Welcome to the LibGuide for China Data!
Data is useful when you just need a few numbers to support an argument. This guide provides information on best practice in seeking research data on China.The material in this page is provided for XJTLU researchers and students as a reference.
Data & Research Data
"Related items of (chiefly numerical) information considered collectively, typically obtained by scientific work and used for reference, analysis, or calculation."
Data are distinct pieces of information, usually formatted in a special way. Strictly speaking, data is the plural of datum, a single piece of information. In practice, however, people use data as both the singular and plural form of the word. In database management systems, data files are the files that store the database information.
Research data is data that is collected, observed, or created, for purposes of analysis to produce original research results. The word “data” is used throughout this site to refer to research data.
Type of Data
Research data can be generated for different purposes and through different processes, and can be divided into different categories. Each category may require a different type of data management plan.
Observational: data captured in real-time, usually irreplaceable. For example, sensor data, survey data, sample data, neurological images.
Experimental: data from lab equipment, often reproducible, but can be expensive. For example, gene sequences, chromatograms, toroid magnetic field data.
Simulation: data generated from test models where model and metadata are more important than output data. For example, climate models, economic models.
Derived or compiled: data is reproducible but expensive. For example, text and data mining, compiled database, 3D models.
Reference or canonical: a (static or organic) conglomeration or collection of smaller (peer-reviewed) datasets, most probably published and curated. For example, gene sequence databanks, chemical structures, or spatial data portals.
Research data are an important and expensive output of the scholarly research process, across all disciplines. They are an essential part of the evidence necessary to evaluate research results, and to reconstruct the events and processes leading to them. Their value increases as they are aggregated into collections and as they become more available for re-use to address new and challenging research questions. Without proper organization, this value is greatly diminished.