Data processing is the collection and transformation of raw data into meaningful, usable information through operations such as organizing, validating, analyzing, summarizing, and storing. It encompasses the full pipeline by which inputs are captured and converted into outputs that support decision-making, ranging f…
Data processing is the collection and transformation of raw data into meaningful, usable information through operations such as organizing, validating, analyzing, summarizing, and storing. It encompasses the full pipeline by which inputs are captured and converted into outputs that support decision-making, ranging from simple record handling to large-scale computational analysis. In the context of big data, data processing addresses the challenges of volume, velocity, and variety, requiring databases, distributed computing, and algorithmic methods to extract patterns and insights from datasets too large or complex for conventional handling. Effective processing underlies applications across science, medicine, agriculture, engineering, and business, where it enables prediction, classification, and the detection of trends that would otherwise remain hidden. Research in this journal reflects these themes, including work on databases and computing for Big Data Research, automated detection methods applied to agricultural imaging, and computational analysis of high-throughput measurement data such as mass spectrometry datasets used for biomarker identification. These examples illustrate how data processing techniques are deployed to manage and interpret diverse, high-dimensional information. This page gathers peer-reviewed, open-access research relevant to data processing, computing infrastructure, and analytical methods for extracting value from large and complex datasets.
12 peer-reviewed articles, ranked by relevance. Each links to its DOI.
The 12 articles above have been cited 134 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
A sample of recent works citing this journal's research on Data Processing, linking to each citing work.