Value-Based File Retention

Abstract

Several file retention policy methods propose that a file retention policy should be based on file value. Though such a retention policy might increase the value of accessible files, the method to arrive at such a policy is underresearched. This article discusses how one can arrive at a method for developing file retention policies based on the use values of files. The method's applicability is initially assessed through a case study at Capgemini, Netherlands. In the case study, we hypothesize that one can develop a file retention policy by testing causal relations between file attributes (as used by file retention methods) and the use value of files. Unfortunately, most file attributes used by file retention methods have a weak correlation with file value, resulting in the conclusion that these methods do not well select out high-and low-value files. This would imply the ineffectiveness of the used attributes in our study or errors in our conceptualization of file value. We continue with the last possibility and develop indicators for file utility (with low utility being waste). With this approach we were able to detect waste files, in a sample of files, with an accuracy of 80%. We therefore not only suggest further research in information waste detection as part of a file retention policy, but also to further explore other file attributes that could better predict file value and file utility. ACM Reference Format:Wijnhoven, F., Amrit, C., and Dietz, P. 2014. Value-based file retention: File attributes as file value and information waste indicators.

New Trends in Intellectual Capital Disclosures of Higher Degree Institutions in Indonesia

“…This paper focuses the variables relationship namely, Autonomy, Competitiveness, Age, Size as the determinant factors toward Web-based intellectual capital disclosure. Because the model uses more than two independent variables, thus this study utilize a multivariate analysis called as the multivariate regression model (Wijnhoven et al, 2014). Based on the theoretical model, the following is regression models.…”

“…Where Web-based ICD is the global intellectual capital disclosure index of university; β0 is the constant; β1-β4 is the coefficient of the determinants variables (Autonomy, Competitiveness, Age, and Size); ε i is the error or disturbance terms of university. According to Wijnhoven et al (2014), multivariate regression model can be tested by using Warp PLS, therefore Warp PLS will be utilised in this paper.…”

Challenges in Value-Driven Data Governance

“…The author here infers the value of information based on a number of usage statistics that include usage count, usage time, the source of usage, and the purpose of the usage. Wijnhoven et al extended Chens usage-based data valuation approach with a utility-based estimation based on file metadata [23]. Through case studies in a consulting practice, they found that the frequency of use and the grade of user accessing the file were the most important predictors of value.…”

“…Since data governance and management efforts and investments are on the rise, it is becoming increasingly relevant to identify the economic value of data and the return on investment. Data value has been used as a basis for organisational decision making on quality [11], but also as a part of automated control systems for data lifecycles [8] and file retention [23]. Failing to value data will result in a number of consequences such as retaining information that has little to no value, reduction in data usage, and leaving data investments vulnerable to budget cuts [16].…”

Exploiting user activeness for data retention in HPC systems

“…On the other hand, as the upgrade process of an HPC storage system usually takes a vast amount of investment, time and e ort [7,15,34,47], the total capacity of the scratch space tends to remain xed for a considerably long time after the deployment of a system. Additionally, HPC applications constantly generate a tremendous amount of data [1,2,9,14,[21][22][23]35], making it necessary to manage storage resource e ectively [11,13,18,19,38,48] with, in particular, "data retention" -a process of retaining useful les and purging unimportant les to improve the utilization of storage space.…”