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Current estimates of U.S. property at risk of coastal hazards and sea level rise (SLR) are staggering—evaluated at over a trillion U.S. dollars. Despite being enormous in the aggregate, potential losses due to SLR depend on mitigation, adaptation, and exposure and are highly uneven in their distribution across coastal cities. We provide the first analysis of how changes in exposure ( how and when ) have unfolded over more than a century of coastal urban development in the United States. We do so by leveraging new historical settlement layers from the Historical Settlement Data Compilation for the U.S. (HISDAC-US) to examine building patterns within and between the SLR zones of the conterminous United States since the early twentieth century. Our analysis reveals that SLR zones developed faster and continue to have higher structure density than non-coastal, urban, and inland areas. These patterns are particularly prominent in locations affected by hurricanes. However, density levels in historically less-developed coastal areas are now quickly converging on early settled SLR zones, many of which have reached building saturation. These “saturation effects” suggest that adaptation polices targeting existing buildings and developed areas are likely to grow in importance relative to the protection of previously undeveloped land. 

Information about grants funded by NSF to support SES research from 2000-2015. The grants included in this dataset are a subset that we identified as having an SES research focus from a set of grants accessed using the Dimensions platform (https://dimensions.ai). CSV file with 35 columns and names in header row: "Grant Searched" lists the granting NSF program (text); "Grant Searched 2" lists a secondary granting NSF program, if applicable (text); "Grant ID" is the ID from the Dimensions platform (string); "Grant Number" is the NSF Award number (integer); "Number of Papers (NSF)" is the count of publications listed under "PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH" in the NSF Award Search page for the grant (integer); "Number of Pubs Tracked" is the count of publications from "Number of Papers (NSF)" included in our analysis (integer); "Publication notes" are our notes about the publication information. We used "subset" to denote when a grant was associated with >10 publications and we used a random sample of 10 publications in our analysis (text); "Unique ID" is our unique identifier for each grant in the dataset (integer); "Collaborative/Cross Program" denotes whether the grant was submitted as part of a set of collaborative or cross-program proposals. In this case, all linked proposals are given the same unique identifier and treated together in the analysis. (text); "Title" is the title of the grant (text); "Title translated" is the title of the grant translated to English, where applicable (text); "Abstract" is the abstract of the grant (text); "Abstract translated" is the abstract of the grant translated to English, where applicable (text); "Funding Amount" is the numeric value of funding awarded to the grant (integer); "Currency" is the currency associated with the field "Funding Amount" (text); "Funding Amount in USD" is the numeric value of funding awarded to the grant expressed in US Dollars (integer); "Start Date" is the start date of the grant (mm/dd/yyyy); "Start Year" is the year in which grant funding began (year); "End Date" is the end date of the grant (mm/dd/yyyy); "End Year" is the year in which the term of the grant expired (year); "Researchers" lists the Principal Investigators on the grant in First Name Last Name format, separated by semi-colons (text); "Research Organization - original" gives the affiliation of the lead PI as listed in the grant (text); "Research Organization - standardized" gives the affiliation of each PI in the list, separated by semi-colons (text); "GRID ID" is a list of the unique identifier for each the Research Organization in the Global Research Identifier Database [https://grid.ac/?_ga=2.26738100.847204331.1643218575-1999717347.1643218575], separated by semi-colons (string); "Country of Research organization" is a list of the countries in which each Research Organization is located, separated by semi-colons (text); "Funder" gives the NSF Directorate that funded the grant (text); "Source Linkout" is a link to the NSF Award Search page with information about the grant (URL); "Dimensions URL" is a link to information about the grant in Dimensions (URL); "FOR (ANZSRC) Categories" is a list of Field of Research categories [from the Australian and New Zealand Standard Research Classification (ANZSRC) system] associated with each grant, separated by semi-colons (string); "FOR [1-5]" give the FOR categories separated. "NOTES" provide any other notes added by the authors of this dataset during our processing of these data. 

