Data management is a large topic and there are many excellent resources available on the internet. This page aims to provide links to information specific to the HMTF programme through to general information on best practices in research data management.
As a programme, NERC require that we document our datasets (metadata) to a standard that would allow a future researcher to be able to understand or potentially duplicate the dataset. Comprehensive documentation of datasets is good scientific research practice and will ensure that datasets archived to NERC computer centres (or other appropriate repositories e.g. ForestPlots) can contribute to future research. Part of the documentation process is also ensuring that anyone re-using an archived datasets correctly references the original researchers.
If you have any queries about specific or general data management issues, please contact the HMTF Data Manager (firstname.lastname@example.org).
Metadata – describing your datasets
Metadata is data that describes other data. The EIDC and NERC require metadata that conforms to the UK GEMINI standard for spatial data.
NERC requires discovery metadata – the essential information that enables the potential user of data to find out if a particular resource exists, its location, ownership and whether it meets their requirements.
HMTF data management resources
All researchers have been sent an Excel spreadsheet template to fill in and return to the data manager (email@example.com) that gives basic details about the datasets they will be creating e.g. name, description, file type, likely final size, date dataset likely to be complete.
NERC metadata guidelines
General good practice guidance
Searches on metadata portals and search engines to which the metadata is exposed can result in a large number of results; the metadata should therefore be sufficiently clear and comprehensible to enable the reader to understand the nature of the entry and to assess whether it is suitable for reuse. Poor quality metadata can mean that a resource is effectively hidden from users and remains unused.
When writing good quality metadata, always keep in mind the ABCD of good discovery metadata. Metadata should be:
Accurate – correctly and precisely describe the resource in question
Beneficial – contains information that is useful to the end user without lots of extraneous, irrelevant information
Clear – easily understandable by a non-technical user and unambiguous
Distinctive – contains information that allows it to be distinguished from other, potentially similar, resources
The following metadata fields will be needed. Guidance on each field is given here which should be read in conjunction with this document.
Spatial extent: (bounding box)
Temporal extent: (dates from / to):
Spatial Reference system: e.g. British National Grid, WGS
Spatial representation type: e.g. raster, vector
Spatial resolution (For gridded data, this is the area of the ground (in metres) represented in each pixel. For point data, the ground sample distance is the degree of confidence in the point’s location e.g. for a point expressed as a six-figure grid reference, SN666781, the resolution would be 100m)
Author name: (Bloggs, J.J.)
Where appropriate, all datasets should also have detailed metadata on aspects such as experimental design, sampling, fieldwork or laboratory instrumentation, analytical methods; any information that would be necessary for a researcher not involved in the project to understand and/or re-use the dataset. Further guidance is available