search

DHP-stottepakke / pages

https://dhp-stottepakke.github.io/pages/
Creative Commons Attribution 4.0 International
2 stars 9 forks source link

Mapping to cycle #4

Closed sveinho closed 5 months ago

sveinho commented 7 months ago

What topic do you wish to add? Defining research data cycle from beginning to end, defining some stages and/ or subprocesses

Are there existing pages in the website related to the requested page? Suggest this as a "hidden page" for internal use, meaning for project and support staff

Resources We can choose among many existing cycle descriptions

Context The context is the project, for possible shared thoughts on the linkage between questions in dmp and part in cycle

jennyostrop commented 6 months ago

@sveinho Which data life cycle models do you think should be covered?

The minimalistic phases that we discussed: planning, active phase, publishing

Life cycle that is used e.g. in the RDMkit, which is close to the DMP pilot: https://rdmkit.elixir-europe.org/data_life_cycle

CESSDA has slightly other stages: https://dmeg.cessda.eu/Data-Management-Expert-Guide

ALLEA starts with "identifying data": https://repository.dri.ie/catalog/tq582c863

LLongva commented 6 months ago

Jeg liker nok best RDMkit-modellen. Den er velkjent, og jeg synes den har den mest logiske gangen. ALLEA-modellen introduserer en 'identify'-fase før planlegging. Kanskje det er et poeng i humaniora, å identifisere hva som er datagrunnlaget, før man går til planlegging. Men jeg mener det er mest logisk at denne identifiseringen er en del av planleggingen. CESSDA-modellen er rar i og med at 'collecting/generating data' mangler. Men dette er inkludert i 'Organise & Document', etter det jeg kan se. Men altså: jeg holder en knapp på RDMkit-modellen.

sveinho commented 6 months ago

Hvis vi sammenligner RDM-kit syklus mot DSW KM (i parentes), så forstår jeg det som om en mapping mellom syklus og DSW KM blir omtrent slik:

Plan (includes admin aspects, possibly also discovery of existing data) Collect (includes possibly also re-using data, as well as creating and collecting data) Process (includes to some degree the planning of storage to be used) Analyse (similarities to interpreting data in DSW) Preserve (includes also the process of archiving in DSW) Share (similar to the wording publishing metadata and/or data, similar also to giving access to data)