Data publishing repositories

Choosing the repository

There are a number of data repositories available, and the best one for you depends on your goals, needs and data. Some things to consider:

• Persistent identifier: Does the repository provide a DOI or some other identifier?
• Long-term availability of your data: Is the repository managed by a company, society, institution or government?
• Impact and visibility: From which repository would the potential reusers best find your dataset?
• Support for certain metadata, file format or data presentation features. Some discipline-specific repositories have useful features that add value and reuse potential to your data.

Recommended data repositories

We recommend using a reliable discipline-specific repository to maximize the impact of your dataset. If a suitable discipline-specific repository is not available, we recommend Zenodo as a general purpose data repository.

Discipline-specific data repositories

Consider submitting your data to discipline-specific, community-recognised repositories when possible. To find a data repository, you can start with these services:

• List of data repositories categorized by disciplines, from the University of Chigago Library
• List of recommended data repositories by the data journal Scientific data
• Search the re3data registry of research data repositories directly or with the Repository Finder by DataCite
• List of data repositories in Open Access Directory

Key features of general purpose repositories

Scientific data journals

The key issue in scientific data journals is that the articles do not include analysis of data, but the journals provide a forum to describe and document research data sets. For the researchers that have a specific interest to produce or create data, the data journals may be a relevant publishing channel.  

Examples on general or multidisciplinary data journals

Data in Brief by Elsevier:

• Promotes external, public repositories and recommends interlinking the data and the article.
• Elsevier recommends to publish a data article via the journal, even in cases where the article has been published in another Elsevier journal.
• Enables authors “enrich online article by uploading relevant computer code and data to the RunMyCode repository … “.

Scientific Data by Nature:

• Publish descriptions of data from new or published studies; in latter case dataset must provide new content.
• Covers a broad range of natural science disciplines and will consider descriptions of quantitative datasets from the social sciences, too.

Record description of your dataset to ACRIS, our local catalog

ACRIS (Aalto Current Research Information System) is Aalto's research information management system - the home for Aalto's research information. It is important that you insert the description of your dataset in ACRIS, since universities are judged based on data produced and openness. The instructions for adding dataset description to ACRIS are attached below.