Data collection or data gathering is the process of gathering and

measuring Measurement is the quantification of attributes of an object or event, which can be used to compare with other objects or events. In other words, measurement is a process of determining how large or small a physical quantity is as compared ...

information Information is an abstract concept that refers to that which has the power to inform. At the most fundamental level information pertains to the interpretation of that which may be sensed. Any natural process that is not completely random, ...

on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes.

Data In the pursuit of knowledge, data (; ) is a collection of discrete values that convey information, describing quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpret ...

collection is a

research Research is "creative and systematic work undertaken to increase the stock of knowledge". It involves the collection, organization and analysis of evidence to increase understanding of a topic, characterized by a particular attentiveness ...

component in all study fields, including

physical Physical may refer to: * Physical examination, a regular overall check-up with a doctor * ''Physical'' (Olivia Newton-John album), 1981 ** "Physical" (Olivia Newton-John song) * ''Physical'' (Gabe Gurnsey album) * "Physical" (Alcazar song) (2004) * ...

and

social science Social science is one of the branches of science, devoted to the study of societies and the relationships among individuals within those societies. The term was formerly used to refer to the field of sociology, the original "science of s ...

humanities Humanities are academic disciplines that study aspects of human society and culture. In the Renaissance, the term contrasted with divinity and referred to what is now called classics, the main area of secular study in universities at t ...

, and

business Business is the practice of making one's living or making money by producing or buying and selling products (such as goods and services). It is also "any activity or enterprise entered into for profit." Having a business name does not separ ...

. While methods vary by discipline, the emphasis on ensuring accurate and honest collection remains the same. The goal for all data collection is to capture quality evidence that allows analysis to lead to the formulation of convincing and credible answers to the questions that have been posed. Data collection and validation consists of four steps when it involves taking a census and seven steps when it involves sampling. Regardless of the field of or preference for defining data (

quantitative Quantitative may refer to: * Quantitative research, scientific investigation of quantitative properties * Quantitative analysis (disambiguation) * Quantitative verse, a metrical system in poetry * Statistics, also known as quantitative analysis ...

or qualitative), accurate data collection is essential to maintain research integrity. The selection of appropriate data collection instruments (existing, modified, or newly developed) and delineated instructions for their correct use reduce the likelihood of

errors An error (from the Latin ''error'', meaning "wandering") is an action which is inaccurate or incorrect. In some usages, an error is synonymous with a mistake. The etymology derives from the Latin term 'errare', meaning 'to stray'. In statistics ...

. A formal data collection process is necessary as it ensures that the data gathered are both defined and accurate. This way, subsequent decisions based on arguments embodied in the findings are made using valid data. The process provides both a baseline from which to measure and in certain cases an indication of what to improve. There are 5 common data collection methods: # closed-ended surveys and quizzes, # open-ended surveys and questionnaires, #1-on-1 interviews, # focus groups, and #direct observation.

Data management platform

'' Data management platform'' (DMP) is a centralized storage and analytical system for data. Mainly used by marketers, DMPs exist to compile and transform large amounts of data into discernible information. Marketers may want to receive and utilize first, second and third-party data. DMPs enable this, because they are the aggregate system of DSPs (demand side platform) and SSPs (supply side platform). When it comes to advertising, DMPs are integral for optimizing and guiding marketers in future campaigns. This system and their effectiveness is proof that categorized, analyzed, and compiled data is far more useful than raw data.

Data integrity issues

The main reason for maintaining data integrity is to support the observation of errors in the data collection process. Those errors may be made intentionally (deliberate falsification) or non-intentionally (

random In common usage, randomness is the apparent or actual lack of pattern or predictability in events. A random sequence of events, symbols or steps often has no order and does not follow an intelligible pattern or combination. Individual ran ...

systematic errors Observational error (or measurement error) is the difference between a measured value of a quantity and its true value.Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. In statistics, an error is not necessarily a " mista ...

). There are two approaches that may protect data integrity and secure scientific validity of study results invented by Craddick, Crawford, Rhodes, Redican, Rukenbrod and Laws in 2003: * Quality assurance – all actions carried out before data collection * Quality control – all actions carried out during and after data collection

Quality assurance

Its main focus is prevention which is primarily a cost-effective activity to protect the integrity of data collection. Standardization of protocol best demonstrates this cost-effective activity, which is developed in a comprehensive and detailed procedures manual for data collection. The risk of failing to identify problems and errors in the research process is evidently caused by poorly written guidelines. Listed are several examples of such failures: * Uncertainty of timing, methods and identification of the responsible person * Partial listing of items needed to be collected * Vague description of data collection instruments instead of rigorous step-by-step instructions on administering tests * Failure to recognize exact content and strategies for training and retraining staff members responsible for data collection * Unclear instructions for using, making adjustments to, and calibrating data collection equipment * No predetermined mechanism to document changes in procedures that occur during the investigation

Quality control

Since quality control actions occur during or after the data collection all the details are carefully documented. There is a necessity for a clearly defined communication structure as a precondition for establishing monitoring systems. Uncertainty about the flow of information is not recommended as a poorly organized communication structure leads to lax monitoring and can also limit the opportunities for detecting errors. Quality control is also responsible for the identification of actions necessary for correcting faulty data collection practices and also minimizing such future occurrences. A team is more likely to not realize the necessity to perform these actions if their procedures are written vaguely and are not based on feedback or education. Data collection problems that necessitate prompt action: * Systematic errors * Violation of protocol *

Fraud In law, fraud is intentional deception to secure unfair or unlawful gain, or to deprive a victim of a legal right. Fraud can violate civil law (e.g., a fraud victim may sue the fraud perpetrator to avoid the fraud or recover monetary compen ...

or scientific misconduct * Errors in individual data items * Individual staff or site performance problems

References

External links