If we want to store imaging data on the cloud and allow scientists to experiment with this data with interactive local tools (e.g., Jupyter notebooks), we should provide an easy interface to retrieve this data. We should future-proof this model for extremely large image sets with multiple dimensions, where users may want to pull slices of this data without having to download the entire image set.
An image set will be stored in a tiled format such that ranged requests can be used to efficiently fetch slices of the data. The tiles of the image set is described by a manifest, which is itself broken up into multiple files for easy consumption.
There should be a python API that allows users to point at an image set, ranges across multiple dimensions, and yields the data in numpy format. The python API should retrieve the table of contents, calculate the objects needed, fetch them in parallel, decode them, and slice out the data needed.
The location for each tile is given in coordinates and indices. Coordinates is the location of the tile in geometric space, and indices is the location of the tile in non-geometric space. Together, coordinates and indices resolve exactly where the tile is in the n-dimensional space.
Each image set is described by a manifest, which is a hierarchical tree of JSON table-of-contents documents. The leaf documents (tile sets) describe a list of tiles. The non-leaf documents (collections) contain a map from an arbitrary unique name (within the space of the entire image) to relative paths or URLs containing either other collections or tile sets.
A collection should have the following fields:
| Field Name | Type | Required | Description |
| version | string | Yes | Semantic versioning of the file format. |
| contents | dict | Yes | Map of names to relative paths or URLs of collections or tile sets. |
| extras | dict | No | Additional application-specific payload. The vocabulary and the schema are uncontrolled. |
A tile set should have the following fields:
| Field Name | Type | Required | Description |
| version | string | Yes | Semantic versioning of the file format. |
| dimensions | list | Yes | Names of the dimensions. Dimensions must include x and y. |
| tiles | dict | Yes | See Tiles |
| shape | dict | Yes | Maps each non-geometric dimension to the possible number of values for that dimension for the tiles in this Tile Set. |
| default_tile_shape | dict | No | Mapping from the pixel dimensions to their sizes. |
| default_tile_format | string | No | Default file format of the tiles. |
| zoom | dict | No | See Zoom |
| extras | dict | No | Additional application-specific payload. The vocabulary and the schema are uncontrolled. |
Each item in the tiles section describes a file:
| Field Name | Type | Required | Description |
| file | string | Yes | Relative path to the file. |
| coordinates | dict | Yes | Maps each of the dimensions in geometric space, either x, y, or z, to either a single dimension value, or a tuple specifying the range for that dimension. The x and y coordinates must be provided as ranges. Each of the dimensions here must be specified in the Tile Set. |
| indices | dict | Yes | Maps each of the dimensions not in geometric space to the value for this tile. Each of the dimensions here must be specified in the Tile Set. The values of the indices must be non-negative integers, and every value up to but not including the maximum specified in the shape field of the Tile Set must be represented. |
| tile_shape | dict | No | Mapping from the pixel dimensions to their sizes. If this is not provided, it defaults to default_tile_shape in the Tile Set). If neither is provided, the tile shape is inferred from actual file. |
| tile_format | string | No | File format of the tile. If this is not provided, it defaults to default_tile_format in the Tile Set). If neither is provided, the tile format is inferred from actual file. |
| sha256 | string | No | SHA256 checksum of the tile data. |
| extras | dict | No | Additional application-specific payload. The vocabulary and the schema are uncontrolled. |