Skip to main content

Advertisement

Log in

Exploring best practices in data management: examples from cave and karst research and resource management

  • Original Article
  • Published:
Carbonates and Evaporites Aims and scope Submit manuscript

Abstract

In August 2020, researchers and resource managers from around the world gathered virtually for Conservation of Fragile Karst: A Workshop on Sustainability and Community, in support of UNESCO science programs. The purpose of the workshop was to enhance communication and the sharing of ideas and resources between major international conservation and science programs that protect, study, or manage cave and karst resources. As part of this meeting, a workshop was held to help resource managers and researchers consider data from a data management perspective. The goal was to familiarize participants with best practices in data management, provide resources for following these practices, and promote an understanding and appreciation of the benefits of good data management.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

modified from https://opendatawatch.com/publications/the-data-value-chain-moving-from-production-to-impact/) represents the cycles of production, use, and reuse that add value to data over time. These cycles are continuous, and value increases with each iteration

Fig. 2
Fig. 3

Similar content being viewed by others

Availability of data and materials

Not applicable.

Code availability

Not applicable.

References

  • Belter CW (2014) Measuring the value of research data: A citation analysis of oceanographic data sets. PLoS ONE 9(3):e92590. https://doi.org/10.1371/journal.pone.0092590

    Article  Google Scholar 

  • Borghi J, Abrams S, Lowenberg D, Simms S, Chodacki J (2018) Support your data: A research data management guide for researchers. Res Ideas Outcomes 4:e26439. https://doi.org/10.3897/rio.4.e26439

    Article  Google Scholar 

  • Borgman C, Wallis J, Enyedy N (2007) Little science confronts the data deluge: habitat ecology, embedded sensor networks, and digital libraries. Int J Digit Libr 7:17–30. https://doi.org/10.1007/s00799-007-0022-9

    Article  Google Scholar 

  • Carlson J (2014) The use of lifecycle models in developing and supporting data services. In: Ray J (ed) Research data management: Practical strategies for information professionals. Purdue University Press, West Lafayette

    Google Scholar 

  • Chen Z, Auler AS, Bakalowicz M, Drew D, Griger F, Hartmann J, Jiang G, Moosdorf N, Richts A, Stevanovic Z, Veni G, Goldscheider N (2017a) The World Karst Aquifer Mapping project: concept, mapping procedure and map of Europe. Hydrogeol J 25:771–785. https://doi.org/10.1007/s10040-016-1519-3

    Article  Google Scholar 

  • Chen Z, Goldscheider N, Auler A, Bakalowicz M, Broda S, Drew D, Hartmann J, Jiang G, Moosdorf N, Richts A, Stevanovic Z, Veni G, Dumont A, Aureli A, Clos P, Krombholz M (2017b) World Karst Aquifer Map (WHYMAP WOKAM). BGR IAH, KIT, UNESCO. https://doi.org/10.25928/b2.21_sfkq-r406

    Book  Google Scholar 

  • Chung Y, Servan-Schrieber S, Zgraggen E, Kraska T (2018) Towards quantifying uncertainty in data analysis & exploration. Bull IEEE Comput Soc Tech Comm Data Eng 41:15–27

    Google Scholar 

  • Cox AM, Tam WWT (2018) A critical analysis of lifecycle models of the research process and research data management. Aslib J Inf Manag 70(2):142–157. https://doi.org/10.1108/ajim-11-2017-0251

    Article  Google Scholar 

  • Faundeen JL, Burley TE, Carlino JA, Govoni DL, Henkel HS, Holl SL, Hutchison VB, Martín E, Montgomery ET, Ladino CC, Tessler S, Zolly LS (2013) The United States Geological Survey Science Data Lifecycle Model: U.S. Geological Survey Open-File Report 2013–1265, 4 p. https://doi.org/10.3133/ofr20131265

  • Federer LM, Belter CW, Joubert DJ, Livinski A, Lu Y-L, Snyders LN, Thompson H (2018) Data sharing in PLOS ONE: an analysis of data availability statements. PLoS ONE 13(5):e0194768. https://doi.org/10.1371/journal.pone.0194768

