How are topics born? Understanding the research dynamics preceding the emergence of new areas

The ability to promptly recognise new research trends is strategic for many stake- holders, including universities, institutional funding bodies, academic publishers and companies. While the literature describes several approaches which aim to identify the emergence of new research topics early in their lifecycle, these rely on the assumption that the topic in question is already associated with a number of publications and consistently referred to by a community of researchers. Hence, detecting the emergence of a new research area at an embryonic stage, i.e., before the topic has been consistently labelled by a community of researchers and associated with a number of publications, is still an open challenge. In this paper, we begin to address this challenge by performing a study of the dynamics preceding the creation of new topics. This study indicates that the emergence of a new topic is anticipated by a significant increase in the pace of collaboration between relevant research areas, which can be seen as the ‘parents’ of the new topic. These initial findings (i) confirm our hypothesis that it is possible in principle to detect the emergence of a new topic at the embryonic stage, (ii) provide new empirical evidence supporting relevant theories in Philosophy of Science, and also (iii) suggest that new topics tend to emerge in an environment in which weakly interconnected research areas begin to cross-fertilise

Smart Topic Miner: Supporting Springer Nature Editors with Semantic Web Technologies

Academic publishers, such as Springer Nature, annotate scholarly products with the appropriate research topics and keywords to facilitate the marketing process and to support (digital) libraries and academic search engines. This critical process is usually handled manually by experienced editors, leading to high costs and slow throughput. In this demo paper, we present Smart Topic Miner (STM), a semantic application designed to support the Springer Nature Computer Science editorial team in classifying scholarly publications. STM analyses conference proceedings and annotates them with a set of topics drawn from a large automatically generated ontology of research areas and a set of tags from Springer Nature Classification

Early Detection of Research Trends

Being able to rapidly recognise new research trends is strategic for many stakeholders, including universities, institutional funding bodies, academic publishers and companies. The literature presents several approaches to identifying the emergence of new research topics, which rely on the assumption that the topic is already exhibiting a certain degree of popularity and consistently referred to by a community of researchers. However, detecting the emergence of a new research area at an embryonic stage, i.e., before the topic has been consistently labelled by a community of researchers and associated with a number of publications, is still an open challenge. In this dissertation, we begin to address this challenge by performing a study of the dynamics preceding the creation of new topics. This study indicates that the emergence of a new topic is anticipated by a significant increase in the pace of collaboration between relevant research areas, which can be seen as the 'ancestors' of the new topic. Based on this understanding, we developed Augur, a novel approach to effectively detect the emergence of new research topics. Augur analyses the diachronic relationships between research areas and is able to detect clusters of topics that exhibit dynamics correlated with the emergence of new research topics. Here we also present the Advanced Clique Percolation Method (ACPM), a new community detection algorithm developed specifically for supporting this task. Augur was evaluated on a gold standard of 1,408 debutant topics in the 2000-2011 timeframe and outperformed four alternative approaches in terms of both precision and recall

Analisi dell'insufficienza delle reti di drenaggio urbano

L’impermeabilizzazione del territorio, a seguito della realizzazione di nuovi insediamenti abitativi o industriali, ha messo in evidenza diverse problematiche connesse con lo smaltimento delle acque meteoriche da tali aree. In particolare si possono avere gravi conseguenze sia idrauliche, quale l’insufficienza delle reti di fognatura esistenti e dei corsi d’acqua recettori, sia ambientali come la necessità di trattare la frazione più inquinata delle acque meteoriche e di ridurre i volumi idrici ed i carichi inquinanti immessi nei corsi d’acqua attraverso gli scaricatori di piena. Queste conseguenze possono essere controllate inserendo nelle reti di collettamento manufatti che abbiano la funzione di invasare provvisoriamente una parte dei volumi idrici derivanti dagli eventi meteorici, per inviarli successivamente alla depurazione o per restituirli alla rete a valle e al ricettore finale con portata ridotta e con essi compatibile

2100 AI: Reflections on the mechanisation of scientific discovery

The pace of research is nowadays extremely intensive, with datasets and publications being published at an unprecedented rate. In this context data science, artificial intelligence, machine learning and big data analytics are providing researchers with new automatic techniques which not only help them to manage this flow of information but are also able to identify automatically interesting patterns and insights in this vast sea of information. However, the emergence of mechanised scientific discovery is likely to dramatically change the way we do science, thus introducing and amplifying serious societal implications on the role of researchers themselves, which need to be analysed thoroughly

