Doing It Together Science: D3.2 Innovation Hubs

Report on setting up of citizen science partner innovation hubs, facilities, multiplier arrangements with third parties such as science museums and centres, and future development plan

Citizen Science and Smart Cities

The report summarizes the presentations, discussions, and conclusions of the Citizen Science and Smart Cities Summit organised by the European Commission Joint Research Centre on 5-7th February 2014. In the context of the Summit, the label Citizen Science was used to include both citizen science projects, and others that are about user-generated content, not necessarily addressing a scientific process or issues. The evidence presented by 27 different projects shows the vitality and diversity of the field but also a number of critical points: • Citizen science project are more than collecting data: they are about raising awareness, building capacity, and strengthening communities. • Likewise, smart cities are not only about ICT, energy and transport infrastructures: Smart cities are about smart citizens, who participate in their city’s daily governance, are concerned about increasing the quality of life of their fellow-citizens, and about protecting their environment. Technology may facilitate, but is no solution per se. • Unfortunately to date there seems to be little synergy between citizen science and smart cities initiatives, and there is little interoperability and reusability of the data, apps, and services developed in each project. • It is difficult to compare the results among citizen science, and smart cities projects or translate from one context to another. • The ephemeral nature of much of the data, which disappear short after the end of the projects, means lack of reproducibility of results and longitudinal analysis of time series challenging, if not impossible. • There are also new challenges with respect to the analytical methods needed to integrate quantitative and qualitative data from heterogeneous sources that need further research. • Building and maintaining trust are key points of any citizen science or smart city project. There is a need to work with the community and not just for, or on, the community. It is critical not just to take (data, information, knowledge) but to give back something that is valued by the community itself. The development of citizen science associations in Europe and the US are important developments that may address some of the points above. There are also actions through which the European Commission Joint Research Centre can make an important contribution: • Map citizen science and smart cities projects, and generate a semantic network of concepts between the projects to facilitate search of related activities, and community building. • Provide a repository for citizen science and smart cities data (anonymised and aggregated), software, services, and applications so that they are maintained beyond the life of the projects they originate from, and made shareable and reusable. • Develop regional test beds for the analysis and integration of social and environmental data from heterogeneous sources, with a focus on quality of life and well-being. • Undertake comparative studies, and analyse issues related to scaling up to the European dimension. • Support citizen science and smart cities projects with the JRC knowledge on semantic interoperability, data models, and interoperability arrangements. • Partner with the European Citizen Science Association, and contribute to its interoperability activities. • Work towards making the JRC, and the European Commission, a champion of citizen participation in European science.JRC.H.6-Digital Earth and Reference Dat

An exploratory case study on the preparation of undergraduate civil engineering students at the University of Cape Town to contribute to an inclusive society for people with disabilities

Based on the experiences of the researcher who is a quadriplegic, people with disabilities still encounter many challenges within the built environment. As civil engineers play a central role, this study set out to address the question - How are undergraduate Civil Engineering students at the University of Cape Town (UCT) being prepared to contribute to an inclusive society that accommodates people with disabilities? Based on a conceptual theoretical framework that draws from a broader context of the Universal Declaration of Human Rights and the United Nations Convention on the Rights of People with Disabilities, a production line analogy was adopted to explore the resources, approaches and experiences of key stakeholders involved in the preparation of the students. The adopted model recognised the students as the "raw materials", the graduates as the "products", UCT as the "factory", the Engineering Council of South Africa (ECSA) as the "quality controller", the Engineering Industry "utilised and refined" the product, while people with disabilities were the "consumers". A qualitative, exploratory, multiple case design was utilised incorporating interviews with representatives of UCT, the Engineering Industry, and people with disabilities, while the contents of the website of ECSA was reviewed. ECSA has a transformation agenda that does not explicitly identify issues about disability. However, there were opportunities to incorporate the concept of Universal Design (UD) into the exit level outcomes of the undergraduate civil engineering programme. Furthermore, while UCT, Industry and people with disabilities identified legislation around disability as a major resource for the training of students, and UCT and Industry shared an open minded approach to the concept of UD, its inclusion in the education programme is still lacking. There was a conspicuous gap for collaboration between the stakeholders, which seem to hinder the adoption of a multidisciplinary approach in the preparation of the students. The study highlighted the need to formalise a platform that brings the key stakeholders together in the preparation of civil engineering students to contribute to the development of an inclusive society that accommodates people with disabilities