    Article  Google Scholar 

  • Gil Y, David CH, Demir I, Essawy BT, Fulweiler RW, Goodall JL, Karlstrom L, Lee H, Mills HJ, Oh J, Pierce SA, Pope A, Tzeng MW, Villamizar SR, Yu X (2016) Toward the Geoscience Paper of the Future: Best practices for documenting and sharing research from data to software to provenance. Earth Sp Sci 3:388–415. https://doi.org/10.1002/2015EA000136

    Article  Google Scholar 

  • Goldstein JC, Mayernik MS, Ramapriyan HK (2017) Identifiers for earth science data sets: where we have been and where we need to go. Data Sci J 16(23):1–12. https://doi.org/10.5334/dsj-2017-023

    Article  Google Scholar 

  • Goodman A, Pepe A, Blocker AW, Borgman CL, Cranmer K, Crosas M, Di Stefano R, Gil Y, Groth P, Hedstrom M, Hogg DW, Kashyap V, Mahabal A, Siemiginowska A, Slavkovic A (2014) Ten simple rules for the care and feeding of scientific data. PLoS Comput Biol 10(4):e1003542. https://doi.org/10.1371/journal.pcbi.1003542

    Article  Google Scholar 

  • Guo H (2017) Big Earth data: A new frontier in Earth and information sciences. Big Earth Data 1(1–2):4–20. https://doi.org/10.1080/20964471.2017.1403062

    Article  Google Scholar 

  • Häuselmann P (2011) UIS mapping grades. Int J Speleol 40(2):IV–VI

    Google Scholar 

  • Helf KL, Moore W, Wells B (2018) Monitoring cave aquatic biota at selected parks in the Cumberland Piedmont Network: Data quality standards—version 1.0. Natural Resource Report. NPS/CUPN/NRR—2018/1696. National Park Service. Fort Collins, Colorado.

  • Holdren JP (2013) Memorandum for the Heads of Executive Departments and Agencies: Increasing Access to the Results of Federally Funded Scientific Research (Office of Science and Technology Policy). http://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf. Accessed 1 July 2020

  • International DOI Foundation (2020) Factsheet: Key Facts on Digital Object Identifier System. https://www.doi.org/factsheets/DOIKeyFacts.html. Accessed 10 Jan 2021

  • Irwin A (2018) No PhDs needed: How citizen science is transforming research. Nature 562:480–482. https://doi.org/10.1038/d41586-018-07106-5

    Article  Google Scholar 

  • Klump J, Huber R, Diepenbroek M (2016) DOI for geoscience data—how early practices shape present perceptions. Earth Sci Inform 9(1):123–136. https://doi.org/10.1007/s12145-015-0231-5

    Article  Google Scholar 

  • McKinley DC, Miller-Rushing AJ, Ballard HL, Bonney R, Brown H, Cook-Patton SC, Evans DM, French RA, Parrish JK, Phillips TB, Ryan SF, Shanley LA, Shirk JL, Stepenuck KF, Weltzin JF, Wiggins A, Boyle OD, Briggs RD, Chapin SF III, Hewitt DA, Preuss PW, Soukup MA (2017) Citizen science can improve conservation science, natural resource management, and environmental protection. Biol Conserv 208:15–28. https://doi.org/10.1016/j.biocon.2016.05.015

    Article  Google Scholar 

  • National Academies of Sciences, Engineering, and Medicine (2018) Open science by design: realizing a vision for 21st century research. National Academies Press, Washington, DC

    Google Scholar 

  • Olarinoye T et al (2019) Global karst springs hydrograph dataset for research and management of the world’s fastest-flowing groundwater. figshare. https://doi.org/10.6084/m9.figshare.9638939.v2. Accessed 1 July 2020

  • Olarinoye T, Gleeson T, Marx V, Seeger S, Adinehvand R, Allocca V, Andreo B, Apaéstegui J, Apolit C, Arfib B, Auler A, Barberá JA, Batiot-Guilhe C, Bechtel T, Binet S, Bittner D, Blatnik M, Bolger T, Brunet P, Charlier J-P, Chen Z, Chiogna G, Coxon G, De Vita P, Doummar J, Epting J, Fournier M, Goldscheider N, Gunn J, Guo F, Guyot JL, Howden N, Huggenberger P, Hunt B, Jeannin P-Y, Jiang G, Jones G, Jourde H, Karmann I, Koit O, Kordilla J, Labat D, Ladouche B, Liso IS, Liu Z, Massei N, Mazzilli N, Mudarra M, Parise M, Pu J, Ravbar N, Sanchez LH, Santo A, Sauter M, Sivelle V, Skoglund RØ, Stevanovic Z, Wood C, Worthington S, Hartmann A (2020) Global karst springs hydrograph dataset for research and management of the world’s fastest-flowing groundwater. Sci Data 7(59):1–9. https://doi.org/10.1038/s41597-019-0346-5

