Named Entity Resolution in Personal Knowledge Graphs

Entity Resolution (ER) is the problem of determining when two entities refer to the same underlying entity. The problem has been studied for over 50 years, and most recently, has taken on new importance in an era of large, heterogeneous 'knowledge graphs' published on the Web and used widely in domains as wide ranging as social media, e-commerce and search. This chapter will discuss the specific problem of named ER in the context of personal knowledge graphs (PKGs). We begin with a formal definition of the problem, and the components necessary for doing high-quality and efficient ER. We also discuss some challenges that are expected to arise for Web-scale data. Next, we provide a brief literature review, with a special focus on how existing techniques can potentially apply to PKGs. We conclude the chapter by covering some applications, as well as promising directions for future research.Comment: To appear as a book chapter by the same name in an upcoming (Oct. 2023) book `Personal Knowledge Graphs (PKGs): Methodology, tools and applications' edited by Tiwari et a

Distributed Governance: a Principal-Agent Approach to Data Governance -- Part 1 Background & Core Definitions

To address the need for regulating digital technologies without hampering innovation or pre-digital transformation regulatory frameworks, we provide a model to evolve Data governance toward Information governance and precise the relation between these two terms. This model bridges digital and non-digital information exchange. By considering the question of governed data usage through the angle of the Principal-Agent problem, we build a distributed governance model based on Autonomous Principals defined as entities capable of choice, therefore capable of exercising a transactional sovereignty. Extending the legal concept of the privacy sphere to a functional equivalent in the digital space leads to the construction of a digital self to which rights and accountability can be attached. Ecosystems, defined as communities of autonomous principals bound by a legitimate authority, provide the basis of interacting structures of increasing complexity endowed with a self-replicating property that mirrors physical world governance systems. The model proposes a governance concept for multi-stakeholder information systems operating across jurisdictions. Using recent software engineering advances in decentralised authentication and semantics, we provide a framework, Dynamic Data Economy to deploy a distributed governance model embedding checks and balance between human and technological governance. Domain specific governance models are left for further publications. Similarly, the technical questions related to the connection between a digital-self and its physical world controller (e.g biometric binding) will be treated in upcoming publications.Comment: 27 pages, 20 figures, basis of presentation at University of Geneva's lectures on Information Securit

Location Reference Recognition from Texts: A Survey and Comparison

A vast amount of location information exists in unstructured texts, such as social media posts, news stories, scientific articles, web pages, travel blogs, and historical archives. Geoparsing refers to recognizing location references from texts and identifying their geospatial representations. While geoparsing can benefit many domains, a summary of its specific applications is still missing. Further, there is a lack of a comprehensive review and comparison of existing approaches for location reference recognition, which is the first and core step of geoparsing. To fill these research gaps, this review first summarizes seven typical application domains of geoparsing: geographic information retrieval, disaster management, disease surveillance, traffic management, spatial humanities, tourism management, and crime management. We then review existing approaches for location reference recognition by categorizing these approaches into four groups based on their underlying functional principle: rule-based, gazetteer matching–based, statistical learning-–based, and hybrid approaches. Next, we thoroughly evaluate the correctness and computational efficiency of the 27 most widely used approaches for location reference recognition based on 26 public datasets with different types of texts (e.g., social media posts and news stories) containing 39,736 location references worldwide. Results from this thorough evaluation can help inform future methodological developments and can help guide the selection of proper approaches based on application needs

A Geographic Database Design for Humanitarian Assistance and Disaster Response

The international humanitarian assistance community responds to a wide variety of crises and disasters that are challenging in their variability, scale, timelines, resources, and politics. The implementation of a geographic database model, or Geodatabase, of geographic information resources will provide emergency responders with a functional relational database to support disaster response missions. The Geodatabase will be compact and deployable, improve functionality and efficiency, reduce error, increase standardization, and record an institutional knowledge base. Distributing the Geodatabase model in the form of a WebGIS website can additionally facilitate organizational communication and decision-making during the phases of emergency management by providing a thematic attribute query search capability. This Project will serve as a proof-of-concept design for future potential implementation and enhancement of the recommended models. The December 26, 2004 tsunami disaster in Indonesia and the surrounding region is the primary study area for this project. The recommendations outlined in this Project will help to support the initial data delivery steps of future humanitarian assistance and disaster response missions

Rover-II: A Context-Aware Middleware for Pervasive Computing Environment

It is well recognized that context plays a significant role in all human endeavors. All decisions are based on information which has to be interpreted in context. By making information systems context-aware we can have systems that significantly enhance human capabilities to make critical decisions. A major challenge of context-aware systems is to balance usability with generality and extensibility. The relevant context changes depending on the particular application. The model used to represent the context and its relationship to entities must be general enough to allow additions of context categories without redesign while remaining usable across many applications. Also, while efforts are put in by application designers and developers to make applications context-aware, these efforts are customized to specific needs of the target application, and only certain common contexts like location and time are taken into account. Therefore, a general framework is called for that can (i) efficiently maintain, represent and integrate contextual information, (ii) act as an integration platform where different applications can share contexts and (iii) provide relevant services to make efficient use of the contextual information. This dissertation presents: * a generic and effective context model - Rover Context Model (RoCoM) that is structured around four primitives: entities, events, relationships, and activities; and practically usable through the concept of templates, * a flexible, extensible and generic ontology - Rover Context Model Ontology (RoCoMO) supporting the model, that addresses the shortcomings of existing ontologies, * an effective mechanism of modeling the context of a situation, through the concept of relevant context, with the help of situation graph, efficiently handling and making best use of context information, * a context middleware - Rover-II, which serves as a framework for contextual information integration, that could be used not just to store and compile the contextual information, but also integrate relevant services to enhance the context information; and more importantly, enable sharing of context among the applications subscribed to it, * the initial design and implementation of a distributed architecture for Rover-II, following a P2P arrangement inspired from Tapestry, The above concepts are illustrated through M-Urgency, a context-aware public safety system that has been deployed at the University of Maryland Police Department

Global Health Security in an Era of Explosive Pandemic Potential

Pandemics pose a significant risk to security, economic stability, and development. Annualized expected losses from pandemics are estimated at $60 billion per year. Despite the certainty and magnitude of the threat, the global community has significantly underestimated and underinvested in avoidance of pandemic threats. We cannot wait or continue with the status quo, in which we pay attention to infectious disease threats only when they are at their peak and then are complacent and remain vulnerable until the next major outbreak. To reinforce and sustain international focus, funding, and action, it is crucial that pandemics rise to the level of “high politics,” becoming standing agenda items for political actors. In this article, we make the case for fundamental reform of the international system to safeguard global health security. We build on the action agenda offered by four international commissions formed in the wake of the Ebola epidemic, calling for the recommended “peace dividend” (an annual incremental investment of$4.5 billion – 65 cents per person) to strengthen global preparedness, for the United Nations to play a greater role in responding to major global health and humanitarian emergencies, and for an effective and efficient R&D strategy with multiple stakeholders—governments, academics, industry, and civil society—identifying R&D priorities and leading a coordinated response. If our action plan were adopted, it would safeguard the global population far better against infectious disease threats. It would reap dividends in security, development, and productivity