Tell Data from Meta
Tracing the Origins of Big Data, Bibliometrics, and the Opac
Bibliographic Data
| ID | 4926889 |
|---|---|
| Authors | Markus Krajewski (0000-0002-8342-7389, Max Planck Society, corresponding author) |
| Year | 2017 |
| Volume | 32 |
| Issue | 1 |
| Pages | 224-240 |
| Publication date | 2017-09-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Osiris (JOURNAL) |
| Journal identifiers | ISSN: 0369-7827 • E-ISSN: 1933-8287 |
| Publisher | University of Chicago Press (PUBLISHER • US) |
| DOI | 10.1086/694228 |
| OpenAlex | W2766957959 |
| Language | EN |
| Citations received | 2 |
| References cited | 7 |
This essay discusses “Big Data” as a historical phenomenon with a long trajectory, dating back to the ancient library of Alexandria and its methods to counter information overload. The essay looks at different situations in which the proliferation of data posed problems and focuses on the development of systems and techniques—for example, bibliometrics—to cope with this abundance. After a brief inquiry into the origins of Big Data as a phenomenon, I will explore a distinction that is necessary to grasp the concept of Big Data, and which proves imperative in order to cope with the consequences of information overload. The distinction between data and metadata will be discussed and developed by dint of the history of the electronic library catalog called OPAC, which fuses two strands of Big Data: quantification and automatization
Bibliometrics · Data science · Library science · Tracing · Advanced Data Storage Technologies · Computability, Logic, AI Algorithms · Computer Science · History · History of Computing Technologies
| Unique citing works | 2 |
|---|---|
| Citations per year | 0.29 |
| Citation span | 2019 - 2026 (8) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |