Metainformation scenarios in Digital Humanities: Characterization and conceptual modelling strategies

Requirements for the analysis, interpretation and reuse of information are becoming more and more ambitious as we generate larger and more complex datasets. This is leading to the development and widespread use of information about information, often called metainformation (or metadata) in most disciplines. The Digital Humanities are not an exception. We often assume that metainformation helps us in documenting information for future reference by recording who has created it, when and how, among other aspects. We also assume that recording metainformation will facilitate the tasks of interpreting information at later stages. However, some works have identified some issues with existing metadata approaches, related to 1) the proliferation of too many “standards” and difficulties to choose between them; 2) the generalized assumption that metadata and data (or metainformation and information) are essentially different, and the subsequent development of separate sets of languages and tools for each (introducing redundant models); and 3) the combination of conceptual and implementation concerns within most approaches, violating basic engineering principles of modularity and separation of concerns. Some of these problems are especially relevant in Digital Humanities. In addition, we argue here that the lack of characterization of the scenarios in which metainformation plays a relevant role in humanistic projects often results in metainformation being recorded and managed without a specific purpose in mind. In turn, this hinders the process of decision making on issues such as what metainformation must be recorded in a specific project, and how it must be conceptualized, stored and managed. This paper presents a review of the most used metadata approaches in Digital Humanities and, taking a conceptual modelling perspective, analyses their major issues as outlined above. It also describes what the most common scenarios for the use of metainformation in Digital Humanities are, presenting a characterization that can assist in the setting of goals for metainformation recording and management in each case. Based on these two aspects, a new approach is proposed for the conceptualization, recording and management of metainformation in the Digital Humanities, using the ConML conceptual modelling language, and adopting the overall view that metainformation is not essentially different to information. The proposal is validated in Digital Humanities scenarios through case studies employing real-world datasetsThis work was partially supported by Spanish Ministry of Economy, Industry and Competitiveness under its Competitive Juan de la Cierva Postdoctoral Research Programme (FJCI-2016-28032)S

Future SDI – Impulses from Geoinformatics Research and IT Trends

The term Spatial Data Infrastructure (SDI) was defined in the nineties as a set of policies, technologies and institutional arrangements for improving the availability and accessibility of spatial data and information. SDIs are typically driven by governmental organizations, and thus follow top-down structures based on regulations and agreements. The drawback is that it renders SDIs less easily capable of evolving with new technological trends. While organizations are still struggling to implement SDIs, the World Wide Web is increasingly developing into a Geospatial Web, i.e. one that extensively supports the spatial and temporal aspects of information. This article is our contribution to the discussion on the future technological directions in the field of SDIs. We give a conceptual view of the dynamics of both SDIs and the Geospatial Web. We present a picture of the SDI of the future, one which benefits from these developments, based on an analysis of geoinformatics research topics and current ICT trends. We provide recommendations on how to improve the adaptability and usability of SDIs as to facilitate the assimilation of new ICT developments and to leverage self-reinforcing growth

Revisiting Urban Dynamics through Social Urban Data:

