This project explores and develops methods for open archiving of socalled "new naturals". A number of tools and templates were created to facilitate collaborative, global - but context-aware and localized - documenting and archiving of "new naturals":
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Within eGovernment, trust in electronic stored information (ESI) is a necessity. In the last decades, most organizations underwent substantial reorganization. The integration of structured data in relational databases has improved documentation of business transactions and increased data quality. That integration has improved accountability as well. Almost 90% of the information that organizations manage is unstructured (e.g., e-mail, documents, multimedia files, etc.). Those files cannot be integrated into a traditional database in an easy way. Like structured data, unstructured ESI in organizations can be denoted as records, when it is meant to be (and used as) evidence for organizational policies, decisions, products, actions and transactions. Stakeholders in eGovernment, like citizens, governments and courts, are making increasing demands for the trustworthiness of this ESI for privacy, evidential and transparency reasons. A theoretical analysis of literature of information, organization and archival science illustrates that for delivering evidence, reconstruction of the past is essential, even in this age of information overload. We want to analyse how Digital Archiving and eDiscovery contribute to the realization of trusted ESI, to the reconstruction of the past and to delivering evidence. Digital Archiving ensures (by implementing and managing the ‘information value chain’) that: [1] ESI can be trusted, that it meets the necessary three dimensions of information: quality, context and relevance, and that [2] trusted ESI meets the remaining fourth dimension of information: survival, so that it is preserved for as long as is necessary (even indefinitely) to comply to privacy, accountability and transparency regulations. EDiscovery is any process (or series of processes) in which (trusted) ESI is sought, located, secured and searched with the intent of using it as evidence in a civil or criminal legal case. A difference between the two mechanisms is that Digital Archiving is implemented ex ante and eDiscovery ex post legal proceedings. The combination of both mechanisms ensures that organizations have a documented understanding of [1] the processing of policies, decisions, products, actions and transactions within (inter-) organizational processes; [2] the way organizations account for those policies, decisions, products, actions and transactions within their business processes; and [3] the reconstruction of policies, decisions, products, actions and transactions from business processes over time. This understanding is extremely important for the realization of eGovernment, for which reconstruction of the past is an essential functionality. Both mechanisms are illustrated with references to practical examples.
The development of the World Wide Web, the emergence of social media and Big Data have led to a rising amount of data. Infor¬mation and Communication Technol¬ogies (ICTs) affect the environment in various ways. Their energy consumption is growing exponentially, with and without the use of ‘green’ energy. Increasing envi¬ronmental aware¬ness has led to discussions on sustainable development. The data deluge makes it not only necessary to pay attention to the hard‑ and software di¬mensions of ICTs but also to the ‘value’ of the data stored. In this paper, we study the possibility to methodically reduce the amount of stored data and records in organizations based on the ‘value’ of informa¬tion, using the Green Archiving Model we have developed. Reducing the amount of data and records in organizations helps in allowing organizations to fight the data deluge and to realize the objectives of both Digital Archiving and Green IT. At the same time, methodi¬cally deleting data and records should reduce the con¬sumption of electricity for data storage. As a consequencs, the organizational cost for electricity use should be reduced. Our research showed that the model can be used to reduce [1] the amount of data (45 percent, using Archival Retention Levels and Retention Schedules) and [2] the electricity con¬sumption for data storage (resulting in a cost reduction of 35 percent). Our research indicates that the Green Ar¬chiving Model is a viable model to reduce the amount of stored data and records and to curb electricity use for storage in organi¬zations. This paper is the result of the first stage of a research project that is aimed at devel¬oping low power ICTs that will automa¬tically appraise, select, preserve or permanently delete data based on their ‘value’. Such an ICT will automatically reduce storage capacity and reduce electricity con¬sumption used for data storage. At the same time, data dispos¬al will reduce overload caused by storing the sa¬me data in different for¬mats, it will lower costs and it reduces the po¬tential for liability.
