Citizens regularly search the Web to make informed decisions on daily life questions, like online purchases, but how they reason with the results is unknown. This reasoning involves engaging with data in ways that require statistical literacy, which is crucial for navigating contemporary data. However, many adults struggle to critically evaluate and interpret such data and make data-informed decisions. Existing literature provides limited insight into how citizens engage with web-sourced information. We investigated: How do adults reason statistically with web-search results to answer daily life questions? In this case study, we observed and interviewed three vocationally educated adults searching for products or mortgages. Unlike data producers, consumers handle pre-existing, often ambiguous data with unclear populations and no single dataset. Participants encountered unstructured (web links) and structured data (prices). We analysed their reasoning and the process of preparing data, which is part of data-ing. Key data-ing actions included judging relevance and trustworthiness of the data and using proxy variables when relevant data were missing (e.g., price for product quality). Participants’ statistical reasoning was mainly informal. For example, they reasoned about association but did not calculate a measure of it, nor assess underlying distributions. This study theoretically contributes to understanding data-ing and why contemporary data may necessitate updating the investigative cycle. As current education focuses mainly on producers’ tasks, we advocate including consumers’ tasks by using authentic contexts (e.g., music, environment, deferred payment) to promote data exploration, informal statistical reasoning, and critical web-search skills—including selecting and filtering information, identifying bias, and evaluating sources.
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Why is it that we know and still act as if we do not know? SMEs are considered engines of job creation and therefore growth and generation of income but is it really true that the solo self-employed and micro entrepreneurs will become small or medium entrepreneurs, e.g. graduate? We knew in the 80’s that this assumption needed to be looked at critically. Research revealed that graduation hardly existed. Practitioners in MSME support and development programmes entertain few illusions about their programmes actually leading to graduation, while NGO and Government policy officers, from behind their desks, often presume that graduation occurs frequently. Actual graduation rates and the extent to which they can be attributed to interventions remain an unresolved and important issue. After more than three decades it is justified to the question whether it is still true that graduation hardly exists? If that is the case one needs to take a critical look into prevailing policies and programs in support of the SME sector.
Completeness of data is vital for the decision making and forecasting on Building Management Systems (BMS) as missing data can result in biased decision making down the line. This study creates a guideline for imputing the gaps in BMS datasets by comparing four methods: K Nearest Neighbour algorithm (KNN), Recurrent Neural Network (RNN), Hot Deck (HD) and Last Observation Carried Forward (LOCF). The guideline contains the best method per gap size and scales of measurement. The four selected methods are from various backgrounds and are tested on a real BMS and metereological dataset. The focus of this paper is not to impute every cell as accurately as possible but to impute trends back into the missing data. The performance is characterised by a set of criteria in order to allow the user to choose the imputation method best suited for its needs. The criteria are: Variance Error (VE) and Root Mean Squared Error (RMSE). VE has been given more weight as its ability to evaluate the imputed trend is better than RMSE. From preliminary results, it was concluded that the best K‐values for KNN are 5 for the smallest gap and 100 for the larger gaps. Using a genetic algorithm the best RNN architecture for the purpose of this paper was determined to be GatedRecurrent Units (GRU). The comparison was performed using a different training dataset than the imputation dataset. The results show no consistent link between the difference in Kurtosis or Skewness and imputation performance. The results of the experiment concluded that RNN is best for interval data and HD is best for both nominal and ratio data. There was no single method that was best for all gap sizes as it was dependent on the data to be imputed.
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“Being completely circular by 2050” that is the goal for the Dutch economy. The transition towards the circular and biobased economy for energy and materials is essential to reach that goal. Sustainably produced materials based on renewable sources like biomass should be developed. One of the industries which recognizes the need for transition is the building industry. Currently, there are a couple of biobased building concepts available which claim to be more than 95% biobased. Since the current resins and adhesives, used to produce panel boards (like cross laminated timber (CLT)), are all produced synthetically, one of the missing links for the building industry to become 100% biobased are biobased resins and adhesives (and binders). In literature, there are several solutions described for resins/adhesives/binders which are based on the biomolecules lignin and cellulose which are abundantly present in fibrous biomass, but these products are not (yet) available on the market. At the same time, there are several fibrous biomass side streams available for which higher added value applications are demanded. These side streams are perfect sources of lignin and cellulose and are, therefore, very suitable sources to form the basis for biobased resins/adhesives/binders. However, they need modification to obtain the desired functionalities. The problem statement of this project, based on the request for valorization of fibrous side streams and the need for biobased building materials, is “How can we valorize fibrous biomass (side streams) into biobased building applications.” This problem statement is translated into the research goal. The aim of this research is to develop a biobased resin, adhesive or binder for the production of panel boards based on the side streams of fibrous/lignocellulosic biomass which meets the requirement of the building industry with respect to VOC emissions, and water resistance so that it contributes to a healthy living environment.
The reclaiming of street spaces for pedestrians during the COVID-19 pandemic, such as on Witte de Withstraat in Rotterdam, appears to have multiple benefits: It allows people to escape the potentially infected indoor air, limits accessibility for cars and reduces emissions. Before ordering their coffee or food, people may want to check one of the many wind and weather apps, such as windy.com: These apps display the air quality at any given time, including, for example, the amount of nitrogen dioxide (NO2), a gas responsible for an increasing number of health issues, particularly respiratory and cardiovascular diseases. Ships and heavy industry in the nearby Port of Rotterdam, Europe’s largest seaport, exacerbate air pollution in the region. Not surprisingly, in 2020 Rotterdam was ranked as one of the unhealthiest cities in the Netherlands, according to research on the health of cities conducted by Arcadis. Reducing air pollution is a key target for the Port Authority and the City of Rotterdam. Missing, however, is widespread awareness among citizens about how air pollution links to socio-spatial development, and thus to the future of the port city cluster of Rotterdam. To encourage awareness and counter the problem of "out of sight - out of mind," filmmaker Entrop&DeZwartFIlms together with ONSTV/NostalgieNet, and Rotterdam Veldakademie, are collaborating with historians of the built environment and computer science and public health from TU Delft and Erasmus University working on a spatial data platform to visualize air pollution dynamics and socio-economic datasets in the Rotterdam region. Following discussion of findings with key stakeholders, we will make a pilot TV-documentary. The documentary, discussed first with Rotterdam citizens, will set the stage for more documentaries on European and international cities, focusing on the health effects—positive and negative—of living and working near ports in the past, present, and future.
