Analyzing criteria for selecting data intended for long-term preservation at the scientific library
https://doi.org/10.33186/1027-3689-2025-7-102-121
Abstract
The spiraling information flows and information preservation demand indepth analysis of criteria to separate valuable data from those with no value, to determine preservation time, and to identify the entries. The purpose of the study is to explore into the selection criteria and to specify those necessary and sufficient to be used by scientific libraries to evaluate and differentiate incoming information. Based on the analysis, the author specifies the criteria for scientific data acquisition and evaluation in the context of time and format diversity; the criteria were grouped based on utilization: for resource selection, data evaluation and inclusion into the database to be stored. The procedures for each criteria and related librarian competences are reviewed. The author specifies the criteria most relevant to scientific literature selection (scientific/historical value, legal assessment) and the secondary ones (completeness, duplication, etc.). The related librarian competences are identified. The author also examines challenges that hinder application of individual criteria and proposes the solutions.
The study findings can be useful for librarians, archivists, and information specialists to acquire and analyze the data for further digital preservation.
The study is completed within the Library’s for Natural Sciences of the Russian Academy of Sciences R&D project “Improvement of methods of long-term preservation of scientific information as the basis of knowledge in the natural sciences”.
About the Author
E. V. Beskaravainaya
Library for Natural Sciences, Russian Academy of Sciences
Russian Federation
Russian Federation
Elena V. Beskaravainaya – Senior Researcher, Library for Natural Sciences
Moscow
References
1. Stoliarov Iu. N. Bibliotechny`i` fond : uchebnoe dlia studentov vuzov, obuchaiushchikhsia po napravleniiu podgotovki 071900 «Bibliotechno-informatcionnaia deiatel`nost`»: kvalifikatciia bakalavr / Iu. N. Stoliarov. Sankt-Peterburg : Izdatel`stvo Professiia, 2015. 383 s. ISBN 978-5-904757-87-8.
2. Gureev V. N. Ispol`zovanie bibliometrii dlia ocenki znachimosti zhurnalov v nauchny`kh bibliotekakh. (Obzor) // Nauchno-tekhnicheskaia informatciia. Ser. 1: Organizatciia i metodika informatcionnoi` raboty`. 2015. № 2. S. 8–19.
3. Zemskov A. I., Evstigneeva G. A. Rol` bibliotek na mirovom ry`nke nauchny`kh publikatcii` // Vestneyk Rossii`skogo fonda fundamental`ny`kh issledovanii`. 2005. №. 4. S. 51–56.
4. Vikhreva G. M., Podkory`tova N. I., Fedotova O. P. Issledovaniia sistemy` fondov bibliotek Sibirskogo otdeleniia Rossii`skoi` akademii nauk // Trudy` GPNTB SO RAN. 2021. № 2 (10). S. 23–33. https://doi.org/10.20913/2618-7575-2021-2-23-33.
5. Vikhreva G. M., Fedotova O. P. Problemy` formirovaniia bibliotechnogo fonda v kontekste filosofii cennostei` // Bibliosfera. 2017. № 2. S. 12–16. https://doi.org/10.20913/1815-3186-2017-2-12-16.
6. Whyte A., Wilson A. How to Appraise and Select Research Data for Curation. DCC How-to Guides. Edinburgh: Digital Curation Centre. 2010. URL: dcc.ac.uk/resources/howguides/appraise-select-data (access: 23.02.2025).
7. Data management costing tool and checklist, version 3, UK Data Service.: UK Data Service (UKDS). 2015. URL: ukdataservice.ac.uk/manage-data/plan/costing (access: 03.03.2025).
8. DCC, Five steps to decide what data to keep: checklist for appraising research data // Edinburgh: Digital Curation Centre. 2014. Vol. 1. URL: dcc.ac.uk/resources/how-guides (access: 11.02.2025).
9. Tenopir C., Rice N. M., Allard S., Baird L., Borycz J., Christian L. et al. Data sharing, management, use, and reuse: Practices and perceptions of scientists worldwide // PLoS ONE. 2020. Vol. 15. № 3. e0229003. https://doi.org/10.1371/journal.pone.0229003.
10. Antopol`skii` A. B. Budushchee nauchny`kh kommunikatcii` i nauchnoi` informatcii // Informatciia i innovatcii. 2019. T. 14. № 1. S. 7–17.
11. Kirillova O. V. Redaktcionnaia podgotovka nauchny`kh zhurnalov po mezhdunarodny`m standartam: rekomendatcii e`ksperta BD Scopus. Moskva, 2013. 90 s. ISBN 978-5-518-73515-6.