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 geographic systems that are difficult to detect in traditional urban data (e.g. census data). However, as the available sources increase in number, the produced datasets increase in diversity. Besides heterogeneity, emerging social urban data are also characterized by multidimensionality. The latter means that the information they contain may simultaneously address spatial, social, temporal, and topical attributes of people and places. Therefore, integration and geospatial (statistical) analysis of multidimensional data remain a challenge. The question which, then, arises is how to integrate heterogeneous and multidimensional social urban data into the analysis of human activity dynamics in cities? To address the above challenge, this thesis proposes the design of a framework of novel methods and tools for the integration, visualization, and exploratory analysis of large-scale and heterogeneous social urban data to facilitate the understanding of urban dynamics. The research focuses particularly on the spatiotemporal dynamics of human activity in cities, as inferred from different sources of social urban data. The main objective is to provide new means to enable the incorporation of heterogeneous social urban data into city analytics, and to explore the influence of emerging data sources on the understanding of cities and their dynamics.  In mitigating the various heterogeneities, a methodology for the transformation of heterogeneous data for cities into multidimensional linked urban data is, therefore, designed. The methodology follows an ontology-based data integration approach and accommodates a variety of semantic (web) and linked data technologies. A use case of data interlinkage is used as a demonstrator of the proposed methodology. The use case employs nine real-world large-scale spatiotemporal data sets from three public transportation organizations, covering the entire public transport network of the city of Athens, Greece.  To further encourage the consumption of linked urban data by planners and policy-makers, a set of webbased tools for the visual representation of ontologies and linked data is designed and developed. The tools – comprising the OSMoSys framework – provide graphical user interfaces for the visual representation, browsing, and interactive exploration of both ontologies and linked urban data.   After introducing methods and tools for data integration, visual exploration of linked urban data, and derivation of various attributes of people and places from different social urban data, it is examined how they can all be combined into a single platform. To achieve this, a novel web-based system (coined SocialGlass) for the visualization and exploratory analysis of human activity dynamics is designed. The system combines data from various geo-enabled social media (i.e. Twitter, Instagram, Sina Weibo) and LBSNs (i.e. Foursquare), sensor networks (i.e. GPS trackers, Wi-Fi cameras), and conventional socioeconomic urban records, but also has the potential to employ custom datasets from other sources. A real-world case study is used as a demonstrator of the capacities of the proposed web-based system in the study of urban dynamics. The case study explores the potential impact of a city-scale event (i.e. the Amsterdam Light festival 2015) on the activity and movement patterns of different social categories (i.e. residents, non-residents, foreign tourists), as compared to their daily and hourly routines in the periods  before and after the event. The aim of the case study is twofold. First, to assess the potential and limitations of the proposed system and, second, to investigate how different sources of social urban data could influence the understanding of urban dynamics. The contribution of this doctoral thesis is the design and development of a framework of novel methods and tools that enables the fusion of heterogeneous multidimensional data for cities. The framework could foster planners, researchers, and policy makers to capitalize on the new possibilities given by emerging social urban data. Having a deep understanding of the spatiotemporal dynamics of cities and, especially of the activity and movement behavior of people, is expected to play a crucial role in addressing the challenges of rapid urbanization. Overall, the framework proposed by this research has potential to open avenues of quantitative explorations of urban dynamics, contributing to the development of a new science of cities

Linked Open Data - Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project

Database Management; Artificial Intelligence (incl. Robotics); Information Systems and Communication Servic

The Nexus Between Security Sector Governance/Reform and Sustainable Development Goal-16

This Security Sector Reform (SSR) Paper offers a universal and analytical perspective on the linkages between Security Sector Governance (SSG)/SSR (SSG/R) and Sustainable Development Goal-16 (SDG-16), focusing on conflict and post-conflict settings as well as transitional and consolidated democracies. Against the background of development and security literatures traditionally maintaining separate and compartmentalized presence in both academic and policymaking circles, it maintains that the contemporary security- and development-related challenges are inextricably linked, requiring effective measures with an accurate understanding of the nature of these challenges. In that sense, SDG-16 is surely a good step in the right direction. After comparing and contrasting SSG/R and SDG-16, this SSR Paper argues that human security lies at the heart of the nexus between the 2030 Agenda of the United Nations (UN) and SSG/R. To do so, it first provides a brief overview of the scholarly and policymaking literature on the development-security nexus to set the background for the adoption of The Agenda 2030. Next, it reviews the literature on SSG/R and SDGs, and how each concept evolved over time. It then identifies the puzzle this study seeks to address by comparing and contrasting SSG/R with SDG-16. After making a case that human security lies at the heart of the nexus between the UN’s 2030 Agenda and SSG/R, this book analyses the strengths and weaknesses of human security as a bridge between SSG/R and SDG-16 and makes policy recommendations on how SSG/R, bolstered by human security, may help achieve better results on the SDG-16 targets. It specifically emphasizes the importance of transparency, oversight, and accountability on the one hand, and participative approach and local ownership on the other. It concludes by arguing that a simultaneous emphasis on security and development is sorely needed for addressing the issues under the purview of SDG-16