Kevin A. Butler

Lauren A. Jackson

Michael C. Kruk

Nazila Merati

Tiffany C. Vance

Frontiers in Climate

Directory of Open Access Journals

TYPE EditorialPUBLISHED 17 January 2023DOI 10.3389/fclim.2022.1081021OPEN ACCESSEDITED AND REVIEWED BYChris C. Funk,College of Letters & Science (UC),United States*CORRESPONDENCELauren A. Jacksonlauren.jackson@noaa.govSPECIALTY SECTIONThis article was submitted toClimate Services,a section of the journalFrontiers in ClimateRECEIVED 26 October 2022ACCEPTED 15 December 2022PUBLISHED 17 January 2023CITATIONButler KA, Jackson LA, Kruk MC,Merati N and Vance TC (2023)Editorial: Democratizing data:Environmental data access and itsfuture. Front. Clim. 4:1081021.doi: 10.3389/fclim.2022.1081021COPYRIGHT© 2023 Butler, Jackson, Kruk, Meratiand Vance. This is an open-accessarticle distributed under the terms ofthe Creative Commons AttributionLicense (CC BY). The use, distributionor reproduction in other forums ispermitted, provided the originalauthor(s) and the copyright owner(s)are credited and that the originalpublication in this journal is cited, inaccordance with accepted academicpractice. No use, distribution orreproduction is permitted which doesnot comply with these terms.Editorial: Democratizing data:Environmental data access andits futureKevin A. Butler1, Lauren A. Jackson2*, Michael C. Kruk2,Nazila Merati3 and Ti any C. Vance41Environmental Systems Research Institute (ESRI), Redlands, CA, United States, 2National Centers forEnvironmental Information, National Oceanic and Atmospheric Administration (NOAA),Stennis Space Center, MS, United States, 3National Centers for Environmental Information, NationalOceanic and Atmospheric Administration (NOAA), Boulder, CO, United States, 4United States (U.S.)Integrated Ocean Observing System, National Oceanic and Atmospheric Administration (NOAA),Silver Spring, MD, United StatesKEYWORDSdata discoverability, data access, data and service equity, data usability,reproducibility, environmental dataEditorial on the Research TopicDemocratizing data: Environmental data access and its futureBrief introduction to the Research TopicData democratization is the equal and interdependent responsibility of dataproducers, consumers, and curators to make data discoverable, accessible, equitable,and usable (Figure 1). The genesis of democratization stems from critical changesin the supply and demand of data over the last decades. First, the supply of data,particularly environmental data, has exploded, partly due to improvements in thenumber and resolution of observational platforms and governmental entities and privateorganizations embracing the philosophy of open public data declaring data as a publicgood. Likewise, the increased demand for environmental data stems from the realizationthat planet-scale problems require planet-scale analyses and an increased emphasis ondata-driven environmental decision-making (Tonn et al., 2000).The global phenomenon of datafication (Mayer-Schönberger and Cukier, 2013)has resulted in ever-increasing availability, demand, and use of environmental data atunprecedented physical and social scales. Taylor (1997, p. 327) prophetically states,“in the twenty-first century, the community—not the federal government—will be theprincipal unit of solution to social and economic difficulties.” This shift has expandedthe collection and reach of environmental data to previously unforeseen data consumerssuch as citizen scientists. However, even traditional consumers of environmental data,science practitioners, face data challenges in this era of big data. Meeting the goals of dataas a public good and supporting science at local scales requires a new perspective on theproduction, management, and curation of data. We refer to this new perspective as datademocratization—introducing democratic principles into all aspects of data processesFrontiers inClimate 01 frontiersin.orgButler et al. 10.3389/fclim.2022.1081021(see Tilly, 2001 for a complete discussion of democratization).The submissions in this Research Topic raise importantquestions and provide practical examples for making data morediscoverable, accessible, equitable, and usable.Demographics of participationThe nine articles on the Research Topic were submittedby 43 authors representing 27 institutions or organizations.The majority (58%) were submitted by authors affiliated witheducational institutions, with the remainder from commercial(7%), governmental (21%), or non-profit (14%) entities.The heterogeneous institutional affiliations suggest thatdemocratizing data presents challenges and opportunities for alldata producers.Topics of the collectionThree broad themes emerged from the collection:• Maintaining a user focus in all aspects of the datalifecycle: Virapongse et al. challenge Earth scientists to beintrospective about the methods and processes they useto produce more effective information products to helpplace-based communities build resilience. Cantor et al.FIGURE 1Components of data democratization.suggest that the decision-maker needs to be incorporateddirectly into data systems design. Finally, Gärtner-Roeret al. highlight the recent increased availability of glacierdata and the role a centralized user-focused repository andstandards organization can play.• Making data usability a priority: Stern et al. describean open-source platform for extracting archival data andcreating analysis-ready, cloud-optimized data stores thatempower a broader community of scientists. Contributorsalso highlighted the challenges of repurposing and makingexisting data repositories more usable (Rossi et al.) andunique usability challenges in 3D data (Paxton et al.).