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Data, Metadata, Narrative. Barriers to the Reuse of Cultural Sources

Part of the Communications in Computer and Information Science book series (CCIS,volume 755)

Abstract

The networking of objects facilitated by the Internet of Things isn’t new. Every object that is catalogued for display within a GLAM institution is assigned entry-level data, along with further data layers on that object that each interactive agent (researcher) will draw upon to create their research narratives, irrespective of their disciplinary background or bias. Within the community of researchers working with cultural data in particular, the desire to compare and aggregate diverse sources held together by a thin red thread of potential narrative cohesion, is only increasing. This poses challenges to information retrieval and contextualization in the digital age, it forces us to reassess the value and cost of metadata, and the consequences that accompany the use and reuse of digital data in a humanities or cultural research context. This paper discusses a number of the key barriers to the digital representation of complex cultural data and presents the preliminary findings and recommendations of the EU Commission’s Horizon 2020 funded KPLEX project (kplex-project.eu) in the field of knowledge complexity and cultural data.

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Notes

  1. 1.

    See [13] for a discussion on the impact of the absence of standardisation on the interoperability of historical trade data.

  2. 2.

    See [8] for further discussion of the cleaning that takes place in long-term data gathering projects.

  3. 3.

    “NASA EOS DIS Data Processing Levels,” https://science.nasa.gov/earth-science/earth-science-data/data-processing-levels-for-eosdis-data-products.

References

  1. Rosenberg, D.: Data before the fact. In: Gitelman, L. (ed.) “Raw Data” is an Oxymoron, pp. 15–40. MIT Press, London (2013)

    Google Scholar 

  2. Rosenthal, J.: Introduction: “Narrative against Data.” In: Genre 50.1, pp 1–18. Duke University Press, 1 April 2017. https://doi.org/10.1215/00166928-3761312

  3. Borgman, C.L.: Big Data, Little Data, No Data: Scholarship in the Networked World. MIT Press, Cambridge (2015)

    Google Scholar 

  4. Raley, R.: Dataveillance and Countervailance. In: Gitelman, L. (ed.) “Raw Data” is an Oxymoron, pp. 121–145. MIT Press, Cambridge (2013)

    Google Scholar 

  5. Briet, S.: Quoted in Day RE. Indexing It All: The Subject in the Age of Documentation, Information, and Data, p. 156. MIT Press, Cambridge (2014)

    Google Scholar 

  6. Briet, S., et al.: What Is Documentation? English Translation of the Classic French Text, p. 10. Scarecrow Press, Lanham (2006)

    Google Scholar 

  7. Uricchio, W.: Data, culture and the ambivalence of algorithms. In: Schäfer, M.T., van Es, K. (eds.) The Datafied Society: Studying Culture through Data, pp. 125–138. Amsterdam University Press, Amsterdam (2017)

    Google Scholar 

  8. Ribes, D., Jackson, S.J.: Data bite man: the work of sustaining a long-term study. In: Gitelman, L. (ed.) “Raw Data” is an Oxymoron, pp. 147–166. MIT Press, Cambridge (2013)

    Google Scholar 

  9. Presner, T.: The ethics of the algorithm: close and distant listening to the shoah foundation visual history archive. In: Fogu, C., Kansteiner, W., Presner, P. (eds.) Probing the Ethics of Holocaust Culture. Harvard University Press, Cambridge (2015)

    Google Scholar 

  10. Kahneman, D.: Thinking Fast and Slow. Farrar, Straus & Giroux Inc., New York (2013)

    Google Scholar 

  11. Brine, K.R., Poovey, M.: From measuring data to quantifying expectations: a late nineteenth-century effort to marry economic theory and data. In: Gitelman, L. (ed.) “Raw Data” is an Oxymoron, pp. 61–76. MIT Press, Cambridge (2013)

    Google Scholar 

  12. Edmond, J.: Will historians ever have big data? In: Bozic, B., Mendel-Gleason, G., Debruyne, C., O’Sullivan, D. (eds.) CHDDH 2016. IAICT, vol. 482, pp. 91–105. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46224-0_9

    Chapter  Google Scholar 

  13. Kirwan, L.: Databases for quantitative history. In: Proceedings of the Third Conference on Digital Humanities in Luxembourg with a Special Focus on Reading Historical Sources in the Digital Age, Luxembourg, December 5–6, CEUR Workshop Proceedings, 1613 (2013)

    Google Scholar 

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Acknowledgements

This work has been funded by the European Commission as a part of the Knowledge Complexity (KPLEX) project, contract number 732340. It bears an intellectual debt to Dr. Michelle Doran of the KPLEX project team.

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Correspondence to Georgina Nugent Folan .

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Edmond, J., Nugent Folan, G. (2017). Data, Metadata, Narrative. Barriers to the Reuse of Cultural Sources. In: Garoufallou, E., Virkus, S., Siatri, R., Koutsomiha, D. (eds) Metadata and Semantic Research. MTSR 2017. Communications in Computer and Information Science, vol 755. Springer, Cham. https://doi.org/10.1007/978-3-319-70863-8_25

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  • DOI: https://doi.org/10.1007/978-3-319-70863-8_25

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