  Scientific exploitation of the ever increasing volumes of astronomical data
requires efficient and practical methods for data access, visualisation, and
analysis. Hierarchical sky tessellation techniques enable a multi-resolution
approach to organising data on angular scales from the full sky down to the
individual image pixels. Aims. We aim to show that the Hierarchical progressive
survey (HiPS) scheme for describing astronomical images, source catalogues, and
three-dimensional data cubes is a practical solution to managing large volumes
of heterogeneous data and that it enables a new level of scientific
interoperability across large collections of data of these different data
types. Methods. HiPS uses the HEALPix tessellation of the sphere to define a
hierarchical tile and pixel structure to describe and organise astronomical
data. HiPS is designed to conserve the scientific properties of the data
alongside both visualisation considerations and emphasis on the ease of
implementation. We describe the development of HiPS to manage a large number of
diverse image surveys, as well as the extension of hierarchical image systems
to cube and catalogue data. We demonstrate the interoperability of HiPS and
Multi-Order Coverage (MOC) maps and highlight the HiPS mechanism to provide
links to the original data. Results. Hierarchical progressive surveys have been
generated by various data centres and groups for ~200 data collections
including many wide area sky surveys, and archives of pointed observations.
These can be accessed and visualised in Aladin, Aladin Lite, and other
applications. HiPS provides a basis for further innovations in the use of
hierarchical data structures to facilitate the description and statistical
analysis of large astronomical data sets.