• Ensuring data veracity and equity: In addition to thetraditional data veracity challenges in big environmentaldata, ensuring veracity in time series (Sweeney) andsimulation data (Mullendore et al.) presented uniquechallenges. Finally, Dosemagen and Williams state thatprioritizing environmental data as a public good is akey to data usability, and usability is key to addressingenvironmental justice issues.Increased pressure from funding agencies that promoteor even mandate open data sharing has resulted in a newperspective on data—an explicit focus on the user. Historically,the data lifecycle supported the process of knowledge production,collecting, and analyzing data for peer-reviewed journalpublications (Baker and Mayernik, 2020). A complementaryFrontiers inClimate 02 frontiersin.orgButler et al. 10.3389/fclim.2022.1081021data lifecycle, data production, “creates data intended for releaseto a data repository that makes data accessible for reuseby others” (p. 4). This user-focused perspective dramaticallyimpacts how data are documented, managed, and shared. Justas a democratic system of government requires an informedcitizenry, democratized systems of data require informeddata users.While big environmental data presents tremendousopportunities, they also come with tremendous challenges.For example, data’s sheer volume, variety, and velocitycan impede its usability. Contributors touched on manyaspects of the findability, accessibility, interoperability,and reuse (FAIR) principles (Wilkinson et al., 2016),providing the following insights that help reach the goalsof democratization:• View data not as stand-alone datasets but as a system in andof itself (Stern et al.).• Design data systems to meet the data needs of decision-makers (decision-driven data systems) rather thanrequiring decision-makers to adapt to existing systems(Cantor et al.).• Include data users and producers in the design of dataaccess systems (Dosemagen and Williams).• Strive for effective use of data (Virapongse et al.).Data veracity is, arguably, the riskiest aspect of datademocratization. Issues of data quality and fitness for purposebecome more critical as data sharing and data use networksgrow beyond the data producer. Producers and curatorsare responsible for summarizing and communicating dataquality issues and fitness for purpose in a form and toneapproachable by data users outside the subject domainand the technical expertise of the data producers. Thisapproach is consistent with the trend in several academicconferences and journals requesting a plain-language summaryof scientific research.Beyond FAIRHow is data democratization different from the FAIRprinciples? While the FAIR principles are an essential firststep to promoting the democratization of data, they are,in our view, focused on the data provider. Boeckhoutet al. (2018, p. 931) argue that “even though the principlescreate a powerful platform for furthering data sharingand improving data stewardship, they do not addressthe normative issues and challenges associated withdata sharing.” Strict check-listed adherence to the FAIRprinciples is a necessary but insufficient first step. Datademocratization is a more holistic, comprehensive view ofa process to make data discoverable, accessible, equitable,and usable.Although not mentioned in our Research Topic, the CAREprinciples are a seminal example of shifting the focus from dataproviders to data consumers and moving beyond FAIR (Carrollet al., 2021). Developed by and for indigenous communities,these principles promote data ecosystems that provide collectivebenefit, where the authority to control the data resides with thedata subjects and where there is a recognized responsibility toengage respectfully with data subjects. In addition, the ethics ofthe data subjects should inform data use.Author contributionsKB and LJ drafted the content of this document. MK, TV,and NM provided edits. KB contributed figures. All authorscontributed to the article and approved the submitted version.AcknowledgmentsThe topic editors thank the authors that contributedpapers to this topic. We also thank the reviewers for theirdedication and time invested in providing invaluable feedbackto the authors.Conflict of interestKB was employed by Environmental Systems ResearchInstitute (ESRI).The remaining authors declare that the research wasconducted in the absence of any commercial or financialrelationships that could be construed as a potential conflictof interest.Publisher’s noteAll claims expressed in this article are solely those of theauthors and do not necessarily represent those of their affiliatedorganizations, or those of the publisher, the editors and thereviewers. Any product that may be evaluated in this article, orclaim that may be made by its manufacturer, is not guaranteedor endorsed by the publisher.Frontiers inClimate 03 frontiersin.orgButler et al. 10.3389/fclim.2022.1081021ReferencesBaker, K. S., and Mayernik, M. S. (2020). Disentangling knowledge productionand data production. Ecosphere 11, e03191. doi: 10.1002/ecs2.3191Boeckhout, M., Zielhuis, G. A., and Bredenoord, A. L. (2018). The FAIR guidingprinciples for data stewardship: fair enough? Euro. J. Hum. Genet. 26, 931–936.doi: 10.1038/s41431-018-0160-0Carroll, S. R., Herczog, E., Hudson, M., Russell, K., and Stall, S. (2021).Operationalizing the CARE and FAIR principles for indigenous data futures. SciData 8, 108. doi: 10.1038/s41597-021-00892-0Mayer-Schönberger, V., and Cukier, K. (2013). Big Data: A Revolution ThatWill Transform How We Live, Work, and Think. Boston, MA: HoughtonMifflin Harcourt.Taylor, H. L. Jr. (1997). Nomore ivory towers: connecting the research universityto the community. J. Plan. Liter. 11, 327–332. doi: 10.1177/088541229701100304Tilly, C. (2001). Mechanisms in political processes. Ann. Rev. Polit. Sci. 4, 21–41.doi: 10.1146/annurev.polisci.4.1.21Tonn, B., English, M., and Travis, C. (2000). A framework for understanding andimproving environmental decision making. J. Environ. Plan. Manage. 43, 163–183.doi: 10.1080/09640560010658Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton,M., Baak, A., et al. (2016). The FAIR guiding principles for scientificdata management and stewardship. Sci. Data 3, 160018. doi: 10.1038/sdata.2016.18Frontiers inClimate 04 frontiersin.org

Editorial: Democratizing data: Environmental data access and its future

https://www.frontiersin.org/articles/10.3389/fclim.2022.1081021/pdf

Editorial: Democratizing data: Environmental data access and its future

Abstract

Similar works

Full text

Available Versions

Directory of Open Access Journals