12. Mokhnachyova Iu. V., Tcvetkova V. A. Vozmozhny`e puti polucheniia nauchnoi` informatcii v novy`kh usloviiakh // Upravlenie naukoi`: teoriia i praktika. 2023. T. 5. № 3. S. 117–158. https://doi.org/10.19181/smtp.2023.5.3.9.
13. Tcvetkova V. A., Mokhnachyova Iu. V., Hary`bina T. N., Beskaravai`naia E. V., Mitroshin I. A. Prostranstvo znanii`: podhody` k izvlecheniiu znanii` iz nauchny`kh tekstov // Informatcionny`e resursy` Rossii. 2019. № 2 (168). S. 31–34.
14. Zemskov A. I. Data Curation khranenie nauchny`kh danny`kh i obsluzhivanie imi novoe napravlenie deiatel`nosti bibliotek // Nauchny`e i tekhnicheskie biblioteki. 2013. № 2. S. 85–101.
15. Krasnov F. V., Dimentov A. V., Shvartcman M. E. Ispol`zovanie tematicheskikh modelei` dlia parnogo sravneniia kollektcii` nauchny`kh statei` // Informatika i eyo primeneniia. 2020. T. 14. №. 3. S. 129–135.
16. Anohin A. M., Glotov V. A., Pavel`ev V. V., Cherkashin A. M. Metody` opredeleniia koe`ffitcientov vazhnosti kriteriev. Avtomatika i telemehanika // Avtomatika i telemehanika. 1997. № 8. S. 3–35.
17. Ozbey C., Dincsoy O. An Efficient Pairwise Comparison Scheme for Document Ranking. 2020 28th Signal Processing and Communications Applications Conference (SIU), Gaziantep, Turkey, 2020. Pp. 1–4. https://doi.org/10.1109/SIU49456.2020.9302078.
18. Zhang Z., Zhau J., Liu N., Gu, X., Zhang Y. An improved pairwise comparison scaling method for subjective image quality assessment/2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Cagliari, Italy, 2017. Pp. 1–6. https://doi.org/10.1109/BMSB.2017.7986235.
19. Hakimova E. V. Avtomatizirovannaia sistema komplektovaniia knizhnogo fonda na osnove e`kspertny`kh ocenok // Perspektivy` razvitiia informatcionny`kh tekhnologii`. 2011. № 3–2. S. 258–262.
20. Gureev V. N. Modeli i kriterii otbora izdanii` v fond nauchnoi` biblioteki // Nauchny`e i tekhnicheskie biblioteki. 2015. № 7. S. 31–50.
21. Ivanov Iu. N. Osnovny`e kriterii otbora dokumentov s pozitcii` istoricheskoi` cennosti i dostovernosti // Крыніцазнаўства, археаграфія, архівазнаўства ў XX–XXI ст. у Беларусі : зб. навук. артыкулаў, прысвечаных 100-годдзю з дня нараджэння М. М. Улашчыка / рэдкал. : С. М. Ходзін (адк. рэд.) [і інш.]. Мінск : BDU, 2007. S. 203–210. ISBN 978-985-485-977-4.
22. Brakker N. V., Kui`by`shev L. A. Sbor i arhivirovanie setevy`kh resursov. Opy`t natcional` ny`kh bibliotek zarubezhny`kh stran // Bibliotekovedenie. 2013. № 2. S. 88–96. https://doi.org/10.25281/0869-608X-2013-0-2-88-96.
23. Alebastrova E. S. Kraevedcheskii` kontent E`lektronnoi` biblioteki Natcional`noi` biblioteki Respubliki Saha (Iakutiia): problemy` formirovaniia i ispol`zovaniia // Vestneyk natcional`noi` biblioteki Respubliki Saha (Iakutiia). 2019. № 2 (19). S. 19–24.
24. Stepanov V. K. Formirovanie tcifrovy`kh kollektcii` v traditcionny`kh bibliotekakh // Nauchny`e i tekhnicheskie biblioteki. 2007. № 2. С. 89–94.
25. Bocharova E. N. Kriterii otbora dokumentov v fond nauchnoi` biblioteki // Vzaimovliianie informatcionno-bibliotechnoi` sredy` i obshchestvenny`kh nauk : sbornik nauchny`kh statei` / RAN. INION. Fundamental`naia biblioteka ; nauch. red. L. N. Tihonova, A. A. Dzhigo. Moskva : Institut nauchnoi` informatcii po obshchestvenny`m naukam RAN, 2018. S. 62–78.
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For citations:
Beskaravainaya E.V. Analyzing criteria for selecting data intended for long-term preservation at the scientific library. Scientific and Technical Libraries. 2025;(7):102-121. (In Russ.) https://doi.org/10.33186/1027-3689-2025-7-102-121
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