For many years, economics researchers have discussed the importance of sharing code and data files to ensure replicability. The discussion, however, rarely includes questions about long-term access to those files. This paper looks in-depth at the code and data policies from top economics journals to understand the guidance provided to researchers regarding data sharing and asks if that guidance supports preservation of code and data files for access and use, long into the future. We used content analysis to review journal policies from 184 economics journals. We discovered that while most journals recommend code and data be released with papers and that a few journals recommend practices consistent with long-term preservation, almost no journals specifically or emphatically consider long-term preservation of those files.The data replication file is anticipated to be available in December 2021.

Copy and paste citation tools exist for traditional academic publication types from places like Citation Machine or Google Scholar, but similar plugins for datasets are scarce. In response, the Federal Reserve Bank of Kansas City built a data citation template for all acquired and select open data sources to allow economists to copy and paste data citations into their preferred word processing program.

Originally presented to the 2017 DLF Forum, Pittsburgh, PA.Recommended citation: Currier, B. D., Kim, B., Edwards, C., & Butler, C. R. (2017). Research Data Preservation Beyond Data Sharing and Open Science. Presentation to the 2017 DLF Forum, Pittsburgh, PA. Accessed through LIS Scholarship Archive. Available at http://doi.org/10.17605/OSF.IO/A8HM2 Research data preservation has often been discussed as part of data sharing and open science. However, research often involves data with restrictions, and regardless of sharing, preservation is a crucial process for research integrity. This presentation walks through questions for thinking about legal issues in data.

Originally presented to the 2017 Annual International Association for Social Science Information Services & Technology (IASSIST) Conference, Lawrence, KS.Recommended citation: Butler, C. R. & Currier, B. D. (2017). Creating Data Citations in LaTeX for Economists. Poster presented to the 2017 Annual International Association for Social Science Information Services & Technology (IASSIST) Conference, Lawrence, KS. Accessed through LIS Scholarship Archive. Available at http://doi.org/10.17605/OSF.IO/P64BRThe Federal Reserve Bank of Kansas City built a LaTeX file for acquired data so economists could copy and paste the data citations into their preferred word processing program, which is LaTeX. Copy and paste citations exist for traditional academic articles and books from places like Citation Machine or Google Scholar, which provides researchers with the code they need for various citation styles and word processing programs, including LaTeX. We could not identify a similar plugin for datasets. We reviewed all active contracts and open data sources for publication permissions, restrictions or limitations, post-termination rights, and specific data citation guidelines. Information was then compiled and made available on a private intranet site to avoid violation of non-disclosure agreements. Citation information was translated into LaTeX scripting in Modified Chicago Style when specific citation requirements were not indicated by the Licensor. This poster will explain that process, provide a template for data citations and their LaTeX scripting, and a LaTeX file for publicly available data.

We report here the complete genome sequences of four subcluster L3 mycobacteriophages newly isolated from soil samples, using Mycobacterium smegmatis mc2155 as the host. Comparative genomic analyses with four previously described subcluster L3 phages reveal strong nucleotide similarity and gene conservation, with several large insertions/deletions near their right genome ends.