# Sciebo RDS - reducing friction of FAIR data handling for researchers

- Institution: CERN
- Department: HEP Computing
- Taught by: Richard Freitag, Juri Hößelbarth
- Year: 2023
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3016403)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Research Data Services (RDS) is a self-hosted cross-platform interoperability layer which allows research data to be curated, prepared and published directly from an EFSS solution such as Sciebo (ownCloud) or Sunet Drive (Nextcloud). It provides modular interoperability to external data repositories like the Open Science Framework (OSF), InvenioRDM (e.g., Zenodo), Harvard Dataverse, or Doris from the Swedish National Dataservice, each including domain-specific customizations.

Publishing data sets, corresponding metadata and persisting the information with a digital object identifier (DOI) is not only increasingly required by project funding entities such as the European Union or scientific journals, but also positively contributes to researchers' credibility and visibility. However, publishing research data requires often requires a specific data repository. This challenge is addressed by using Sciebo Research Data Services (RDS) as an interface between the enterprise file sync and share solution (EFSS) and the data repository. While research object crates (RO-Crate) are used as an intermediate lightweight package for the data and respective metadata, individual connector microservices ensure compliance with each publication service and easily developed support for additional data repositories. Metadata is added through Describo and based on schema.org annotations in JSON-LD and aims to make best-practice in formal metadata description accessible and practical for use in a wider variety of situations, from an individual researcher working with a folder of data, to large data-intensive computational research environments.

An integral part of the research data lifecycle process is the publication of research data, either by itself or as part of the supplementary information (SI) of a published article. Contributing to the Open Science movement, research data should be FAIR: findable, accessible, interoperable, and reusable. However, not only researchers' fears…

## Lectures

1. [Sciebo RDS - reducing friction of FAIR data handling for researchers](https://invisiblenetwork.ai/learn/cern/3016403/71b18668c211), 16 min (CERN's player)