11,818 research outputs found
Folks in Folksonomies: Social Link Prediction from Shared Metadata
Web 2.0 applications have attracted a considerable amount of attention
because their open-ended nature allows users to create light-weight semantic
scaffolding to organize and share content. To date, the interplay of the social
and semantic components of social media has been only partially explored. Here
we focus on Flickr and Last.fm, two social media systems in which we can relate
the tagging activity of the users with an explicit representation of their
social network. We show that a substantial level of local lexical and topical
alignment is observable among users who lie close to each other in the social
network. We introduce a null model that preserves user activity while removing
local correlations, allowing us to disentangle the actual local alignment
between users from statistical effects due to the assortative mixing of user
activity and centrality in the social network. This analysis suggests that
users with similar topical interests are more likely to be friends, and
therefore semantic similarity measures among users based solely on their
annotation metadata should be predictive of social links. We test this
hypothesis on the Last.fm data set, confirming that the social network
constructed from semantic similarity captures actual friendship more accurately
than Last.fm's suggestions based on listening patterns.Comment: http://portal.acm.org/citation.cfm?doid=1718487.171852
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Towards evaluation design for smart city development
Smart city developments integrate digital, human, and physical systems in the built environment. With growing urbanization and widespread developments, identifying suitable evaluation methodologies is important. Case-study research across five UK cities - Birmingham, Bristol, Manchester, Milton Keynes and Peterborough - revealed that city evaluation approaches were principally project-focused with city-level evaluation plans at early stages. Key challenges centred on selecting suitable evaluation methodologies to evidence urban value and outcomes, addressing city authority requirements. Recommendations for evaluation design draw on urban studies and measurement frameworks, capitalizing on big data opportunities and developing appropriate, valid, credible integrative approaches across projects, programmes and city-level developments
Framework for sustainability assessment of industrial processes with multi-scale technology at design level: microcapsules production process
In a world with limited resources and serious environmental, social and economical impacts, a more sustainable life style is everyday more important. Therefore, the general objective of this work is to develop a methodological procedure for eco-efficiency and sustainability assessment of industrial processes with multi-scale technology at design level. The methodology developed follows the ISO 14040 series for environmental LCA standard. To integrate the three pillars of sustainability the analytical hierarchical process was used. The results are represented in a triple bottom line framework. The methodology was applied to the case study "production of perfume-containing microcapsules" and different scenarios were assessed and compared. Several sustainability indicators were chosen to analyze the impacts. The results showed that this methodology can be used as a decision making tool for sustainability reporting. It can be applied to any process choosing in each case the corresponding set of inventory data and sustainability impact indicators.En un mundo con recursos limitados y graves impactos ambientales, sociales y económicos, un estilo de vida más sostenible es cada día más importante. Debido a esto, el objetivo general de este trabajo es desarrollar un procedimiento metodológico para evaluar eco-eficiencia y sostenibilidad de procesos industriales con tecnología multi-escala a nivel de diseño. La metodología desarrollada sigue la serie ISO 14040 para el medio ambiente. Se utilizó el proceso analítico jerárquico para integrar los tres pilares de sostenibilidad. Los resultados se presentan en un balance triple. La metodología se aplicó al caso de estudio "producción de micro-cápsulas que contienen perfume" y se analizaron y compararon diferentes escenarios. Se seleccionaron diversos indicadores de sostenibilidad para analizar los impactos. Los resultados demostraron que esta metodología puede ser utilizada como herramienta de toma de decisiones y que puede aplicarse a cualquier proceso seleccionando, en cada caso, los datos del inventario y los indicadores
A stigmergy-based analysis of city hotspots to discover trends and anomalies in urban transportation usage
A key aspect of a sustainable urban transportation system is the
effectiveness of transportation policies. To be effective, a policy has to
consider a broad range of elements, such as pollution emission, traffic flow,
and human mobility. Due to the complexity and variability of these elements in
the urban area, to produce effective policies remains a very challenging task.
With the introduction of the smart city paradigm, a widely available amount of
data can be generated in the urban spaces. Such data can be a fundamental
source of knowledge to improve policies because they can reflect the
sustainability issues underlying the city. In this context, we propose an
approach to exploit urban positioning data based on stigmergy, a bio-inspired
mechanism providing scalar and temporal aggregation of samples. By employing
stigmergy, samples in proximity with each other are aggregated into a
functional structure called trail. The trail summarizes relevant dynamics in
data and allows matching them, providing a measure of their similarity.
