document

Mass Media Musical Meaning: Opportunities from the Collaborative Web

Liem, C.C.S. (author)

In the digital domain, music is usually studied from a positivist viewpoint, focusing on general ‘objective’ music descriptors. In this work, we strive to put music in a more social and cultural context, looking into ways to unify data analysis methods with thoughts from the humanities on musical meaning and significance. More specifically, we...

conference paper 2015

document

Cybersecurity via Intermediaries: Analyzing Security Measurements to Understand Intermediary Incentives and Inform Public Policy

Asghari, H. (author)

Research in the field of information security economics has clarified how attacker and defender incentives affect cybersecurity. It has also highlighted the role of intermediaries in strengthening cybersecurity. Intermediaries are organizations and firms that provide the Internet’s infrastructure and platforms. This dissertation looks at how...

doctoral thesis 2016

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Revisiting Urban Dynamics through Social Urban Data: Methods and tools for data integration, visualization, and exploratory analysis to understand the spatiotemporal dynamics of human activity in cities

Psyllidis, A. (author)

The study of dynamic spatial and social phenomena in cities has evolved rapidly in the recent years, yielding new insights into urban dynamics. This evolution is strongly related to the emergence of new sources of data for cities (e.g. sensors, mobile phones, online social media etc.), which have potential to capture dimensions of social and...

doctoral thesis 2016

document

Data Collaboratives: How to create value from data for public problem solving? Panel

Susha, I. (author), Verhulst, Stefaan (author), Janssen, M.F.W.H.A. (author), Pardo, Theresa (author)

This panel is dedicated to the theme of 'data collaboratives', a novel form of public private partnership to leverage data for addressing societal challenges. The panel brings together prolific researchers and practitioners to share lessons and discuss how value is created from data collaboratives for the solving of public problems. The panel...

conference paper 2017

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Personalized Energy Services: A Data-Driven Methodology towards Sustainable, Smart Energy Systems

Uttama Nambi, Akshay (author)

The rapid pace of urbanization has an impact on climate change and other environmental issues. Currently, 54% of the global population lives in cities accounting for two-thirds of global energy demand. Sustainable energy generation and consumption is the top humanity’s problem for the next 50 years. Faced with rising urban population and the...

doctoral thesis 2017

document

A Convolutional Neural Network-Based Model for Predicting The Perceived Attractiveness of Urban Places

Psyllidis, A. (author), Choiri, Hendra Hadhil (author)

An understanding of how people perceive attractive or unattractive places in cities is vitally important to urban planning and policy making. Given the subjective nature of human perception and the ambiguous character of attractiveness as an attribute of urban places, it is challenging to quantify and reliably assess the extent to which a place...

abstract 2018

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Data science empowering the public: Data-driven dashboards for transparent and accountable decision-making in smart cities

Matheus, R. (author), Janssen, M.F.W.H.A. (author), Maheshwari, D. (author)

Dashboards visualize a consolidated set data for a certain purpose which enables users to see what is happening and to initiate actions. Dashboards can be used by governments to support their decision-making and policy processes or to communicate and interact with the public. The objective of this paper is to understand and to support the...

journal article 2018

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Using Social Media for Attendees Density Estimation in City-Scale Events

Gong, X. (author), Yang, J. (author), Daamen, W. (author), Bozzon, A. (author), Hoogendoorn, S.P. (author), Houben, G.J.P.M. (author)

City-scale events attract large amounts of attendees in temporarily re-purposed urban environments. In this setting, the real-time measurement of the density of attendees stationing in – or moving through – the event terrain is central to applications such as crowd management, emergency support, and quality of service...

journal article 2018

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Reproducible research and GIScience: An evaluation using AGILE conference papers

Nüst, Daniel (author), Granell, Carlos (author), Hofer, Barbara (author), Konkol, Markus (author), Ostermann, Frank O. (author), Sileryte, R. (author), Cerutti, Valentina (author)

The demand for reproducible research is on the rise in disciplines concerned with data analysis and computational methods. Therefore, we reviewed current recommendations for reproducible research and translated them into criteria for assessing the reproducibility of articles in the field of geographic information science (GIScience). Using...

journal article 2018

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An ethico-legal framework for social data science

Forgó, Nikolaus (author), Hänold, Stefanie (author), van den Hoven, M.J. (author), Krügel, Tina (author), Lishchuk, Iryna (author), Mahieu, R.L.P. (author), Monreale, Anna (author), Pedreschi, Dino (author), Pratesi, Francesca (author), van Putten, D.C. (author)

