Raw data are installed as DataLad datasets from https://github.com/gunnarvoet/piston-raw-mooring-data.
Processed data are saved to a DataLad parent dataset at https://github.com/gunnarvoet/piston-mooring-data that holds subdatasets for each instrument type (so far only ADCP data).
If you discover a bug or have a question about any of the data, please submit an issue.
This repository is a DataLad dataset. It provides fine-grained data access down to the level of individual files, and allows for tracking future updates. In order to use this repository for data retrieval, DataLad is required. It is a free and open source command line tool, available for all major operating systems, and builds up on Git and git-annex to allow sharing, synchronizing, and version controlling collections of large files. You can find information on how to install DataLad at handbook.datalad.org/en/latest/intro/installation.html.
A DataLad dataset can be cloned by running
datalad clone <url>
Once a dataset is cloned, it is a light-weight directory on your local machine. At this point, it contains only small metadata and information on the identity of the files in the dataset, but not actual content of the (sometimes large) data files.
After cloning a dataset, you can retrieve file contents by running
datalad get <path/to/directory/or/file>`
This command will trigger a download of the files, directories, or subdatasets you have specified.
DataLad datasets can contain other datasets, so called subdatasets.
If you clone the top-level dataset, subdatasets do not yet contain
metadata and information on the identity of files, but appear to be
empty directories. In order to retrieve file availability metadata in
subdatasets, use -n flag like so:
datalad get -n <path/to/subdataset>
Afterwards, you can browse the retrieved metadata to find out about
subdataset contents, and use datalad get once again (no flag this time) to retrieve individual files.
If you use datalad get <path/to/subdataset>, all contents of the
subdataset will be downloaded at once.
DataLad datasets can be updated. The command datalad update will
fetch updates and store them on a different branch (by default
remotes/origin/master). Running
datalad update --merge
will pull available updates and integrate them in one go.
DataLad datasets contain their history in the git log.
By running git log (or a tool that displays Git history) in the dataset or on
specific files, you can find out what has been done to the dataset or to individual files
by whom, and when.
More information on DataLad and how to use it can be found in the DataLad Handbook at handbook.datalad.org. The chapter "DataLad datasets" can help you to familiarize yourself with the concept of a dataset.