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We present a draft Minimum Information About Geospatial Information System (MIAGIS) standard for facilitating public deposition of geospatial information system (GIS) datasets that follows the FAIR (Findable, Accessible, Interoperable and Reusable) principles. The draft MIAGIS standard includes a deposition directory structure and a minimum javascript object notation (JSON) metadata formatted file that is designed to capture critical metadata describing GIS layers and maps as well as their sources of data and methods of generation. The associated miagis Python package facilitates the creation of this MIAGIS metadata file and directly supports metadata extraction from both Esri JSON and GEOJSON GIS data formats plus options for extraction from user-specified JSON formats. We also demonstrate their use in crafting two example depositions of ArcGIS generated maps. We hope this draft MIAGIS standard along with the supporting miagis Python package will assist in establishing a GIS standards group that will develop the draft into a full standard for the wider GIS community as well as a future public repository for GIS datasets.

 

Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation to drinking water systems. As datasets of PFAS drinking water sampling continue to grow as part of evolving regulatory requirements, we used this Kentucky dataset as an example to promote the reuse of this dataset and others like it. We incorporated the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by creating a Figshare item that includes all data and associated metadata with these five ArcGIS maps.

 

In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it’s important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub ( https://moseleybioinformaticslab.github.io/academic_tracker/ ) and is also available on the Python Package Index ( https://pypi.org/project/academic_tracker ) for easy installation. 

Recent sea surface height (SSH) trends in the South Pacific are substantially greater than trends in the North Pacific. Here, we use the Estimating the Climate and Circulation of the Ocean Version 4 Release 4 ocean state estimate and the Ocean Reanalysis System 5 to identify the forcing and mechanisms underlying that meridional asymmetry during 2005–2015. Thermosteric contributions dominate the spatial structure in Pacific SSH trends, but contributions from local surface heat fluxes are small. Wind stress trends drive a spin‐up of the South Pacific subtropical gyre and a northward shift of the North Pacific subtropical gyre. A reduced gravity model forced with reanalysis winds qualitatively reproduces the meridional seesaw in sea level, suggesting that asymmetric trends in subtropical wind stress drive a cross‐equatorial heat transport. A reversal in forcing associated with this process could impact near‐term rates of coastal sea‐level change, particularly in Pacific Island communities.