The ever-growing availability of research artefacts of potential interest for users calls for helpers to assist their discovery. Artefacts of interest vary for the typology, eg papers, datasets, software. User interests are multifaceted and evolving. This paper analyses and classifies studies on recommender systems exploited to suggest research artefacts to researchers regarding the type of algorithm, users and their representations, item typologies and their representation, and evaluation methods used to assess the effectiveness of the recommendations. This study found that most of the current scientific artefacts recommender system focused only on recommending paper to individual researchers, just a few papers focused on dataset recommendation and software recommender system is unprecedented.

Virtual Research Environments, Science Gateways and Virtual Laboratories are systems aiming at serving the needs of their designated communities of practice by providing them with a working environment for performing their tasks. These systems have been proposed and exploited in diverse application domains and scopes ranging from education to simulation, collaboration, and open science. This paper analyses the literature published from 2010 to start characterising this manifold family of systems. In particular, the study identified and analysed a corpus of 1167 research papers to highlight their distribution over time, the most frequent publication venues and the characterising topics.