1,721,052 research outputs found

    Policies and Infrastructures for Innovation and Impact in Open Science. An interview with Paolo Manghi

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    In this interview Paolo Manghi discusses how policymaking, e-infrastructures and funding mechanisms are trying to bring into everyday routine the difficult shift of mindset towards Open Science: a scenario of publishing service systems that supports communities with methodologies to produce concrete, testable and reusable scientific results

    Types for path correctness of XML queries

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    If a subexpression in a query will never contribute data to the query answer, this should be regarded as an error. This principle has been recently accepted into mainstream XML query languages, but was still waiting for a complete treatment. We provide here a precise definition for this class of errors, and define a type system that is sound and complete, in its search for such errors, for a core language, under mild restrictions on the use of recursion in type definitions. In the process, we describe a dichotomy among existential and universal type systems, which is useful to understand some unusual features of our type system

    Tracing Data Footprints: Formal and Informal Data Citations in the Scientific Literature

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    Data citation has become a prevalent practice within the scientific community, serving the purpose of facilitating data discovery, reproducibility, and credit attribution. Consequently, data has gained significant importance in the scholarly process. Despite its growing prominence, data citation is still at an early stage, with considerable variations in practices observed across scientific domains. Such diversity hampers the ability to consistently analyze, detect, and quantify data citations. We focus on the European Marine Science (MES) community to examine how data is cited in this specific context. We identify four types of data citations: formal, informal, complete, and incomplete. By analyzing the usage of these diverse data citation modalities, we investigate their impact on the widespread adoption of data citation practices

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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