Utility-University Collaboration Publication Data

This dataset is a collection of metadata describing the authors, their organizational affiliations, and locations associated with academic publications that result from collaborations between academic researchers and electric utilities. It is queried from the Scopus database by searching for publications where at least one author is affiliated with one of the 20 largest U.S. electric utilities.

We used this data set to better understand the nature of and factors in utility-university collaboration formation. In addition to understanding the role geography/proximity plays, we also conducted limited network analysis to identify high frequency collaborators at both the author and organizational scale. We identified some time series trends such as increasing numbers of publications and increasing distances between collaborators over time, but we did not determine their significance by controlling for external factors like funding, regulation, and technological changes. Future work could use the included classifications for each publication to understand the changing mix of research topics over time.

The interviews we conducted for the accompanying research suggest that several types of collaborations are not represented in the publication dataset, including unsuccessful collaborations, many types of student-driven practicum-style work, and for-hire work that may assist in regulatory filings, internal documents, or other non-academic publications.

We include four separate versions of this dataset at different stages of its refinement to better enable any reproductions, expansions or refinements of the dataset.

The first file (Initial Publication Queries By Utility.zip) is our raw output from the Scopus queries.

The second file (Author-Parsed Publication Queries By Utilities.zip) is the parsed output of the queries, where each author and affiliation are separated.

The third file (Publication Dataset with Duplicates and Erroneous Entries.csv) combines all utilities into a single file and includes many manual corrections to parsed or missing information, as well as some additional fields to classify data and identify duplicates and records erroneously included.

The fourth file (Final Utility-University Publication Dataset.csv) then removes some of those additional fields as well as all duplicates and erroneously included records. This was the file we used for our final analyses.

本数据集汇集了描述作者、其所属组织及与学术出版物相关联的地理位置的元数据，这些出版物源自学术研究人员与电力公用事业公司的合作。该数据集通过在Scopus数据库中搜索至少有一位作者隶属于美国20家最大电力公用事业公司之一的出版物进行查询。利用此数据集，我们旨在更深入地理解电力公司与大学合作形成的本质及其影响因素。除了探究地理/邻近性所扮演的角色外，我们还进行了有限的网络分析，以识别在作者和组织层面的高频合作者。我们识别出一些时间序列趋势，例如出版物数量的增加以及合作者之间距离随时间增长，但未通过控制外部因素如资金、监管和技术变革来确定其重要性。未来的研究可以利用所包含的出版物分类来理解随着时间的推移研究主题的混合变化。我们对伴随研究进行的访谈表明，该出版物数据集中未体现多种类型的合作，包括失败的协作、众多由学生驱动的实践型工作，以及可能协助监管文件、内部文件或其他非学术出版物的工作。我们提供了数据集的四个不同版本的独立版本，以不同阶段的精炼程度，旨在更好地促进任何数据集的重现、扩展或改进。第一个文件（Initial Publication Queries By Utility.zip）是我们从Scopus查询中得到的原始输出。第二个文件（Author-Parsed Publication Queries By Utilities.zip）是查询的解析输出，其中每个作者和所属单位都被单独列出。第三个文件（Publication Dataset with Duplicates and Erroneous Entries.csv）将所有公用事业公司合并到一个文件中，并包含对解析或缺失信息的许多手动修正，以及一些额外的字段以分类数据、识别重复项和错误包含的记录。第四个文件（Final Utility-University Publication Dataset.csv）随后移除了部分附加字段以及所有重复项和错误包含的记录。这是我们用于最终分析使用的文件。