Historical Databases, Big and Small
Big Data is a relative term, and Small Data can be equally important. Not only the volume of data defines if data is 'Big', but three more Vs characterise the term: velocity (speed of data generation and processing), veracity (referring to data quality) and variety. Perhaps the most defini...
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| Format: | Article |
| Language: | English |
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International Institute of Social History
2021-03-01
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| Series: | Historical Life Course Studies |
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| Online Access: | https://openjournals.nl/index.php/hlcs/article/view/9562 |
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| author | Peter Doorn |
| author_facet | Peter Doorn |
| author_sort | Peter Doorn |
| collection | DOAJ |
| description | Big Data is a relative term, and Small Data can be equally important. Not only the volume of data defines if data is 'Big', but three more Vs characterise the term: velocity (speed of data generation and processing), veracity (referring to data quality) and variety. Perhaps the most defining is methodological: data becomes really big when new methods are needed to process and analyse it. In contrast, this paper demonstrates how even a tiny dataset can contribute to our understanding of the past, in this case of the historical geography of two provinces in Ottoman Greece in the 17th century. Graph analysis is used on a dataset of just 16 data pairs, illustrating the point that a close-up view of data complements the look from farther away at bigger data volumes. |
| format | Article |
| id | doaj-art-9b143faf99d44f4b92a793a9a99b626e |
| institution | Kabale University |
| issn | 2352-6343 |
| language | English |
| publishDate | 2021-03-01 |
| publisher | International Institute of Social History |
| record_format | Article |
| series | Historical Life Course Studies |
| spelling | doaj-art-9b143faf99d44f4b92a793a9a99b626e2025-02-02T07:57:42ZengInternational Institute of Social HistoryHistorical Life Course Studies2352-63432021-03-011010.51964/hlcs9562Historical Databases, Big and SmallPeter DoornBig Data is a relative term, and Small Data can be equally important. Not only the volume of data defines if data is 'Big', but three more Vs characterise the term: velocity (speed of data generation and processing), veracity (referring to data quality) and variety. Perhaps the most defining is methodological: data becomes really big when new methods are needed to process and analyse it. In contrast, this paper demonstrates how even a tiny dataset can contribute to our understanding of the past, in this case of the historical geography of two provinces in Ottoman Greece in the 17th century. Graph analysis is used on a dataset of just 16 data pairs, illustrating the point that a close-up view of data complements the look from farther away at bigger data volumes.https://openjournals.nl/index.php/hlcs/article/view/9562Big DataGreeceOttoman provincesGraph analysis |
| spellingShingle | Peter Doorn Historical Databases, Big and Small Historical Life Course Studies Big Data Greece Ottoman provinces Graph analysis |
| title | Historical Databases, Big and Small |
| title_full | Historical Databases, Big and Small |
| title_fullStr | Historical Databases, Big and Small |
| title_full_unstemmed | Historical Databases, Big and Small |
| title_short | Historical Databases, Big and Small |
| title_sort | historical databases big and small |
| topic | Big Data Greece Ottoman provinces Graph analysis |
| url | https://openjournals.nl/index.php/hlcs/article/view/9562 |
| work_keys_str_mv | AT peterdoorn historicaldatabasesbigandsmall |