Los circuitos lingüísticos de la publicación científica latinoamericana

Dado el papel actual de la producción científica publicada en revistas, es fundamental comprender sus patrones de circulación lingüística. Para ello, examinamos las revistas y artículos incluidos en Scopus y Web of Science para demostrar su falta de  representatividad y diversidad, especialmente para la producción científica latinoamericana. Uno de los principales objetivos de este trabajo esvisibilizar un corpus de producción científica publicado en revistas  latinoamericanas. Para ello, analizamos más de 900 mil artículos y 1.720 revistas científicas. Tanto el volumen de artículos como el número de revistas analizadas revelan un espacio  dinámico de circulación regional con fuertes raíces  sociohistóricas,  caracterizado por un acceso abierto no comercial y predominantemente multilingüe. Partiendo del concepto de circuito lingüístico, concluimos ilustrando la importancia de este multilingüismo creciente para el desarrollo y la internacionalización de la ciencia latinoamericana.Dado o papel atual da produção  científica publicada em periódicos, é essencial compreender seus padrões de circulação linguística. Para tanto, examinamos as revistas e artigos incluídos no Scopus e na Web of Science para demonstrar sua falta de representação e diversidade,  especialmente, para a produção científica latino-americana. Um dos principais objetivos deste trabalho é tornar visível um corpus de produção científica publicado em periódicos latino-americanos. Para isso, analisamos mais de 900 mil artigos e 1.720 periódicos  científicos. Tanto o volume de artigos quanto o número de periódicos analisados revelam um espaço de circulação regional dinâmico com fortes raízes sócio-históricas, caracterizado por um acesso aberto não comercial e predominantemente multilíngue. A partir do conceito de circuito linguístico, concluímos  ilustrando a importância desse crescente multilinguismo para o desenvolvimento e a  internacionalização da ciência latino-americana.Given the current role of scientific production published in journals, it is essential to understand their linguistic circulation patterns. To this end, we examined the journals and articles included in Scopus and Web of Science to demonstrate their lack of representation and diversity, especiallyfor Latin American scientific  production. One of the main objectives of this work is to make visible a corpus of scientific production published in Latin America. To this end, we analyzed more than 900,000 articles and 1.720 scientific journals. Both the volume of articles and the number of journals analyzed reveal a dynamic regional circulation space with strong socio-historical roots, characterized by non-commercial open access and  predominantly multilingual. From theconcept of linguistic circuit, we  conclude how important is this  increasing multilingualism for the development and internationalization of Latin American science

Early Detection and Forecasting of Research Trends

Identifying and forecasting research trends is of critical importance for a variety of stakeholders, including researchers, academic publishers, institutional funding bodies, companies operating in the innovation space and others. Currently, this task is performed either by domain experts, with the assistance of tools for exploring research data, or by automatic approaches. The constant increase of research data makes the second solution more appropriate, howeverautomatic methods suffer from a number of limitations. For instance, they are unable to detect emerging but yet unlabelled research areas (e.g., Semantic Web before 2000). Furthermore, they usually quantify the popularity of a topic simply in terms of the number of related publications or authors for each year; hence they can provide good forecasts only on trends which have existed for at least 3-4 years. This doctoral work aims at solving these limitations by providing a novel approach for the early detection and forecasting of research trends that will take advantage of the rich variety of semantic relationships between research entities (e.g., authors, workshops, communities) and of social media data (e.g., tweets, blogs)

Mixing and segregation in fluidized bed thermochemical conversion of biomass

The recent shift in policy intentions catalysed by COP21 is stimulating the much-needed global energy transition giving new momentum to the move towards a lower-carbon and more efficient energy system. Bio-based energy and chemicals are taking the lead in the progress toward extensive replacement of fossil resources with renewables. Fluidized bed thermochemical conversion of biomass (combustion, gasification, pyrolysis) displays a long record of successes, spanning from lab- to industrial scales, and stems out as the most viable pathway for the exploitation of biogenic fuels, either alone or in combination with fossil fuels. In spite of its diffusion, there are still open design and operational issues that are largely related to segregation and mixing of solid and gas phases in fluidized beds and effectiveness of multiphase contacting patterns. The common claim of fluidized beds being well stirred/well controlled environments for heterogeneous and gas-phase reactions falls short when applied to processing of biomass fuels. The lecture aims at providing a comprehensive framework of fundamental phenomena affecting mixing/segregation of phases during thermochemical processing of biomass, and of their interlinks. The basic processes include patterns and kinetics of biomass devolatilization, particle and volatile matter segregation along and across the reaction chamber, particle attrition/fragmentation and generation of fine particulates, the diversity of gasification patterns and rates, as related to chemical composition and morphology of the parent biogenic fuels. Segregation brings about important consequences in terms of temperature uniformity, of proper control of heterogeneous and gas-phase reaction pathways, of ash behaviour, of pollutant emissions, of plant operability and dependability. Measures to counteract segregation, including pre-processing of biomass and/or appropriate control of bed hydrodynamics, will also be surveyed from the fundamental and applied standpoints

Classifying Research Papers with the Computer Science Ontology

Ontologies of research areas are important tools for characterising, exploring and analysing the research landscape. We recently released the Computer Science Ontology (CSO), a large-scale, automatically generated ontology of research areas, which includes about 26K topics and 226K semantic relationships. CSO currently powers several tools adopted by the Springer Nature editorial team and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends. As an effort to encourage the usage of CSO, we have developed the CSO Portal, a web application that enables users to download, explore, and provide granular feedbacks at different levels of the ontology. In this paper, we present the CSO Classifier, an application for automatically classifying academic papers according to the rich taxonomy of topics from CSO. The aim is to facilitate the adoption of CSO across the various communities engaged with scholarly data and to foster the development of new applications based on this knowledge base