Case Study on Requirements Engineering in Information Mining Project: Metallurgical Enterprise

Sep 11, 2026

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Information Mining projects transform organizational data into actionable knowledge for decision-making, requiring meticulous, due diligence requirements specification that remains consistent and traceable across the entire project. Existing Information Mining methodologies often overlook stakeholder and customer requirements management, limiting practical engineering of business knowledge. The paper proposes a solution model for Information Mining project management, then applies it through a case study in a metallurgical enterprise context.

LanguageEnglish

CategoryGeneral

FormatPDF

Pages9

Reading Time3 min

AccessFree to download

Abstract

1. Introduction

2. Problem Description

3. Solution Proposal

4. Case Study

5. Conclusions and Future Work

Case Study on Requirements Engineering in Information Mining Project: Metallurgical Enterprise Pollo-Cattaneo, M. F. PhD Program on Computer Science. Computer Science School. National University of La Plata. Information System Methodologies Research Group. Technological National University. Buenos Aires, Argentina. [flo.pollo@gmail.com](flo.pollo@gmail.com) Pesado, P. School of Computer Science. National University of La Plata. Buenos Aires, Argentina. [ppesado@lidi.info](ppesado@lidi.info). [unlp.edu.ar](unlp.edu.ar) Britos, P. Information Mining Research Group. National. Lab ID + i in Visualization, Computer Graphics and Creative Code. University of Rio Negro at El Bolsón, Río Negro, Argentina. [paobritos@gmail.com](paobritos@gmail.com) García-Martínez, R. Information Systems Research Group. National University of Lanus, Buenos Aires, Argentina. [rgarcia@unla.edu.ar](rgarcia@unla.edu.ar) ABSTRACT There can be no debate that Information Mining Projects cause processing tools to arise with the sole purpose of converting available organization data into useful knowledge on account of decision-making. Considering the aforementioned, this type of projects demands due diligence in the requirement specification process, as the latter needs to be thorough and traceable throughout the entire project, and therefore, process associated with requirements engineering are not to be reused in any future projects among the like. Similarly, latest methodologies within the field of Information Mining fail to take practices associated to stakeholders and costumers’ requirements management into account. With this aim in mind, a solution model to the Information Mining Project Management necessities is proposed. CCS Concepts • Computing methodologies➝Modeling and simulation • Information systems➝Information systems applications Keywords Information Mining, Requirement Management, Process, Methodology, Requirement Engineering. 1. INTRODUCTION The basis of Information Mining is centered on data processing for nontrivial knowledge collection, an organizational task in which analysis and synthesis tools are indispensable [1] . The aforementioned knowledge being unknown, it can be further exploited by organizations on account of the decision-making process [2] . Information Systems specialists claim data relationships, fluctuations and dependencies to be the core of the process, rather than the data itself [3]; whether these relationships reflect the reality and are then regarded as valid for doing so, the fact that they revolutionize the criteria for decision-making cannot be dismissed [4] . Taking the CRISP-DM [5], P3TQ [6], and SEMMA [7] standout Information Mining Methodologies as examples, it can be seen that these all fail to take into account aspects of those related to both project management and the organizational context where the project is taken on, thus failing to engineer the key concepts in business knowledge [8] . All things considered, this paper employs a proposed model which contributes to the development of a thorough requirements management in the context of an Information Mining project. In order to do so, the detected problem is first described (Section 2), and then a solution proposal is suggested (Section 3) . Afterwards, a case study in which the proposed process is implemented is then shown (Section 4), and lastly, conclusions and future work lines arepresented (Section 5) . 2. PROBLEM DESCRIPTION What a proper Information Mining project needs is a due consistent and traceable the project throughout - requirements specification, which should, at first, allow for an orderly project management, and also leave out any possible requirements misunderstandings [9]. Nonetheless, there is one glaring difference between this type of projects and traditional software projects, asan Information Mining Project demands no software product construction, but none other than the transformat

FAQs

Why are due diligence and traceability crucial in Information Mining project requirements specification?

Information Mining projects must have requirements that are consistent and traceable throughout the entire specification process to support orderly project management and reduce misunderstandings.

What limitation do many Information Mining methodologies have regarding requirements engineering?

They often fail to consider stakeholder and customer requirements management, so they do not engineer key concepts in business knowledge effectively.

How does the proposed work address the gap between Information Mining and traditional software requirements?

It recognizes that Information Mining demands no software product construction, but rather a process that transforms data into knowledge, so requirements do not follow traditional software engineering restrictions and functionalities.

Sep 11, 2026

Upload by Finn