A Value-Driven Framework for Software Architecture

Software that is not aligned with the business values of the organization for which it was developed does not entirely fulfill its raison d’etre. Business values represent what is important in a company, or organization, and should influence the overall software system behavior, contributing to the overall success of the organization. However, approaches to derive a software architecture considering the business values exchanged between an organization and its market players are lacking. Our quest is to address this problem and investigate how to derive value-centered architectural models systematically. We used the Technology Research method to address this PhD research question. This methodological approach proposes three steps: problem analysis, innovation, and validation. The problem analysis was performed using systematic studies of the literature to obtain full coverage on the main themes of this work, particularly, business value modeling, software architecture methods, and software architecture derivation methods. Next, the innovation step was accomplished by creating a framework for the derivation of a software reference architecture model considering an organization’s business values. The resulting framework is composed of three core modules: Business Value Modeling, Agile Reference Architecture Modeling, and Goal-Driven SOA Architecture Modeling. While the Business value modeling module focuses on building a stakeholder-centric business specification, the Agile Reference Architecture Modeling and the Goal-Driven SOA Architecture Modeling modules concentrate on generating a software reference architecture aligned with the business value specification. Finally, the validation part of our framework is achieved through proof-of-concept prototypes for three new domain specific languages, case studies, and quasi-experiments, including a family of controlled experiments. The findings from our research show that the complexity and lack of rigor in the existing approaches to represent business values can be addressed by an early requirements specification method that represents the value exchanges of a business. Also, by using sophisticated model-driven engineering techniques (e.g., metamodels, model transformations, and model transformation languages), it was possible to obtain source generators to derive a software architecture model based on early requirements value models, while assuring traceability throughout the architectural derivation process. In conclusion, despite using sophisticated techniques, the derivation process of a software reference architecture is helped by simple to use methods supported by black box transformations and guidelines that facilitate the activities for the less experienced software architects. The experimental validation process used confirmed that our framework is feasible and perceived as easy to use and useful, also indicating that the participants of the experiments intend to use it in the future