Detailed information and published mission or aims scope for journals in which 3 or more publications from the dataset Publications associated with SES grants, 2000-2015 appeared. CSV file with 10 columns and names in header row: journal is the name of the scientific journal or outlet in which at least 3 papers were published (text); number of papers is the number of papers from the dataset Publications associated with SES grants, 2000-2015 published in the journal (integer); Impact factor is the most recent available Impact Factor for the journal as of March 2020 (float); Discipline is the broad disciplinary category to which the journal belongs, as identified by the authors of this dataset (text); Stated aimsscope is the text of the journal aimsscope as provided on the journal website (text); Mission includes interdisciplinary? categorizes whether the stated aimsscope of the journal includes dissemination of interdisciplinary research (Y indicates the stated aimsscope explicitly include interdisciplinary research, I indicates that publication of interdisciplinary research is implicit but not directly stated in the aimsscope, N indicates there is no evidence that interdisciplinary research are part of the aimsscope of the journal); Mission includes humans/social? categorizes whether the stated aimsscope of the journal includes dissemination of research about human or social systems (Y indicates the stated aimsscope include some mention of human impacts, social systems, etc., N indicates there is no evidence that research on human or social systems are part of the aimsscope of the journal) Gutcheck Interdisciplinary? is an evaluation of whether the journal publishes interdisciplinary research as a matter of course, as judged by the authors of the dataset (Y indicates the journal publishes interdisciplinary research s a matter of course, N indicates journal does not tend to publish interdisciplinary research, kinda to indicate some history of publishing interdisciplinary research that may not be a major focus of published content. Forward slashes between values show where the dataset authors differed in their assessments.); Gutcheck CNHS? is an evaluation of whether the journal publishes research on socio-environmental systems (social-ecological systems, coupled natural and human systems) as a matter of course, as judged by the authors of the dataset (Y indicates the journal publishes research on socio-environmental systems as a matter of course, N indicates journal does not tend to publish research on socio-environmental systems , kinda to indicate some history of publishing research on socio-environmental systems that may not be a major focus of published content. Forward slashes between values show where the dataset authors differed in their assessments.); Notes provide any other notes added by the authors of this dataset during our processing of these data (text). 

Information about individual publications associated with grants funded by NSF to support SES research from 2000-2015 (see "SES grants, 2000-2015"). For grants with ten or fewer publications, we included information about all available publications in this dataset. For grants with more than ten publications, we randomly selected ten to include in this dataset. CSV file with 13 columns and names in header row: "Grant ID" is the ID from the Dimensions platform (string); "Grant Number" is the NSF Award number (integer); "Publication Title" is the title of the paper (text); "Publication Year" is the year in which the paper was published (year); "Authors" is a list or abbreviated list of the authors of the paper (text); "Journal" is the name of the scientific journal or outlet in which the paper is published (text); "Interdis Rubric 1" is a metric representing the dataset authors' assessment for the level of interdisciplinarity represented by the paper (integer: “1” indicated social and natural science interdisciplinarity where both social and environmental conditions are measured or explored and/or author affiliations included departments across these disciplines; “2” indicated general interdisciplinarity between two or more different fields (that may both be within natural or social science); and “3” indicated single-disciplinarity) "Citations" is the count of citations the paper had received as of the date listed in "date for cite count", as reported in Google Scholar (integer); "date for cite count" is the date on which citation count for the paper was obtained (ddBBByy); "Abstract" is the text of the abstract of the paper, where available (text); "Notes" are any notes added by the authors of the dataset (text). 

CSV file with header row and two columns: "Journal" lists names of journals (text) "Discipline" lists broad disciplinary category to which the journal belongs, as identified by the authors of this dataset (text) 

The growing push for open data resulted in an abundance of data for coastal researchers, which can lead to problems for individual researchers related to data discoverability. One solution is to explicitly develop services for coastal researchers to help curate data for discovery, hosting discussions around reuse, community building, and finding collaborators. To develop the idea of a coastal data curation service, we investigate aspects of the UNESCO International Coastal Atlas Network member sites that could be used to build a curation service. We develop a minimal example of a coastal data curation service, deploy this as a website, and describe the next steps to move beyond the prototype phase. We envision a coastal data curation service as a way to cultivate a community focused on coastal data discovery and reuse.