CERN openlab Whitepaper on Future IT Challenges in Scientific Research

This whitepaper describes the major IT challenges in scientific research at CERN and several other European and international research laboratories and projects. Each challenge is exemplified through a set of concrete use cases drawn from the requirements of large-scale scientific programs. The paper is based on contributions from many researchers and IT experts of the participating laboratories and also input from the existing CERN openlab industrial sponsors. The views expressed in this document are those of the individual contributors and do not necessarily reflect the view of their organisations and/or affiliates

Reinventing the Social Scientist and Humanist in the Era of Big Data

This book explores the big data evolution by interrogating the notion that big data is a disruptive innovation that appears to be challenging existing epistemologies in the humanities and social sciences. Exploring various (controversial) facets of big data such as ethics, data power, and data justice, the book attempts to clarify the trajectory of the epistemology of (big) data-driven science in the humanities and social sciences

HIL: designing an exokernel for the data center

We propose a new Exokernel-like layer to allow mutually untrusting physically deployed services to efficiently share the resources of a data center. We believe that such a layer offers not only efficiency gains, but may also enable new economic models, new applications, and new security-sensitive uses. A prototype (currently in active use) demonstrates that the proposed layer is viable, and can support a variety of existing provisioning tools and use cases.Partial support for this work was provided by the MassTech Collaborative Research Matching Grant Program, National Science Foundation awards 1347525 and 1149232 as well as the several commercial partners of the Massachusetts Open Cloud who may be found at http://www.massopencloud.or

Crowds for Clouds: Recent Trends in Humanities Research Infrastructures

Humanities have convincingly argued that they need transnational research opportunities and through the digital transformation of their disciplines also have the means to proceed with it on an up to now unknown scale. The digital transformation of research and its resources means that many of the artifacts, documents, materials, etc. that interest humanities research can now be combined in new and innovative ways. Due to the digital transformations, (big) data and information have become central to the study of culture and society. Humanities research infrastructures manage, organise and distribute this kind of information and many more data objects as they becomes relevant for social and cultural research

Building Cultural Heritage Reference Collections from Social Media through Pooling Strategies: The Case of 2020’s Tensions Over Race and Heritage

Preprint del artículo[Abstract] Social networks constitute a valuable source for documenting heritage constitution processes or obtaining a real-time snapshot of a cultural heritage research topic. Many heritage researchers use social networks as a social thermometer to study these processes, creating, for this purpose, collections that constitute born-digital archives potentially reusable, searchable, and of interest to other researchers or citizens. However, retrieval and archiving techniques used in social networks within heritage studies are still semi-manual, being a time-consuming task and hindering the reproducibility, evaluation, and open-up of the collections created. By combining Information Retrieval strategies with emerging archival techniques, some of these weaknesses can be left behind. Specifically, pooling is a well-known Information Retrieval method to extract a sample of documents from an entire document set (posts in case of social network's information), obtaining the most complete and unbiased set of relevant documents on a given topic. Using this approach, researchers could create a reference collection while avoiding annotating the entire corpus of documents or posts retrieved. This is especially useful in social media due to the large number of topics treated by the same user or in the same thread or post. We present a platform for applying pooling strategies combined with expert judgment to create cultural heritage reference collections from social networks in a customisable, reproducible, documented, and shareable way. The platform is validated by building a reference collection from a social network about the recent attacks on patrimonial entities motivated by anti-racist protests. This reference collection and the results obtained from its preliminary study are available for use. This real application has allowed us to validate the platform and the pooling strategies for creating reference collections in heritage studies from social networks.This research has received financial support from: (i) Saving European Archaeology from the Digital Dark Age (SEADDA) 2019-2023 COST ACTION CA 18128; (ii) “Ministerio de Ciencia, Innovación y Universidades” of the Government of Spain and the ERDF (projects RTI2018-093336-B-C21 and RTI2018-093336-B-C22); (iii) Xunta de Galicia - “Consellería de Cultura, Educación e Universidade” (project GPC ED431B 2019/03); (iv) Xunta de Galicia - “Consellería de Cultura, Educación e Universidade” and the ERDF (“Centro Singular de Investigación de Galicia” accreditation ED431G 2019/01)European Cooperation in Science and Technology; CA18128Xunta de Galicia; ED431B 2019/03Xunta de Galicia; ED431G 2019/0

Privacy Preserved Model Based Approaches for Generating Open Travel Behavioural Data

Location-aware technologies and smart phones are fast growing in usage and adoption as a medium of service request and delivery of daily activities. However, the increasing usage of these technologies has birthed new challenges that needs to be addressed. Privacy protection and the need for disaggregate mobility data for transportation modelling needs to be balanced for applications and academic research. This dissertation focuses on developing modern privacy mechanisms that seek to satisfy requirements on privacy and data utility for fine-grained travel behavioural modelling applications using large-scale mobility data. To accomplish this, we review the challenges and opportunities that are needed to be solved in order to harness the full potential of “Big Transportation Data”. Also, we perform a quantitative evaluation on the degree of privacy that are provided by popular location anonymization techniques when undertaken on sensitive location data (i.e. homes, offices) of a travel survey. As a step to solve the trade-off between privacy and utility, we develop a differentially-private generative model for simultaneously synthesizing both socio-economic attributes and sequences of activity diary. Adversarial attack models are proposed and tested to evaluate the effectiveness of the proposed system against privacy attacks. The results show that datasets from the developed privacy enhancing system can be used for travel behavioural modelling with satisfactory results while ensuring an acceptable level of privacy

XIII Міжнародна конференція з математичної, природничо-наукової та технологічної освіти (ICon-MaSTEd 2021) 12-14 травня 2021 року, м. Кривий Ріг, Україна

XIII International Conference on Mathematics, Science and Technology Education (ICon-MaSTEd 2021) 12-14 May 2021, Kryvyi Rih, Ukraine - proceedings.XIII Міжнародна конференція з математичної, природничо-наукової та технологічної освіти (ICon-MaSTEd 2021) 12-14 травня 2021 року, м. Кривий Ріг, Україна - матеріали