Data, Big data and Database Semantics (entry in ISKO Encyclopedia, 2018)

You might be interested in taking a look at this new entry in ISKO Encyclopedia of Knowledge Organisation: Data: with big data and database semanticsby Birger Hjørland

This paper seeks to define data and to relate this concept to other core concepts in → library and information science (LIS), including facts, information and documents.

Data is a much-used concept in many fields, including LIS, in particular in composite terms such as database, data archive, data mining, descriptive data, metadatalinked data and now big data. These terms are common terms of the field and need proper theoretical and terminological attention...


It is argued that data should be defined as information on properties of units of analysis. Epistemologically it is important to establish that what is considered data by somebody need not be data for somebody else. This article considers the nature of data and big data and the relation among data, information, knowledge and documents. It is common for all these concepts that they are about phenomena produced in specific contexts for specific purposes and may be represented in documents, including as representations in databases. One important aspect about big data is that they are often unintentional traces we leave during all kinds of activities. Their potential to inform somebody about something is therefore less direct as compared to data that have been produced intentionally as, for example, scientific databases.

Table of contents: 

1. Introduction 
2. Defining data: 
2.1 Epistemological issues; 
2.2 Data, facts, information and documents; 
2.3 Data and documents confused; 
2.4 Recorded data; 
2.5 Further definitions and conclusion 

3. Big data: 
3.1 Etymology; 
3.2 Defining big data; 
3.3 Big data in different contexts 

4. Big data and undiscovered public knowledge 

5. Towards a social epistemological understanding of data: 
5.1 The myth of empiricism; 
5.2 Standards; 
5.3 Database semantics 

6. Conclusion 


Data & Semantics : learn more :  

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