Moreover, this mechanism can be specialized to unfold specific dynamics.
Specifically, we identify high-density urban areas (i.e hotspots), analyze
their activity over time, and unfold anomalies. Moreover, by matching activity
patterns, a continuous measure of the dissimilarity with respect to the typical
activity pattern is provided. This measure can be used by policy makers to
evaluate the effect of policies and change them dynamically. As a case study,
we analyze taxi trip data gathered in Manhattan from 2013 to 2015.Comment: Preprin
Standardization Framework for Sustainability from Circular Economy 4.0
The circular economy (CE) is widely known as a way to implement and achieve sustainability, mainly due to its contribution towards the separation of biological and technical nutrients under cyclic industrial metabolism. The incorporation of the principles of the CE in the links of the value chain of the various sectors of the economy strives to ensure circularity, safety, and efficiency. The framework proposed is aligned with the goals of the 2030 Agenda for Sustainable Development regarding the orientation towards the mitigation and regeneration of the metabolic rift by considering a double perspective. Firstly, it strives to conceptualize the CE as a paradigm of sustainability. Its principles are established, and its techniques and tools are organized into two frameworks oriented towards causes (cradle to cradle) and effects (life cycle assessment), and these are structured under the three pillars of sustainability, for their projection within the proposed framework. Secondly, a framework is established to facilitate the implementation of the CE with the use of standards, which constitute the requirements, tools, and indicators to control each life cycle phase, and of key enabling technologies (KETs) that add circular value 4.0 to the socio-ecological transition
Theory and Practice of Data Citation
Citations are the cornerstone of knowledge propagation and the primary means
of assessing the quality of research, as well as directing investments in
science. Science is increasingly becoming "data-intensive", where large volumes
of data are collected and analyzed to discover complex patterns through
simulations and experiments, and most scientific reference works have been
replaced by online curated datasets. Yet, given a dataset, there is no
quantitative, consistent and established way of knowing how it has been used
over time, who contributed to its curation, what results have been yielded or
what value it has.
The development of a theory and practice of data citation is fundamental for
considering data as first-class research objects with the same relevance and
centrality of traditional scientific products. Many works in recent years have
discussed data citation from different viewpoints: illustrating why data
citation is needed, defining the principles and outlining recommendations for
data citation systems, and providing computational methods for addressing
specific issues of data citation.
The current panorama is many-faceted and an overall view that brings together
diverse aspects of this topic is still missing. Therefore, this paper aims to
describe the lay of the land for data citation, both from the theoretical (the
why and what) and the practical (the how) angle.Comment: 24 pages, 2 tables, pre-print accepted in Journal of the Association
for Information Science and Technology (JASIST), 201
Managing contextual information in semantically-driven temporal information systems
Context-aware (CA) systems have demonstrated the provision of a robust solution for personalized information delivery in the current content-rich and dynamic information age we live in. They allow software agents to autonomously interact with users by modeling the user’s environment (e.g. profile, location, relevant public information etc.) as dynamically-evolving and interoperable contexts. There is a flurry of research activities in a wide spectrum at context-aware research areas such as managing the user’s profile, context acquisition from external environments, context storage, context representation and interpretation, context service delivery and matching of context attributes to users‘ queries etc. We propose SDCAS, a Semantic-Driven Context Aware System that facilitates public services recommendation to users at temporal location. This paper focuses on information management and service recommendation using semantic technologies, taking into account the challenges of relationship complexity in temporal and contextual information
Open semantic service networks
Online service marketplaces will soon be part of the economy to scale the provision of specialized multi-party services through automation and standardization. Current research, such as the *-USDL service description language family, is already defining the basic building blocks to model the next generation of business services. Nonetheless, the developments being made do not target to interconnect services via service relationships. Without the concept of relationship, marketplaces will be seen as mere functional silos containing service descriptions. Yet, in real economies, all services are related and connected. Therefore, to address this gap we introduce the concept of open semantic service network (OSSN), concerned with the establishment of rich relationships between services. These networks will provide valuable knowledge on the global service economy, which can be exploited for many socio-economic and scientific purposes such as service network analysis, management, and control
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