
The Open Insight Sessions series is designed to deepen community engagement with the Irish Monitor, strengthen institutional adoption, and gather valuable user feedback. Across five monthly sessions, we’ll review achievements, address data quality, explore collaborative potential, and create opportunities for institutions to share their experiences. These sessions aim to build a robust, sustainable foundation for the Monitor. Each session begins with a short webinar (20-minute presentation and 10-minute Q&A), followed by a 30-minute interactive segment where attendees can participate in hands-on activities and discussions. Presentations and recordings from each session will be posted on Zenodo and subsequently shared on the Irish Monitor engagement and training page (https://oamonitor.ireland.openaire.eu/engagement-training). Session's theme: Data Quality & Text Mining The session includes: Presentation on data quality practices in the Monitor, recent updates, and the role of AI and text mining in enhancing Monitor insights Q&A with the data quality team, covering data consistency, deduplication, and text mining applications Date: 23 January 2025 OpenAIRE experts who presented:Ioanna Grypari, Technical Project ManagerClaudio Atzori, Lead Data EngineerHarry Dimitropoulos, Text Mining Lead and Funders Expert Recording: https://youtu.be/KFQm5mfS3MI
OpenAIRE, open access, data quality practices, text mining
OpenAIRE, open access, data quality practices, text mining
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
