In order to deposit the data, researchers will develop a Data Management Plan (DMP) and choose the repository to upload the dataset. Researchers have a significant amount of guidelines for the elaboration of a research DMP.
Most calls for project funding require the preparation of a DMP from the outset. A DMP is a "living" document (in the sense that it can be changed or reviewed during his “live”) that describes how the data are collected or generated during and after the research project. A DMP might describe:
The DMP is not a static document (in the sense that it's not unchangeable), but evolves and acquires more precision and content during the development of the investigation. The first version of the DMP should be completed during the first months of the project. Then, it should be updated at least halfway and at the end of the project. The researcher has to adjust it to the data generated and the uses identified by the project research group.
Remember that::
In this section we provide you with several documents to help you in the elaboration of the DMPs.
An open access repository stores and provides free access to a digital collection of research outputs. A repository can provide a persistent identifier that makes it easier to find publications. Many data repositories also accept publications and allow linking between publications and their underlying data.
If no thematic or institutional repository is available, researchers can use the Zenodo repository, provided by the European Commission and hosted by CERN.
There are also data harvesters. These are systems that make metadata searchable, but instead of hosting the data itself, they point to the repositories where it is stored.
Surgió de la iniciativa de un grupo de importantes revistas y sociedades científicas de adoptar una política conjunta de archivo de datos para sus publicaciones y del reconocimiento de que era necesaria una infraestructura de datos abierta, fácil de usar, sin ánimo de lucro y gestionada por la propia comunidad.
Inicialmente fue un desarrollo de Macmillan Publishers de 2011.
Cada colección individual de Dataverse es una colección personalizable de conjuntos de datos para organizar, gestionar y mostrar conjuntos de datos.Al publicar los datos se obtiene una cita de datos estándar con un Identificador de Objetos Digitales (DOI) y los metadatos estarán abiertos y se podrán encontrar a través de los motores de búsqueda, incluso cuando los datos estén restringidos.