In 2017, I introduced a new theoretical framework in Archival Science, that of the ‘Archive–as–Is’. This framework proposes a theoretical foundation for Enterprise Information Management (EIM) in World 2.0, the virtual, interactive, and hyper connected platform that is developing around us. This framework should allow EIM to end the existing ‘information chaos’, to computerize information management, to improve the organizational ability to reach business objectives, and to define business strategies. The concepts of records and archives are crucial for those endeavours. The framework of the ‘Archive–as–Is’ is an organization–oriented archival theory, consisting of five components, namely: [1] four dimensions of information, [2] two archival principles, [3] five requirements of information accessibility, [4] the information value chain; and [5] organizational behaviour. In this paper, the subject of research is component 5 of the framework: organizational behaviour. Behaviour of employees (including archivists) is one of the most complicated aspects within organizations when creating, processing, managing, and preserving information, records, and archives. There is an almost universal ‘sound of silence’ in scholarly literature from archival and information studies although this subject and its effects on information management are studied extensively in many other disciplines, like psychology, sociology, anthropology, and organization science. In this paper, I want to study how and why employees behave as they do when they are working with records and archives and how EIM is influenced by this behaviour.
From the article: "Abstract Maintenance processes of Dutch housing associations are often still organized in a traditional manner. Contracts are based on lowest price instead of ‘best quality for lowest price’ considering users’ demands. Dutch housing associations acknowledge the need to improve their maintenance processes in order to lower maintenance cost, but are not sure how. In this research, this problem is addressed by investigating different supply chain partnering principles and the role of information management. The main question is “How can the organisation of maintenance processes of Dutch housing associations, in different supply chain partnering principles and the related information management, be improved?” The answer is sought through case study research."
Presented at Conference: IPMA World Conference 2014, At Rotterdam, The Netherlands, Volume: 28 A taxonomy is used for classifying things in general. For the purpose of this paper it is a systematic classification of competences into hierarchical groups where each sublevel constitutes a breakdown of the higher level. Although a vast amount of research has been done in project management competences, there is no standard set of project management competences used (Nijhuis, 2012). Important reasons for constructing a taxonomy for project management competences are found in comparing previous research and in identifying key fields for project management education in higher education. First a definition of competence is given, secondly the rationale of this research is given by discussing recent research. Several different published taxonomies of competences are reviewed. Finally a proposed taxonomy for project management competences is presented.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
In dit project ontwikkelen we Herstelcirkel ++, een gezondheidscoöperatie voor mensen met (risico op) leefstijlgerelateerde aandoeningen (o.a. diabetes). Coöperatie definiëren wij open als een (maatschappelijke) onderneming of autonome organisatie waarbij de deelnemers zeggenschap hebben over hoe zij voorzien in hun behoeften door het realiseren of beheren van voorzieningen en/of diensten. Deze ontwikkeling beantwoordt de wens van mensen met leefstijlaandoeningen (meer regie over de eigen gezondheid) en de door professionals gevoelde noodzaak om de eerstelijnszorg toegankelijk te houden. Het uitgangspunt is dat zorg en gezondheidsbevordering zoveel mogelijk rond, door en voor mensen met vergelijkbare wensen georganiseerd kan worden, in de eigen omgeving zodat de stap naar formele zorg minder nodig is. Complementair aan formele zorg en duurzaam verankerd in een wijklandschap van gezondheidsbevordering. Ondanks Nederlandse burgerinitiatieven rond zorg en gezondheid ontstaan coöperatieve vormen van zelfhulp niet altijd en overal, vooral niet in stadswijken (met achterstandsproblematiek). Hoe kunnen professionals die in de wijk actief zijn rond zorg, gezondheid en welzijn en MKB-bedrijven die zoeken naar innovatieve dienstverlening m.b.t. voeding, beweging en coaching samen met bewoners meer coöperatieve samenwerking bewerkstelligen ten behoeve van vitaliteit? Centraal in dit project staat de doorontwikkeling van Herstelcirkel in de wijk (HCIW) een sociale innovatie die diabetes-zelfmanagementeducatie en zelfhulp combineert door groepen mensen onder begeleiding van coaching aan leefstijlverandering te laten werken. Ondanks veelbelovende resultaten na het eenjarige traject, blijkt voor het merendeel het effect niet duurzaam. Uitgangspunten project: Co-designaanpak die professionals leert kennismaken met ontwerpgerichte methoden om met en voor bewoners passende dienstverlening in de wijk te ontwikkelen die coöperatieve zelfhulp faciliteren. Versterken van positieve krachten van bewoners en wijken (‘assets’) als elementen van de sociale en fysieke leefomgeving die deelnemers in staat stellen gezondheid te bevorderen. Ontwikkeling van een coöperatie, inclusief organisatorische aspecten: samenwerking met gezondheids- en welzijnsprofessionals en duurzame verankering in de wijk.
