Data/
Dataset

Chaya Liebeskind, Jerusalem College of Technology, Israel
liebchaya@gmail.com

Data encompasses individual pieces of information, such as factual details and numerical values, which are gathered, analysed, and interpreted to convey meaning or comprehension. It can be expressed in different formats, such as numbers, text, images, sounds, symbols, or any other measurable or descriptive value.

A dataset is a systematically compiled set of associated data that is generally acquired for a particular intent, such as research, machine learning model training, or analysis. By organising data elements in a predetermined format, such as matrices, tables, or records, dataset facilitates identification, interpretation, and investigation of patterns and connections with greater efficiency. Datasets frequently comprise supplementary information, known as metadata, which furnishes contextual details regarding the sources of the data, methods of collection, definitions of variables, and limitations on usage.

Datasets are crucial in multiple domains, since they form the basis for empirical investigations, algorithmic advancements, and decision-making procedures. They exist in various forms and quantities, ranging from modest, carefully selected collections to extensive reservoirs of information obtained from multiple sources. Aside from conventional organised datasets that conform to a predetermined schema, unstructured datasets including text documents, pictures, and multimedia files are becoming more widespread. The presence of extensive datasets, commonly known as ‘big data’, offers both advantages and difficulties, as academics and professionals strive to derive significant observations while confronting concerns regarding data accuracy, privacy, and scalability. Furthermore, the continuous progress in data collection technologies, including sensors, IoT devices, and web scraping techniques, consistently broaden the range and complexity of accessible information, fostering innovation and influencing the field of data-driven decision-making.

Keywords: data, information, metadata

References:
Davis, L. S., & Abdurazokzoda, F. (2016). Language, culture and institutions: Evidence from a new linguistic dataset. Journal of Comparative Economics, 44(3), 541-561.‏
Gao, L., Biderman, S., Black, S., Golding, L., Hoppe, T., Foster, C., ... & Leahy, C. (2020). The pile: An 800gb dataset of diverse text for language modeling. arXiv preprint arXiv:2101.00027.‏
Zins, C. (2007). Conceptual approaches for defining data, information, and knowledge. Journal of the American society for information science and technology, 58(4), 479-493.‏