FAIRCORE4EOSC Deliverable D1.5 Strategic Alignment and Contribution to the EOSC Partnership
Notice bibliographique
Résumé
The FAIRCORE4EOSC is a European Open Science Cloud (EOSC) project, funded from Horizon Europe programme, that is tasked to develop nine new EOSC-Core services to support a FAIR EOSC as well as to enhance interoperability and discoverability of an increased amount of research outputs. The services are developed by leveraging existing technologies and services. Furthermore, the project has ensured the user centricity of the component development by identifying case studies, represented by partners coming from different scientific communities. The case studies are early adopters of the services within these communities. The purpose of this report is to present the strategic alignment activities carried out during the FAIRCORE4EOSC project and to outline the contribution to the EOSC partnership that the project has built during the project and that continues to produce impact after the project. This report is also aimed to outline the lessons that the project has learned by conducting the alignment activities during the project. Strategic alignment can take different forms, and the level of engagement in alignment activities can vary. Different forms of activities can be defined at the project planning phase, or maybe alignment can be identified only at the project implementation phase, in more or less formalized forms. A classification for planning alignment activities is discussed in the introduction of this report. Some of the planned activities turned out to be as useful, some even more useful than foreseen. Some planned actions turned out to be of low relevance. There were also unforeseen collaborations that proved to be highly synergistic. The level of engagement in alignment activities can depend on resources allocated for such activities, and the maturity of the project outputs. First, it is crucial for projects to share knowledge on different developments, and to find synergies so that the work does not take place in silos. Sharing information may prevent misalignment of efforts between actors and prevent duplication of work. Second, raising awareness for project outputs helps to ensure the developed services match the needs of users through engaging identified actors in requirement elicitation and validation of developed features. Third, both broad and targeted dissemination help in finding interested users and increasing adoption of the developed services. These three things are major facets in creating the projects impact. However, sometimes expectations for alignment activities are simply too high and the alignment does not take place at an expected level. Reasons for this may be for example that the services developed in FAIRCORE4EOSC are mostly mature enough for adoption only in the end of the project. Expectation management plays a relevant role here. We have classified the alignment activities into groups by target actor type: EOSC partnership, INFRAEOSC projects, strategic communities, and other stakeholders. The alignment activities are be outlined in this report alongside the challenges that the project has overcome to improve the sustainability of the project contributions in the EOSC partnership. The overall rationale for alignment has been to maximise the impact of the services developed for the past three years to make them relevant to research communities.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,015 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,012 | 0,006 |
| Science ouverte | 0,003 | 0,013 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,108 | 0,052 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».