Digital curation and costs

Abstract

The production of large volumes of scientific information, considering its cost, requires approaches that ensure its maintenance, reuse and recovery. These concerns prompted the emergence of digital curation. We intend to discuss the relevant thinking concerning the costs of digital curation. This means addressing the definition of the concept and the issue of costs, based on the studies related to cost models. A literature review was conducted using B-On and RCAAP as research sources, exploring the perceptions of the authors regarding the digital curation and its costs. The views expressed were organized around a scheme based on the Digital Curation Centre (DCC) lifecycle and the reference model Open Archival Information System (OAIS). It is proposed a systematization of digital curation issues bridging the DCC life cycle view of the digital object curation to the OAIS reference model approach, using a cross view seized by cost models and plan/data management policies.

DaLiF: a data lifecycle framework for data-driven governments

“…We assign a "mandatory" category to phase that has > 70% of appearance in the data lifecycles, and in other cases, we assigned it "optional" category as shown in Table 2. Additionally, we provide detailed information about the data lifecycles and their [15,53,58,134,143], receive [17], acquisition [13,117], retrieve [115,121], produce [140], acquire [55,63,90,97,147], capture [84,94,126,130,135,148], generation [26,56,95,96,[118][119][120], create [47, 109-111, 116, 124, 149] Collection P3 Integration [17,26,109,124,126,129,130,146,148,153,155], integrate [15,28,116,140,156], aggregate…”

“…Share/Publish P9 Use [15,26,66,90,90,111,116,118,134,135,142], consumption [92] feedback [93] using [53], usage [10,48,119,133,143,146,148,153], Reuse [28,61,84,88,107], exploit [85,110], consume [114], application [130], use and re(use) [13,49,147], feedback [52,140], review [48,141] Use [58,116], destroy [111,143], Delete [13,66,108,124,148], dispose [51,113],termination [49]…”

“…We noticed in the literature that the storage phase is considered in all data lifecycles models. There is a demand for stable and usually web-accessible storage [90,144,147]. Data Lakes ingest raw data in its original format from various data sources, meet their role as storage repositories, and allow users to query and explore them to extract knowledge [167].…”

“…• If relevant, ask permission from citizens and businesses to store data of their property [66]. • Store data in an appropriate location (in-house data center or private cloud environment) in a secure, scalable, accessible, and reliable manner [65,90,147]. • Compliance with industry standards, a) to store GBD along with improved data structures, appropriate cloud data security, and backing fault tolerance; and b) to improve data storage systems performance in terms of capacity and speed [65,75,142,166].…”

“…Access The data access phase focuses on ways of communication between the data provider and data consumer in the big data ecosystem [60]. Through this phase, we decide and document which user [60,147] or re-user [90,147] is accessing which data and with what mechanisms [58]. Public sector organizations offer multiple channels for data access [94].…”