m+Medelevator.RU
← Поиск публикаций
Advances in colloid and interface science · 2026

The Interface Science Data Repository: A (meta)data framework and platform for FAIR data reporting in experimental fluid interface science.

СтатьяОбзорНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Bertsch Pascal, Chatzigiannakis Emmanouil, Fischer Peter, Hinderink Emma, Isa Lucio, Leser Martin, Maldonado-Valderrama Julia, Miller Reinhard, Murray Brent S, Robinson William E, Sagis Leonard, Vialetto Jacopo, Yang Jack, Malmsten Martin

Аннотация

Interface science, i.e., the study of adsorption, phase behavior and flow of matter at liquid interfaces, is a highly interdisciplinary research area that brings together researchers from fundamental theory to industrial production. FAIR - Findable, Accessible, Interoperable, Reusable - reporting of data and metadata is currently not common practice in interface science, although it could considerably promote the reuse of data across disciplines and foster translations to industry. For research fields with heterogeneous, non-standardized datasets such as interface science, community-driven agreement on relevant data, metadata, and reporting formats is an essential prerequisite before more advanced machine-operable infrastructures can be developed. We here propose a framework for relevant data and metadata for different interface science methods, surface-active species, and liquid subphases. We further introduce the Interface Science Data Repository (zenodo.org/communities/isdr) to provide a common platform for sharing interface science data. We discuss considerations for future machine-operable interface science databases and how standardized reporting can facilitate the development of data-driven modelling approaches, including machine learning. We hope that this work represents a first step towards establishing an active culture of FAIR data sharing in interface science while laying the groundwork for increasingly interoperable and automated data infrastructures.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты