Supporting awareness in heterogeneous collaboration environments
Notice bibliographique
Résumé
Rapid technological advancements have made it possible for humans to collaborate as never before. However demands of group work necessitate distributed collaboration in very heterogeneous environments. Heterogeneity as in various applications, platforms, hardware and communication infrastructure. User mobility, lack of availability and cost often make imposing a common collaboration environment infeasible. Awareness is essential for successful collaboration. Awareness is a key design criterion in groupware but often collaboration occurs with applications not designed to support useful awareness. This dissertation deals with the issue of effective group awareness support in heterogeneous environments.;Awareness propagation is effective if the appropriate amount of information, relevant to the user's sphere of activity is delivered in a timely, unobtrusive fashion. Thus issues such as information overload, and distraction have to be addressed. Furthermore ability to establish the appropriate balance between awareness and privacy is essential. Enhanced forms of awareness such as intersubjectivity and historical awareness are often invaluable. Heterogeneous environments significantly impact the above quality factors impeding effective awareness propagation. Users are unable to tailor the quality of awareness received.;Heterogeneity issues that affect awareness quality are identified. An awareness framework is proposed that binds various sources of awareness information. However for effective awareness support, physical integration must be augmented by information integration. As a solution, an awareness model is proposed. Specification of the awareness model and framework's architecture and features is the key contribution. The proposed model has been validated through simulations of realistic collaboration involving human participation. Scenarios created, have tested the model's usefulness in enhancing the quality of group work by propagating effective awareness among users. To accomplish the same, an Awareness Simulator application has been created. In the validation process, efforts made to create an experimental methodology revealed some techniques related to awareness evaluation in CSCW, which are proposed. Various issues required to successfully engineer such awareness frameworks are identified and their impact on requirements such as security and performance, discussed. With various standards and technologies that can be harnessed to create awareness frameworks, there is great promise that barriers in heterogeneous collaboration environments can be overcome.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,002 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».