How to Inspect and Measure Data Quality about Scientific Publications: Use Case of Wikipedia and CRIS Databases

Otmane Azeroual,Włodzimierz Lewoniewski

doi:10.3390/a13050107

Abstract

The quality assurance of publication data in collaborative knowledge bases and in current research information systems (CRIS) becomes more and more relevant by the use of freely available spatial information in different application scenarios. When integrating this data into CRIS, it is necessary to be able to recognize and assess their quality. Only then is it possible to compile a result from the available data that fulfills its purpose for the user, namely to deliver reliable data and information. This paper discussed the quality problems of source metadata in Wikipedia and CRIS. Based on real data from over 40 million Wikipedia articles in various languages, we performed preliminary quality analysis of the metadata of scientific publications using a data quality tool. So far, no data quality measurements have been programmed with Python to assess the quality of metadata from scientific publications in Wikipedia and CRIS. With this in mind, we programmed the methods and algorithms as code, but presented it in the form of pseudocode in this paper to measure the quality related to objective data quality dimensions such as completeness, correctness, consistency, and timeliness. This was prepared as a macro service so that the users can use the measurement results with the program code to make a statement about their scientific publications metadata so that the management can rely on high-quality data when making decisions.

Highlights

Information and communication technologies are not the only ones that play an important role in all aspects of modern society [1]
Incorrect research data only come to light in the current research information systems (CRIS)
We can achieve a degree from 0% to 100%

Summary

Introduction

Information and communication technologies are not the only ones that play an important role in all aspects of modern society [1]. The processing of electronic research data by the institutions. Research data are an essential part of the operational processes of scientific organizations. Research data at the institution level has become accessible to researchers in many countries [2]. There is an explosion of large data—various forms of establishment-level information that are typically created for business purposes [2]. Incorrect research data only come to light in the current research information systems (CRIS) (The nomenclature for research information systems is more or less not standardized, including RIMS (Research Information Management System), RIS (Research Information System), RNS

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