Datasets selected for archiving should be accompanied by appropriate documentation and metadata, preferably also provided in digital format. As discussed in How to document your resources, the documentation which accompanies a dataset should enable a third party to make sense of the data. In addition to the documentation suggested in previously , a single set of general project-level information is also required. This is described in the general ‘Project Metadata’ section and specific examples of information that you may wish to include are provided below:

Element(s)	General Description	Examples / Suggestions
Description	History of the Originating Project	the purpose of the project topic(s) of research geographic and temporal limits other relevant information
Description	Information about Methods	methods used to create the data set methods used to georeference data consistency checks error corrections sampling strategies employed other relevant information
Relations	Details of source materials used to create the dataset	archives interrogated for desktop assessments maps used to georeference site grids or surveys previous excavations/evaluations of the site data selection or sampling procedures procedures for updating, combining, or enhancing source data description of any known copyrights held on source material
Relations	Details of how the dataset relates to other archives and publications	bibliographic references to any publications about the site or project information about any archives, museums, SMRs, NMRs, etc. which hold material related to the dataset information about any non-public material relating to the dataset
Format	Content and structure of dataset	list of filenames and description of contents type of computer on which data were created and manipulated description of identification numbers assigned list of codes used, and what they mean description of any known errors indications of any known areas of weakness details of derived variables or coverages data dictionaries, if available documentation of record conversion to new systems and formats description of the record-keeping system used to document the dataset names of primary project staff history of format changes to dataset history of how the dataset has been used other relevant information

Deposit formats

As noted at the start of this guide, copyright restrictions generally prevent the archiving of primary remotely sensed data. Where data can be freely archived and disseminated, the formats that are safest for digital preservation vary with the type of information contained within a file. As a result, recommendations are given here for the formatting of images, documentation, and metadata relating to digital resources based on aerial photographs or remotely sensed data. If aerial photography and remote sensing data is managed within a GIS environment, please refer to the GIS Guide to good practice

Image files

Image formats are commonly used to hold interpretations and rectifications of aerial photographs or remotely sensed images. While it may not be necessary to archive every single image created during the life of a project, a good archive will consist of final versions of those images important in the final analysis. The old adage often applies here: an image is worth a thousand words. Archiving a single image can often be worth more than a thousand words of documentation, but remember that if the image is to be really useful to others, it must be accompanied by background documentation explaining how and why it was created.

It is recommended that images are saved in uncompressed TIFF or PNG formats. Of these two recommended formats, PNG is preferable as this format retains information about the gamma values in images, but TIFF is currently a far more common image format for preservation. Other image formats may also be suitable and are discussed in detail in the Raster Images guide.

As also discussed in the images guide, many other formats may result in the loss of data contained within the original image, and these should be avoided as archival formats where possible. In some cases, datasets may also need to be compressed to assist in transferring information and large datasets with numerous component files are most easily handled in this way. There is always the risk of data loss, however, with data compression routines.