This paper presents a framework for research infrastructures enabling ethically sensitive and legally compliant data science in Europe. Our goal is to describe how to design and implement an open platform for big data social science, including, in particular, personal data. To this end, we discuss a number of infrastructural, organizational...

journal article 2020

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Sensing the city through new forms of urban data

Psyllidis, A. (author)

book chapter 2020

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Questions for Data Scientists in Software Engineering: A Replication

Huijgens, H.K.M. (author), Rastogi, A. (author), Mulders, E.A. (author), Gousios, G. (author), van Deursen, A. (author)

In 2014, a Microsoft study investigated the sort of questions that data science applied to software engineering should answer. This resulted in 145 questions that developers considered relevant for data scientists to answer, thus providing a research agenda to the community. Fast forward to five years, no further studies investigated whether the...

conference paper 2020

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Revisiting statistical analysis curriculum in a data era: a learning-by-mistake approach

Gabriela Duque, Ana (author), Gonçalves Melo Pequito, S.D. (author), Rosado Coelho, Joana (author)

Contribution: We re-think the ‘Statistical Analysis’ curriculum building upon system engineering tools where assumptions (e.g., ABET criteria and student profiles) are carefully assessed, a learn-by-mistake approach ensures that several of the main statistical mistakes are learned, and advanced topics are proposed to make a strong connection...

report 2020

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Trusted decision-making: Data governance for creating trust in data science decision outcomes

Brous, Paul (author), Janssen, M.F.W.H.A. (author)

Organizations are increasingly introducing data science initiatives to support decision-making. However, the decision outcomes of data science initiatives are not always used or adopted by decision-makers, often due to uncertainty about the quality of data input. It is, therefore, not surprising that organizations are increasingly turning to...

journal article 2020

document

Data Governance as Success Factor for Data Science

Brous, P.A. (author), Janssen, M.F.W.H.A. (author), Krans, Rutger (author)

More and more, asset management organizations are introducing data science initiatives to support predictive maintenance and anomaly detection. Asset management organizations are by nature data intensive to manage their assets like bridges, dykes, railways and roads. For this, they often implement data lakes using a variety of architectures...

conference paper 2020

document

Rethinking filter: An interdisciplinary inquiry into typology and concept of filter, towards an active filter model

Razghandi, Khashayar (author), Yaghmaei, E. (author)

This work aims to re-investigate different aspects of a variety of filters and filtration processes within diverse realms of knowledge from an interdisciplinary point of view, and develops a comprehensive Active Model of Filter that accommodates the phenomena in its entire diversity and complexity. The Active Filter Model proposes to take...

journal article 2020

document

Data science as knowledge creation a framework for synergies between data analysts and domain professionals

van der Voort, H.G. (author), van Bulderen, Sabine (author), Cunningham, Scott (author), Janssen, M.F.W.H.A. (author)

The road from data generation to data use is commonly approached as a data-driven, functional process in which domain expertise is integrated as an afterthought. In this contribution we complement this functional view with an institutional view, that takes data analysis and domain professionalism as complementary (yet fallible) knowledge...

journal article 2021

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Identification of diseases and physiological disorders in potato via multispectral drone imagery using machine learning tools

León-Rueda, William A. (author), León Sánchez, C.A. (author), Caro, Sandra Gómez (author), Ramírez-Gil, Joaquín Guillermo (author)

The rapid and precise detection of diseases and plant disorders is the basis for the adequate and timely design of management strategies. Currently, there are several non-destructive alternatives that allow early detection, highlighting the use of spectral cameras attached to unmanned aerial vehicles (UAVs). The objective of this research was...

journal article 2021

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Editorial: Data Science Applications to Inverse and Optimization Problems in Earth Science

Leeuwenburgh, O. (author), Emerick, Alexandre A. (author), Jafarpour, Behnam (author), Zhang, Dongxiao (author), Luo, Xiaodong (author)

contribution to periodical 2021

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A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer

Kulin, Merima (author), Kazaz, T. (author), De Poorter, Eli (author), Moerman, Ingrid (author)

This paper presents a systematic and comprehensive survey that reviews the latest research efforts focused on machine learning (ML) based performance improvement of wireless networks, while considering all layers of the protocol stack: PHY,MAC and network. First, the related work and paper contributions are discussed, followed by providing...

journal article 2021