    Article  Google Scholar 

  • Rentmeester S (ed) (2010) Regional Guidance on Metadata for Environmental Data. PNAMP Series Report No. 2010–001. Cook, WA: Pacific Northwest Aquatic Monitoring Partnership. http://www.pnamp.org/document/2771. Accessed 1 July 2020

  • Stall S, Yarmey LR, Boehm R, Cousiijn H, Cruse P, Cutcher-Gershenfeld J, Dasler R, de Waard A, Duerr R, Elger K, Fenner M, Glaves H, Hanson B, Hausman J, Heber J, Hills DJ, Hoebelheinrich N, Hou S, Kinkade D, Koskela R, Martin R, Lehnert K, Murphy F, Nosek B, Parsons MA, Petters J, Plante R, Robinson E, Samors R, Servilla M, Ulrich R, Witt M, Wyborn L (2018) Advancing FAIR Data in Earth, space, and environmental science. Eos. https://doi.org/10.1029/2018EO109301

    Article  Google Scholar 

  • Stall S, Yarmey L, Cutcher-Gershenfeld J, Hanson B, Lehnert K, Nosek B, Parsons M, Robinson E, Wyborn L (2019) Make all scientific data FAIR. Nature 570:27–29. https://doi.org/10.1038/d41586-019-01720-7

    Article  Google Scholar 

  • Stevens LE, Springer AE, Ledbetter JD (2016) Springs ecosystem inventory protocols. Springs Stewardship Institute, Museum of Northern Arizona, Flagstaff

    Google Scholar 

  • Vannan S, Downs RR, Meier W, Wilson BE, Gerasimov IV (2020) Data sets are foundational to research. Why don’t we cite them? Eos. https://doi.org/10.1029/2020EO151665

    Article  Google Scholar 

  • Volk CJ, Lucero Y, Barnas K (2014) Why is data sharing in collaborative natural resource efforts so hard and what can we do to improve it? Env Manag 53(5):883–893. https://doi.org/10.1007/s00267-014-0258-2

    Article  Google Scholar 

  • Weary DJ, Doctor DH (2014) Karst in the United States: a digital map compilation and database. U.S. Geological Survey Open-File Report 2014–1156. https://doi.org/10.3133/ofr20141156

  • Wilkinson M, Dumontier M, Aalbersberg I, Appleton G, Axton M, Baak A, Blomberg N, Boiten J, Bonino de Silva Santos L, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJG, Groth P, Goble C, Grethe JS, Heringa J, Hoen PAC, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, Rv S, Sansone S, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B (2016) The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3:160018. https://doi.org/10.1038/sdata.2016.18

    Article  Google Scholar 

  • Zheng F, Tao R, Maier HR, See L, Savic D, Zhang T, Chen Q, Assumpção TH, Yang P, Heidari B, Rieckermann J, Minsker B, Bi W, Cai X, Solomatine D, Popescu I (2018) Crowdsourcing methods for data collection in geophysics: state of the art, issues, and future directions. Rev Geophys 56:698–740. https://doi.org/10.1029/2018RG000616

    Article  Google Scholar 

Download references

Funding

No funding was received to assist with the preparation of this manuscript.

Author information

Authors and Affiliations

Authors

Contributions

SMA: conceptualization, writing—original draft preparation, and literature search. PNK: conceptualization, writing—review and editing, and literature search.

Corresponding author

Correspondence to Sarah M. Arpin.

Ethics declarations

Conflicts of interest/competing interests

The authors have no conflicts of interest to declare that are relevant to the content of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Arpin, S.M., Kambesis, P.N. Exploring best practices in data management: examples from cave and karst research and resource management. Carbonates Evaporites 37, 53 (2022). https://doi.org/10.1007/s13146-022-00772-7

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13146-022-00772-7

Keywords

Navigation