zebrafish Database
+      URL: https://zfin.org
+      AuthorName: ZFIN
+      AuthorURL: https://zfin.org
+    - Title: MGI - Mouse Genome Database
+      URL: http://www.informatics.jax.org
+      AuthorName: MGI
+      AuthorURL: http://www.informatics.jax.org
+    - Title: RGD - Rat Genome Database
+      URL: https://rgd.mcw.edu
+      AuthorName: RGD
+      AuthorURL: https://rgd.mcw.edu
+    - Title: SGD - Saccharomyces Genome Database
+      URL: https://www.yeastgenome.org
+      AuthorName: SGD
+      AuthorURL: https://www.yeastgenome.org
+    - Title: Xenbase - Xenopus Database
+      URL: http://www.xenbase.org
+      AuthorName: Xenbase
+      AuthorURL: http://www.xenbase.org
+  Publications:
+    - Title: Alliance of Genome Resources Portal - unified model organism research platform
+      URL: https://doi.org/10.1093/nar/gkac1003
+      AuthorName: Alliance of Genome Resources Consortium
+ADXCategories:
+  - Healthcare & Life Sciences Data

datasets/amazon-last-mile-challenges.yaml

@@ -7,6 +7,10 @@ Contact: lastmile-research-challenge@amazon.com
 ManagedBy: "[Amazon](https://www.amazon.com/)"
 UpdateFrequency: None
 
+Collabs:
+  ASDI:
+    Tags:
+      - infrastructure
 Tags:
   - transportation
   - machine learning