Notice bibliographique
Résumé
While digital technologies have revolutionized how we collect and visually represent data, humans continue the thousand-year tradition of producing physical representations of data. Physical representations of data can range from the mundane (hourglass egg timers in an everyday kitchen) to the spectacular (large-scale data sculptures in a museum). Physical representations of data are experiencing a dramatic renaissance, driven by new fabrication technologies, materials, and processes as well as a growing enthusiasm for all things data.The artists, designers, and scientists who create physical representations of data draw from a range of domains and traditions, and represent a fascinating, inspiring, and revealing cross-section of contemporary maker and data culture. To highlight the diversity of approaches, we are currently curating a collection of first-hand accounts from 25+ artists, designers, and researchers that document the process of designing and creating new physical representations and experiences with data. Each story describes the creators’ motivation and inspiration, their approaches for sourcing and encoding data, and their experience navigating the design and fabrication process. In our talk, we will present five themes that capture how people are “making with data” today: Data craft highlights artists and designers whose hand-crafted pieces manually (and sometimes painstakingly) integrate data into objects – from the extraordinaryexotic and bespoke to the personal and everyday. Digital production examines how digital fabrication techniques like 3D printing and digital milling can produce unique and expressive data-driven physical forms. Data automation introduces new physical platforms that use automation and robotics to dynamically and interactively encode data physically. Participatory showcases ways in which designers invite viewers into the creation process, allowing them to encode or reveal data through their interactions with a piece, material, or other people. Environmental projects, meanwhile, reveal data in the context of our surroundingsnatural environments, often exploring the use of natural processes to create new and compelling representations.Each of these approaches entails profound design choices and considerations which impact the design and production process, the tools and skills required to create the works, and ultimately the connection that is created between the creator, the viewer, and the dataIn this lighting talk, we will present highlights from our rich and exciting set of art pieces, projects, and installations. We will illustrate each theme with a case study featuring a particularly compelling work, and also provide our own first-hand reflections on creating and experiencing physical representations of data. Finally, we will turn the discussion back to the broader community, examining additional approaches not captured by our themes, and highlighting aspects of the creation process that are of particular interest to the information plus audience.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».