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  • Queries to identify climate change research that takes an engineering approach
    This dataset was created as part of work conducted for the NSF Engineering Research Visioning Alliance's inaugural Visioning Event, entitled "The Role of Engineering in Addressing Climate Change". The dataset is composed of four text (.txt) files, each containing a single query used to identify research relevant to climate change; and three comma-separated values (.csv) files including information about how engineering research was defined.The goal of this work was to conduct bibliometric analyses aimed at better understanding the role engineering plays in climate change research. To do so, the set of documents returned from the climate change queries was crossed with the set of documents returned from the engineering query. Files 01 through 04 each contain a single Scopus query that aims to capture either general climate change research (01) or specific topics of interest within climate change research (02-04). These are queries that could be run using the scopus.com advanced document search feature. Given engineering is a broad field, keyword-based queries were not an efficient way to capture all relevant articles. Instead, three complementary classification schemes were used to capture this research. The following files summarize which parts of the classification schemes were mostly engineering-focused. An effort was made to keep this publication set maximally inclusive, such that it also includes some wider applied research subfields. File 05a contains the All Science Journal Classification (ASJC) classes that were identified as being engineering for the purpose of this project. The ASJC is a journal-level classification, which means that all articles from a given journal are classified in the same subject area(s). A complete list of ASJC codes can be found here. File 05b refers to Science-Metrix (SM) subfields identified as being engineering. The SM classification is also made at the journal-level, but articles from multidisciplinary journals such as Science or Nature are reclassified at the article level by a machine learning model (Read the article here), allowing us to capture more articles than using ASJC alone. File 05c refers to the SciVal Topics that were included in the engineering publication set. Topics are collections of documents that share a common intellectual interest, as identified through their direct citation patterns. For a high-level description of SciVal Topics, see this page. A detailed description of the methodology used to create Topics is also available in this article.
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  • Research Futures 2.0 - survey of researchers
    Two studies completed since the original project in 2018 to provide an evolving view: 1. 2020 a survey of 1,066 researchers. Fieldwork July 2021. 2. 2021 a survey of 1,173 researchers. Fieldwork August 2021. Methodology was random sample of researchers (unbranded) for both waves. Many questions were asked in both studies to provide comparative data to show change over time. Survey tool: Online survey available in English only.
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  • Regular data
    Regular dataset.
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