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.
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In the last decade, organizations have re-engineered their business processes and started using standard software solutions. Integration of structured data in relational databases has improved documentation of business transactions and increased data quality. But almost 90% of the information cannot be integrated in relational data bases. This amount of ‘unstructured’ information is exploding within the Enterprise 2.0. The use of social media tools to enhance collaboration, creates corporate blogs, wikis, forums, and other types of unstructured information. Structured and unstructured information are records, meant and used as evidence for policies, decisions, products, actions and transactions. Most stakeholders are making increasing demands for the trustworthiness of records for accountability reasons. In this age of evolving social media use, organizational chains, inter-organizational data warehouses and cloud computing, it is crucial for the Enterprise 2.0. that its policies, decisions, products, actions and transactions can be reliably reconstructed in context. Digital Archiving is a necessity for the Enterprise 2.0.: the reconstruction of the past depends on records and their meta data. Blogs, wikis, forums, etc., used for collaboration within the business processes of the organization, need to be documented for reconstruction in the future. Digital Archiving is a combination of three mechanisms: enterprise records management, organizational memory and records auditing. These mechanisms ensure that a digitized organization as the Enterprise 2.0. has a documented understanding of its past. In that way, it improves organizational accountability.
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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.
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Archiving by Design betekent dat je de archieffunctie als een organisatiefunctie ontwerpt en systemen inzet die dat ontwerp realiseren. Centraal bepalen, regelen en organiseren hoe moet worden gearchiveerd en decentraal faciliteren met (misschien meerdere) systemen en (misschien meerdere) edepotvoorzieningen voor langetermijnbewaring. Waarom niet? Als een organisatie maar weet wat en hoe - en daar ook naar handelt.
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The development of the World Wide Web, the emergence of social media and Big Data have led to a rising amount of data. Information and Communication Technologies (ICTs) affect the environment in various ways. Their energyconsumption is growing exponentially, with and without the use of ‘green’ energy. Increasing environmental awareness has led to discussions on sustainable development. The data deluge makes it not only necessary to pay attention to the hard- and software dimensions 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 information, 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, methodically deleting data and records should reduce the consumption of electricity for data storage. As a consequence, 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 consumption for data storage (resulting in a cost reduction of 35 percent). Our research indicates that the Green Archiving Model is a viable model to reduce the amount of stored data and records and to curb electricity use for storage in organizations. This paper is the result of the first stage of a research project that is aimed at developing low power ICTs that will automatically appraise, select, preserve or permanently delete data based on their ‘value’. Such an ICT will automatically reduce storage capacity and reduce electricity consumption used for data storage. At the same time, data disposal will reduce overload caused by storing the same data in different formats, it will lower costs and it reduces the potential forliability.
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Information and Communication Technologies (ICTs) affect the environment in various ways. Their energy consumption is growing exponentially, with and without the use of ‘green’ energy. Increasing environmental awareness within information science has led to discussions on sustainable development. ‘Green Computing’ has been introduced: the study and practice of environmentally sus- tainable computing. This can be defined as ‘designing, manufacturing, using, and disposing of com- puters, servers, and associated subsystems - such as monitors, printers, storage devices, and net- working and communications systems - efficiently and effectively with minimal or no impact on the en- vironment’. Nevertheless, the data deluge makes it not only necessary to pay attention to the hard- and software dimensions of ICTs but also to the value of the data stored. We explore the possibilities to use information and archival science to reduce the amount of stored data. In reducing this amount of stored data, it’s possible to curb unnecessary power consumption. The objectives of this paper are to develop a model (and test its viablility) to [1] increase awareness in organizations for the environ- mental aspects of data storage, [2] reduce the amount of stored data, and [3] reduce power consump- tion for data storage. This model integrates the theories of Green Computing, Information Value Chain (IVC) and Archival Retention Levels (ARLs). We call this combination ‘Green Archiving’. Our explora- tory research was a combination of desk research, qualitative interviews with information technology and information management experts, a focus group, and two exploratory case studies. This paper is the result of the first stage of a research project that is aimed at developing low power ICTs that will automatically appraise, select, preserve or permanently delete data based on their value. Such an ICT will automatically reduce storage capacity and curb power consumption used for data storage. At the same time, data disposal will reduce overload caused by storing the same data in different for- mats, it will lower costs and it reduces the potential for liability.
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Geert-Jan van Bussel, bijzonder lector Digital Archiving & Compliance, sprak op dinsdag 16 oktober 2012 zijn lectorale rede uit in het Kohnstammzaal. Van Bussel sprak over de betrouwbaarheid van informatie en de manieren waarop ‘Digital Archiving’ en ‘Compliance’ de informatiestromen in organisaties besturen.
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Can you remember the last time the ground gave way beneath you? When you thought the ground was stable, but for some reason it wasn’t? Perhaps you encountered a pothole on the streets of Amsterdam, or you were renovating your house and broke through the floor. Perhaps there was a molehill in a park or garden. You probably had to hold on to something to steady yourself. Perhaps you even slipped or fell. While I sincerely hope that nobody here was hurt in the process, I would like you to keep that feeling in your mind when reading what follows. It is the central theme of the words that will follow. The ground beneath our feet today is not as stable as the streets of Amsterdam, your park around the corner or even a poorly renovated upstairs bedroom. This is because whatever devices we use and whatever pathways we choose, we all live in hybrid physical and digital social spaces (Kitchin and Dodge 2011). Digital social spaces can be social media platforms like Twitter or Facebook, but also chat apps like WhatsApp or Signal. Crucially, social spaces are increasingly hybrid, in which conversations take place across digital spaces (WhatsApp chat group) and physical spaces (meeting friends in a cafe) simultaneously. The ground beneath our feet is not made of concrete or stone or wood but of bits and bytes.
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Systematic literature review on digital transformation skills
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Background: Digital health is well-positioned in low and middle-income countries (LMICs) to revolutionize health care due, in part, to increasing mobile phone access and internet connectivity. This paper evaluates the underlying factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Objective: The objective of this study is to identify the current digital health projects and studies being carried out in Pakistan, as well as the key stakeholders involved in these initiatives. We aim to follow a mixed-methods strategy and to evaluate these projects and studies through a strengths, weaknesses, opportunities, and threats (SWOT) analysis to identify the internal and external factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Methods: This study aims to evaluate digital health projects carried out in the last 5 years in Pakistan with mixed methods. The qualitative and quantitative data obtained from field surveys were categorized according to the World Health Organization’s (WHO) recommended building blocks for health systems research, and the data were analyzed using a SWOT analysis strategy. Results: Of the digital health projects carried out in the last 5 years in Pakistan, 51 are studied. Of these projects, 46% (23/51) used technology for conducting research, 30% (15/51) used technology for implementation, and 12% (6/51) used technology for app development. The health domains targeted were general health (23/51, 46%), immunization (13/51, 26%), and diagnostics (5/51, 10%). Smartphones and devices were used in 55% (28/51) of the interventions, and 59% (30/51) of projects included plans for scaling up. Artificial intelligence (AI) or machine learning (ML) was used in 31% (16/51) of projects, and 74% (38/51) of interventions were being evaluated. The barriers faced by developers during the implementation phase included the populations’ inability to use the technology or mobile phones in 21% (11/51) of projects, costs in 16% (8/51) of projects, and privacy concerns in 12% (6/51) of projects.
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