Digital topics on cultural heritage investigated: how can data-driven and data-guided methods support to identify current topics and trends in digital heritage?
Abstract In research and policies, the identification of trends as well as emerging topics and topics in decline is an important source of information for both academic and innovation management. Since at present policy analysis mostly employs qualitative research methods, the following article pres...
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Format: | Article |
Language: | English |
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SpringerOpen
2021-12-01
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Series: | Built Heritage |
Subjects: | |
Online Access: | https://doi.org/10.1186/s43238-021-00045-7 |
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author | Sander Münster Ronja Utescher Selda Ulutas Aydogan |
author_facet | Sander Münster Ronja Utescher Selda Ulutas Aydogan |
author_sort | Sander Münster |
collection | DOAJ |
description | Abstract In research and policies, the identification of trends as well as emerging topics and topics in decline is an important source of information for both academic and innovation management. Since at present policy analysis mostly employs qualitative research methods, the following article presents and assesses different approaches – trend analysis based on questionnaires, quantitative bibliometric surveys, the use of computer-linguistic approaches and machine learning and qualitative investigations. Against this backdrop, this article examines digital applications in cultural heritage and, in particular, built heritage via various investigative frameworks to identify topics of relevance and trendlines, mainly for European Union (EU)-based research and policies. Furthermore, this article exemplifies and assesses the specific opportunities and limitations of the different methodical approaches against the backdrop of data-driven vs. data-guided analytical frameworks. As its major findings, our study shows that both research and policies related to digital applications for cultural heritage are mainly driven by the availability of new technologies. Since policies focus on meta-topics such as digitisation, openness or automation, the research descriptors are more granular. In general, data-driven approaches are promising for identifying topics and trendlines and even predicting the development of near future trends. Conversely, qualitative approaches are able to answer “why” questions with regard to whether topics are emerging due to disruptive innovations or due to new terminologies or whether topics are becoming obsolete because they are common knowledge, as is the case for the term “internet”. |
first_indexed | 2024-03-12T04:06:56Z |
format | Article |
id | doaj.art-8790e15f321c46b5979ca700d4639cac |
institution | Directory Open Access Journal |
issn | 2096-3041 2662-6802 |
language | English |
last_indexed | 2024-03-12T04:06:56Z |
publishDate | 2021-12-01 |
publisher | SpringerOpen |
record_format | Article |
series | Built Heritage |
spelling | doaj.art-8790e15f321c46b5979ca700d4639cac2023-09-03T11:16:54ZengSpringerOpenBuilt Heritage2096-30412662-68022021-12-015111310.1186/s43238-021-00045-7Digital topics on cultural heritage investigated: how can data-driven and data-guided methods support to identify current topics and trends in digital heritage?Sander Münster0Ronja Utescher1Selda Ulutas Aydogan2Digital Humanities, Friedrich Schiller University JenaDigital Humanities, Friedrich Schiller University JenaDigital Humanities, Friedrich Schiller University JenaAbstract In research and policies, the identification of trends as well as emerging topics and topics in decline is an important source of information for both academic and innovation management. Since at present policy analysis mostly employs qualitative research methods, the following article presents and assesses different approaches – trend analysis based on questionnaires, quantitative bibliometric surveys, the use of computer-linguistic approaches and machine learning and qualitative investigations. Against this backdrop, this article examines digital applications in cultural heritage and, in particular, built heritage via various investigative frameworks to identify topics of relevance and trendlines, mainly for European Union (EU)-based research and policies. Furthermore, this article exemplifies and assesses the specific opportunities and limitations of the different methodical approaches against the backdrop of data-driven vs. data-guided analytical frameworks. As its major findings, our study shows that both research and policies related to digital applications for cultural heritage are mainly driven by the availability of new technologies. Since policies focus on meta-topics such as digitisation, openness or automation, the research descriptors are more granular. In general, data-driven approaches are promising for identifying topics and trendlines and even predicting the development of near future trends. Conversely, qualitative approaches are able to answer “why” questions with regard to whether topics are emerging due to disruptive innovations or due to new terminologies or whether topics are becoming obsolete because they are common knowledge, as is the case for the term “internet”.https://doi.org/10.1186/s43238-021-00045-7Digital heritageResearch topicsPoliciesSurveyBibliometricsNLP |
spellingShingle | Sander Münster Ronja Utescher Selda Ulutas Aydogan Digital topics on cultural heritage investigated: how can data-driven and data-guided methods support to identify current topics and trends in digital heritage? Built Heritage Digital heritage Research topics Policies Survey Bibliometrics NLP |
title | Digital topics on cultural heritage investigated: how can data-driven and data-guided methods support to identify current topics and trends in digital heritage? |
title_full | Digital topics on cultural heritage investigated: how can data-driven and data-guided methods support to identify current topics and trends in digital heritage? |
title_fullStr | Digital topics on cultural heritage investigated: how can data-driven and data-guided methods support to identify current topics and trends in digital heritage? |
title_full_unstemmed | Digital topics on cultural heritage investigated: how can data-driven and data-guided methods support to identify current topics and trends in digital heritage? |
title_short | Digital topics on cultural heritage investigated: how can data-driven and data-guided methods support to identify current topics and trends in digital heritage? |
title_sort | digital topics on cultural heritage investigated how can data driven and data guided methods support to identify current topics and trends in digital heritage |
topic | Digital heritage Research topics Policies Survey Bibliometrics NLP |
url | https://doi.org/10.1186/s43238-021-00045-7 |
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