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

Journalistic Knowledge Platforms: from Idea to Realisation

Journalistiske kunnskapsplattformer (JKPer) er en type intelligente informasjonssystemer designet for å forbedre nyhetsproduksjonsprosesser ved å kombinere stordata, kunstig intelligens (KI) og kunnskapsbaser for å støtte journalister. Til tross for sitt potensial for å revolusjonere journalistikkfeltet, har adopsjonen av JKPer vært treg, med forskere og store nyhetsutløp involvert i forskning og utvikling av JKPer. Den langsomme adopsjonen kan tilskrives den tekniske kompleksiteten til JKPer, som har ført til at nyhetsorganisasjoner stoler på flere uavhengige og oppgavespesifikke produksjonssystemer. Denne situasjonen kan øke ressurs- og koordineringsbehovet og kostnadene, samtidig som den utgjør en trussel om å miste kontrollen over data og havne i leverandørlåssituasjoner. De tekniske kompleksitetene forblir en stor hindring, ettersom det ikke finnes en allerede godt utformet systemarkitektur som ville lette realiseringen og integreringen av JKPer på en sammenhengende måte over tid. Denne doktoravhandlingen bidrar til teorien og praksisen rundt kunnskapsgrafbaserte JKPer ved å studere og designe en programvarearkitektur som referanse for å lette iverksettelsen av konkrete løsninger og adopsjonen av JKPer. Den første bidraget til denne doktoravhandlingen gir en grundig og forståelig analyse av ideen bak JKPer, fra deres opprinnelse til deres nåværende tilstand. Denne analysen gir den første studien noensinne av faktorene som har bidratt til den langsomme adopsjonen, inkludert kompleksiteten i deres sosiale og tekniske aspekter, og identifiserer de største utfordringene og fremtidige retninger for JKPer. Den andre bidraget presenterer programvarearkitekturen som referanse, som gir en generisk blåkopi for design og utvikling av konkrete JKPer. Den foreslåtte referansearkitekturen definerer også to nye typer komponenter ment for å opprettholde og videreutvikle KI-modeller og kunnskapsrepresentasjoner. Den tredje presenterer et eksempel på iverksettelse av programvarearkitekturen som referanse og beskriver en prosess for å forbedre effektiviteten til informasjonsekstraksjonspipelines. Denne rammen muliggjør en fleksibel, parallell og samtidig integrering av teknikker for naturlig språkbehandling og KI-verktøy. I tillegg diskuterer denne avhandlingen konsekvensene av de nyeste KI-fremgangene for JKPer og ulike etiske aspekter ved bruk av JKPer. Totalt sett gir denne PhD-avhandlingen en omfattende og grundig analyse av JKPer, fra teorien til designet av deres tekniske aspekter. Denne forskningen tar sikte på å lette vedtaket av JKPer og fremme forskning på dette feltet.Journalistic Knowledge Platforms (JKPs) are a type of intelligent information systems designed to augment news creation processes by combining big data, artificial intelligence (AI) and knowledge bases to support journalists. Despite their potential to revolutionise the field of journalism, the adoption of JKPs has been slow, with scholars and large news outlets involved in the research and development of JKPs. The slow adoption can be attributed to the technical complexity of JKPs that led news organisation to rely on multiple independent and task-specific production system. This situation can increase the resource and coordination footprint and costs, at the same time it poses a threat to lose control over data and face vendor lock-in scenarios. The technical complexities remain a major obstacle as there is no existing well-designed system architecture that would facilitate the realisation and integration of JKPs in a coherent manner over time. This PhD Thesis contributes to the theory and practice on knowledge-graph based JKPs by studying and designing a software reference architecture to facilitate the instantiation of concrete solutions and the adoption of JKPs. The first contribution of this PhD Thesis provides a thorough and comprehensible analysis of the idea of JKPs, from their origins to their current state. This analysis provides the first-ever study of the factors that have contributed to the slow adoption, including the complexity of their social and technical aspects, and identifies the major challenges and future directions of JKPs. The second contribution presents the software reference architecture that provides a generic blueprint for designing and developing concrete JKPs. The proposed reference architecture also defines two novel types of components intended to maintain and evolve AI models and knowledge representations. The third presents an instantiation example of the software reference architecture and details a process for improving the efficiency of information extraction pipelines. This framework facilitates a flexible, parallel and concurrent integration of natural language processing techniques and AI tools. Additionally, this Thesis discusses the implications of the recent AI advances on JKPs and diverse ethical aspects of using JKPs. Overall, this PhD Thesis provides a comprehensive and in-depth analysis of JKPs, from the theory to the design of their technical aspects. This research aims to facilitate the adoption of JKPs and advance research in this field.Doktorgradsavhandlin

Developing employability in engineering education: a systematic review of the literature

In this systematic review of the research literature on engineering employability, curricular and pedagogical arrangements that prepare graduates for work in the twenty-first century were identified. The research question guiding the review was: Which curricular and pedagogical arrangements promote engineering students’ employability? The particular focus of the study was on how authors prioritised engineering knowledge and professional skills. The review drew on a theoretical framework that differentiated between engineering knowledge and professional skills to explain how employability could be included in engineering programmes. Data was obtained from research studies over the period 2007–2017. We found an interdependent relationship between engineering knowledge and professional skills that enabled engineering graduates to attain employability. The com of engineering problems require students to master engineering knowledge, while the ability to work with others across contexts requires professional skills. Both are necessary for deep understanding of engineering principles and a focus on real world problem

A mapping study on documentation in Continuous Software Development

Context: With an increase in Agile, Lean, and DevOps software methodologies over the last years (collectively referred to as Continuous Software Development (CSD)), we have observed that documentation is often poor. Objective: This work aims at collecting studies on documentation challenges, documentation practices, and tools that can support documentation in CSD. Method: A systematic mapping study was conducted to identify and analyze research on documentation in CSD, covering publications between 2001 and 2019. Results: A total of 63 studies were selected. We found 40 studies related to documentation practices and challenges, and 23 studies related to tools used in CSD. The challenges include: informal documentation is hard to understand, documentation is considered as waste, productivity is measured by working software only, documentation is out-of-sync with the software and there is a short-term focus. The practices include: non-written and informal communication, the usage of development artifacts for documentation, and the use of architecture frameworks. We also made an inventory of numerous tools that can be used for documentation purposes in CSD. Overall, we recommend the usage of executable documentation, modern tools and technologies to retrieve information and transform it into documentation, and the practice of minimal documentation upfront combined with detailed design for knowledge transfer afterwards. Conclusion: It is of paramount importance to increase the quantity and quality of documentation in CSD. While this remains challenging, practitioners will benefit from applying the identified practices and tools in order to mitigate the stated challenges