Many departments and research groups have their own curation checklists which provide guidance on how to complete the metadata for your data submission. These guidelines use the practices within that particular field to ensure that your publication is more FAIR. See a sample one below
ZivaHub | Open Data UCT Curation checklist for: Marine Resource Assessment and Management group (MARAM)
Top 10 FAIR Data & Software Things: Oceanography. https://librarycarpentry.org/Top-10-FAIR//2019/01/18/oceanography/
Top 10 FAIR Data & Software Things: Biodiversity. https://librarycarpentry.org/Top-10-FAIR//2018/12/01/biodiversity/
Title:Example: Summary of 2020 updated West Coast rock lobster stock assessments
Do not exceed 100 characters
Do not put full stops at the end of titles
First author; Second author; Co-Supervisor; Supervisor/Lab Leader (poss. other contributors)
All contributing team members are authors.
Pro tip: Paste the (UCT) email address of the author to disambiguate multiple identities.
Pre-2020 items: some authors/co-authors are retired or no longer in the field - where possible, a current working email address will be given; otherwise their email address at the time (i.e. not necessarily working) of the publication will be given, else no email address will be given (this is the last resort - see c. above).
Marine Resource Assessment and Management group (MARAM)
In most cases, this will be auto-selected based on the type of files uploaded. Only in rare cases will you need to change it from the automatic selection to a new one.
Several new item types have been added to ZivaHub. Of specific interest may be the type “Report”. If this item type is assigned to the Honours Project Reports published on ZivaHub, in place of “Online Resource”, these items should be more findable. The biggest advantage of using “Report” is that items of this type are automatically indexed by Google Scholar.
Single items shouldn’t have more than 10 keywords chosen from the list below. At least three keywords are required. It is recommended that a keyword related to the method, the data and context be included e.g.Hydroacoustic survey, fisheries. Some common keywords could include:
Pg 5 onwards has a table with a list of all the stocks and their regions that MARAM has worked with on our website - from here a list of keywords will be found
MARAM - should always be a keyword
Fisheries resource assessment
Fisheries resource management
Other jargon: Operational Management Procedures (OMP); Total Allowable Catch (TAC); Total Allowable Bycatch (TAB); …
Post-2020 items: I’ll ask the MARAMers to be specific with their keywords, though they will not always remember and the keywords they choose reflect what they think is important for their paper:
Species in the region assessed;
Method used (SCAA, GLM, SCAL, GLMM, multi-species models)
Data used (may not always be applicable);
Assessment e.g. OMP-18rev, OMP-17, MP etc -> only where applicable; …
Assessment output e.g. TAC, TAB, projections, comparison, etc.
Pre-2020 items: will try to stick to above points, but it may not always be applicable, especially going further back historically.
Have done a search using these keywords on figshare.com?
What kind of results are you getting? Are they relevant?
Are you satisfied that the use of your keywords will meaningfully connect this new item with other relevant items on figshare.com?
How best do the people from CCAMLR, IWC, find these items? (Method: “break down” the Googling of the title of the paper into specific, ‘unique’ search terms).
Suggested help pages:
How to do library research: Develop Keywords
This is the data from <title of project> (year). It is an abstract.
Write a brief description of what the dataset contains.
Description could include:
Paper or thesis abstract
Description of the dataset such as:
Explanation of csv files containing the data
Clarification on coding used for analysis of data
Period of data collection
Location of data collection
Reports/Standards - the description may only be one line (e.g. this report details how the TAC for sardine is calculated using OMP-18rev)
We won’t detail where the data comes from because the data may come from other sources/papers or from ‘old’ surveys - it goes too far back to merit its inclusion.
In most cases, the abstracts/descriptions of these items will be one-liners - please expect this (if it is an actual description, then you are just very lucky ;)
Presentations will not include any detailed description - just where it took place
I’ll ask the team to include a brief one-liner on where their data comes from.
The team knows they must include an abstract/description and keywords with their presentation - it is sent back to them to have this information included.
Abstracts/descriptions are in most cases relevant to the organisation is applies to (e.g. IWC, DFFE, ICCAT) - it meets those organisations’ requirements so is unlikely to change
Grant number (NB: NRF grantees!)
Insert a link to the thesis/dissertation/journal article
AND/OR links to external databases from which the data was collected
AND/OR links to where performances were hosted, e.g. YouTube
AND/OR links to where presentations were hosted, e.g. conference website, Slideshare
AND/OR links to departmental websites, project websites, etc.
CC BY 4.0 (unless there is a specific reason to choose otherwise)
Department of Mathematics and Applied Mathematics, University of Cape Town