De meest gebruikte opbouw in business intelligence, predictive analitics en analytics modellen is de moeilijkheidsgraad: 1) descriptive, 2) diagnostic, 3) predictive en 4) prescriptive. Deze schaal vertelt iets over de volwassenheid van het gebruik van data door de organisatie. Een model dat niet op zichzelf staat en een achterliggende methode kent is de data driehoek van EDM (Figuur 1), welke in dit artikel zal worden toegelicht.
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Background: Successful implementation of multifactorial fall prevention interventions (FPIs) is essential to reduce increasing fall rates in communitydwelling older adults. However, implementation often fails due to the complex context of the community involving multiple stakeholders within and across settings, sectors, and organizations. As there is a need for a better understanding of the occurring context-related challenges, the current scoping review purposes to identify what contextual determinants (i.e., barriers and facilitators) influence the implementation of FPIs in the community. Methods: A scoping reviewwas performed using the Arksey andO’Malley framework. First, electronic databases (Pubmed, CINAHL, SPORTDiscus, PsycINFO) were searched. Studies that identified contextual determinants that influence the implementation of FPIs in the community were included. Second, to both validate the findings from the literature and identify complementary determinants, health and social care professionals were consulted during consensus meetings (CMs) in four districts in the region of Utrecht, the Netherlands. Data were analyzed following a directed qualitative content analysis approach, according to the 39 constructs of the Consolidated Framework for Implementation Research. Results: Fourteen relevant studies were included and 35 health and social care professionals (such as general practitioners, practice nurses, and physical therapists) were consulted during four CMs. Directed qualitative content analysis of the included studies yielded determinants within 35 unique constructs operating as barriers and/or facilitators. The majority of the constructs (n = 21) were identified in both the studies and CMs, such as “networks and communications”, “formally appointed internal implementation leaders”, “available resources” and “patient needs and resources”. The other constructs (n = 14) were identified only in the . Discussion: Findings in this review show that awide array of contextual determinants are essential in achieving successful implementation of FPIs in the community. However, some determinants are considered important to address, regardless of the context where the implementation occurs. Such as accounting for time constraints and financial limitations, and considering the needs of older adults. Also, broad cross-sector collaboration and coordination are required in multifactorial FPIs. Additional context analysis is always an essential part of implementation efforts, as contexts may differ greatly, requiring a locally tailored approach.
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Big data heeft niet alleen geleid tot uitdagende technische vraagstukken, ook gaat het gepaard met allerlei nieuwe ethische en morele kwesties. Om verantwoord met big data om te gaan, moet ook over deze kwesties worden nagedacht. Want slecht datagebruik kan nadelige gevolgen hebben voor grote groepen mensen en voor organisaties. In de slotaflevering van deze serie verkennen Klaas Jan Mollema en Niek van Antwerpen op een pragmatische manier de ethische kant van big data, zonder te blijven steken in de negatieve effecten ervan.
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Prompt and timely response to incoming cyber-attacks and incidents is a core requirement for business continuity and safe operations for organizations operating at all levels (commercial, governmental, military). The effectiveness of these measures is significantly limited (and oftentimes defeated altogether) by the inefficiency of the attack identification and response process which is, effectively, a show-stopper for all attack prevention and reaction activities. The cognitive-intensive, human-driven alarm analysis procedures currently employed by Security Operation Centres are made ineffective (as opposed to only inefficient) by the sheer amount of alarm data produced, and the lack of mechanisms to automatically and soundly evaluate the arriving evidence to build operable risk-based metrics for incident response. This project will build foundational technologies to achieve Security Response Centres (SRC) based on three key components: (1) risk-based systems for alarm prioritization, (2) real-time, human-centric procedures for alarm operationalization, and (3) technology integration in response operations. In doing so, SeReNity will develop new techniques, methods, and systems at the intersection of the Design and Defence domains to deliver operable and accurate procedures for efficient incident response. To achieve this, this project will develop semantically and contextually rich alarm data to inform risk-based metrics on the mounting evidence of incoming cyber-attacks (as opposed to firing an alarm for each match of an IDS signature). SeReNity will achieve this by means of advanced techniques from machine learning and information mining and extraction, to identify attack patterns in the network traffic, and automatically identify threat types. Importantly, SeReNity will develop new mechanisms and interfaces to present the gathered evidence to SRC operators dynamically, and based on the specific threat (type) identified by the underlying technology. To achieve this, this project unifies Dutch excellence in intrusion detection, threat intelligence, and human-computer interaction with an industry-leading partner operating in the market of tailored solutions for Security Monitoring.
The precarity in the cultural sector became exposed during the COVID-19 pandemic. With the lockdowns, the sources of income for cultural venues and cultural workers vanished overnight, intensifying an already challenging labour market. Particularly freelance cultural workers were hit hard. While the immediate shock of the pandemic on the cultural sector has been well documented, the effects on the sector in the aftermath of the pandemic are still to be revealed and repaired. This project tackles these issues by zooming in on the case of the performing arts scene in Groningen. This scene constitutes the part of the cultural sector that was affected the most by the lockdowns. Currently, venues and event organizers in Groningen lack qualified freelance staff as many left the industry during the pandemic. At the same time, self-employed cultural workers find it difficult to generate sufficient incomes and develop sustainable careers in the city. The municipality is eager to support the industry, including freelancers, but is unsure about how best to do so. With a consortium composed of the university, the municipality, a knowledge organisation specialised in cultural entrepreneurship, and a network for creative freelancers in the North of the Netherlands the project is well-equipped to reach its two-fold aims of investigating this current situation and coming up with suggestions for solutions. The core component of the project is an interview study with three groups of self-employed cultural freelancers: experienced production staff, experienced performers, and nascent freelancers (both production staff and performers). Based on data from this study, the project provides a multifaceted picture of the cultural ecosystem in Groningen, highlighting how this system is experienced. This establishes a solid foundation for staging discussions on working conditions in the sector, enabling the project to eventually conclude with recommendations on how to improve the situation.
