In this article, we focus on the importance of open research information as the foundation for transparent and responsible research assessment and discovery of research outputs. We introduce work in which we support the open research information commons by enabling, in particular, independent and small Open Access journals to provide metadata to several open data hubs (Open Citations, Wikidata, Open Research Knowledge Graph). In this context, we present The OPTIMETA Way, a means to integrate metadata collection, enrichment, and distribution in an effective and quality-ensured way that enables uptake even amongst small scholar-led publication venues. We have designed an implementation strategy for this approach in the form of two plugins for the most widely used journal publishing software, Open Journal Systems (OJS). These plugins collect, enrich, and automatically deliver citation metadata and spatio-temporal metadata for articles. Our contribution to research assessment and discovery with linked open bibliographic data is threefold. First, we enlarge the open research information data pool by advocating for the collection of enriched, user-validated metadata at the time of publication through open APIs. Second, we integrate data platforms and journals currently not included in the standard scientometric practices because of their language or lack of support from big publishing houses. Third, we allow new use cases based on location and temporal metadata that go beyond commonly used discovery features, specifically, the assessment of research activities using spatial coverage and new transdisciplinary connections between research outputs.
翻译:在文章中,我们强调开放研究信息作为透明和负责的研究评估和发现研究成果的基础的重要性。我们介绍了一项工作,通过使独立和小型的开放存取杂志能够向几个开放数据中心(公开引用、维基数据、开放研究知识图表)提供元数据,支持开放研究信息共同点。在这方面,我们介绍了“开放研究信息”方法,这是将元数据的收集、浓缩和发布以有效、有质量保证的方式整合起来的一种方法,即使能在小型学术主导的空间型出版场所中吸收。我们为这一方法设计了一个实施战略,其形式是两个插件,用于最广泛使用的期刊出版软件《开放日报系统》。这些插件收集、丰富和自动提供引用元数据和空洞时时时时数据。我们介绍了“开放研究知识图”方法,这是将元数据收集、浓缩和发布以有效、有质量保证的方式进行传播的一种方法。我们为这一方法设计了一个实施战略,其形式是两个插件,用于最常用的期刊出版软件《开放日志》系统(OJours Systems),用以收集、丰富、经用户验证的元数据平台和期刊目前没有列入用于标准检索的常规检索中的数据,因为我们缺少了使用的标准检索中的新研究案例。