Relevant bibliographies by topics / Linked Open Dynamic Data

Academic literature on the topic 'Linked Open Dynamic Data'

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Published: 14 March 2023

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Journal articles on the topic "Linked Open Dynamic Data"

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Şah, Melike, and Wendy Hall. "Dynamic Linking and Personalization on the Web using Linked Open Data." International Journal on Semantic Web and Information Systems 9, no. 2 (April 2013): 31–61. http://dx.doi.org/10.4018/jswis.2013040102.

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This paper presents a novel Semantic Web browser, called SemWeB. SemWeB supports Web browsing using Linked Open Data and personalization. This is the first time a Semantic Web browser combines the advances in Adaptive Hypermedia (i.e. personalization) and Linked Open Data. In particular, users are provided with a personalized and semantically rich Web browsing experience. For example, SemWeB supplies goal-based adaptive information retrieval from the LOD, adaptive link recommendation using a novel semantic relatedness measure and adaptive content creation. A user based study was used to assess the value of LOD-based hyperlinks and personally relevant content compared with a standard Web browser (Firefox). Results showed that users were able to browse and view more relevant information, as well as, value significance of LOD-based hyperlinks and personalized content in comparison to a standard Web browser.
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Corno, Fulvio, and Faisal Razzak. "Publishing LO(D)D: Linked Open (Dynamic) Data for Smart Sensing and Measuring Environments." Procedia Computer Science 10 (2012): 381–88. http://dx.doi.org/10.1016/j.procs.2012.06.050.

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Triperina, Evangelia, Cleo Sgouropoulou, Ioannis Xydas, Olivier Terraz, and Georgios Miaoulis. "Creating the Context for Exploiting Linked Open Data in Multidimensional Academic Ranking." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 3, no. 3 (October 19, 2015): 33. http://dx.doi.org/10.3991/ijes.v3i3.5023.

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Academia is a complex socio-technical system with multiple aspects and constituents that involve various stakeholders. In order to address stakeholders’ needs and to assist the institutional accountability, this complexity should be considered during the development of academic services. We have designed a dynamic multidimensional ranking approach, easily modifiable to address user requirements, so as to assess and compare the university performance with a clear view to the support of effective institutional strategic planning and policy making. Our approach comprises the following components: the AcademIS ontology to model the academic domain and its multiple dimensions, the AcademIS Information System to manage and display the academic information, published in Linked Open Data format and the visual-aided Multiple Criteria Decision Making component, to evaluate and rank the performance of the academic units. The data are aggregated from several sources, in different formats, LODified by our system, and presented to the user by the interface to ultimately assist the decision making process.
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Zhu, Yueqin, Wenwen Zhou, Yang Xu, Ji Liu, and Yongjie Tan. "Intelligent Learning for Knowledge Graph towards Geological Data." Scientific Programming 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/5072427.

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Knowledge graph (KG) as a popular semantic network has been widely used. It provides an effective way to describe semantic entities and their relationships by extending ontology in the entity level. This article focuses on the application of KG in the traditional geological field and proposes a novel method to construct KG. On the basis of natural language processing (NLP) and data mining (DM) algorithms, we analyze those key technologies for designing a KG towards geological data, including geological knowledge extraction and semantic association. Through this typical geological ontology extracting on a large number of geological documents and open linked data, the semantic interconnection is achieved, KG framework for geological data is designed, application system of KG towards geological data is constructed, and dynamic updating of the geological information is completed accordingly. Specifically, unsupervised intelligent learning method using linked open data is incorporated into the geological document preprocessing, which generates a geological domain vocabulary ultimately. Furthermore, some application cases in the KG system are provided to show the effectiveness and efficiency of our proposed intelligent learning approach for KG.
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Thomas, Stacy, Tara Lichtenberg, Kristen Dang, Michael Fitzsimons, Robert L. Grossman, Ritika Kundra, Jessica A. Lavery, et al. "Linked Entity Attribute Pair (LEAP): A Harmonization Framework for Data Pooling." JCO Clinical Cancer Informatics, no. 4 (September 2020): 691–99. http://dx.doi.org/10.1200/cci.20.00037.

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PURPOSE As data-sharing projects become increasingly frequent, so does the need to map data elements between multiple classification systems. A generic, robust, shareable architecture will result in increased efficiency and transparency of the mapping process, while upholding the integrity of the data. MATERIALS AND METHODS The American Association for Cancer Research’s Genomics Evidence Neoplasia Information Exchange (GENIE) collects clinical and genomic data for precision cancer medicine. As part of its commitment to open science, GENIE has partnered with the National Cancer Institute’s Genomic Data Commons (GDC) as a secondary repository. After initial efforts to submit data from GENIE to GDC failed, we realized the need for a solution to allow for the iterative mapping of data elements between dynamic classification systems. We developed the Linked Entity Attribute Pair (LEAP) database framework to store and manage the term mappings used to submit data from GENIE to GDC. RESULTS After creating and populating the LEAP framework, we identified 195 mappings from GENIE to GDC requiring remediation and observed a 28% reduction in effort to resolve these issues, as well as a reduction in inadvertent errors. These results led to a decrease in the time to map between OncoTree, the cancer type ontology used by GENIE, and International Classification of Disease for Oncology, 3rd Edition, used by GDC, from several months to less than 1 week. CONCLUSION The LEAP framework provides a streamlined mapping process among various classification systems and allows for reusability so that efforts to create or adjust mappings are straightforward. The ability of the framework to track changes over time streamlines the process to map data elements across various dynamic classification systems.
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Hong, Sung Min, Kyoung Nam Ha, and Joon-Young Kim. "Dynamics Modeling and Motion Simulation of USV/UUV with Linked Underwater Cable." Journal of Marine Science and Engineering 8, no. 5 (April 30, 2020): 318. http://dx.doi.org/10.3390/jmse8050318.

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This paper describes a study on the dynamic modeling and the motion simulation of an unmanned ocean platform to overcome the limitations of existing unmanned ocean platforms for ocean exploration. The proposed unmanned ocean vehicle combines an unmanned surface vehicle and unmanned underwater vehicle with an underwater cable. This platform is connected by underwater cable, and the forces generated in each platform can influence each other’s dynamic motion. Therefore, before developing and operating an unmanned ocean platform, it is necessary to derive a dynamic equation and analyze dynamic behavior using it. In this paper, Newton’s second law and lumped-mass method are used to derive the equations of motion of unmanned surface vehicle, unmanned underwater vehicle, and underwater cable. As the underwater cable among the components of the unmanned ocean platform is expected to affect the motion of unmanned surface vehicle and unmanned underwater vehicle, the similarity of modeling is described by comparing with the cable modeling results and the experimental data. Finally, we constructed a dynamic simulator using Matlab and Simulink, and analyzed the dynamic behavior of the unmanned ocean platform through open-loop simulation.
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Sateli, Bahar, and René Witte. "Semantic representation of scientific literature: bringing claims, contributions and named entities onto the Linked Open Data cloud." PeerJ Computer Science 1 (December 9, 2015): e37. http://dx.doi.org/10.7717/peerj-cs.37.

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Motivation.Finding relevant scientific literature is one of the essential tasks researchers are facing on a daily basis. Digital libraries and web information retrieval techniques provide rapid access to a vast amount of scientific literature. However, no further automated support is available that would enable fine-grained access to the knowledge ‘stored’ in these documents. The emerging domain ofSemantic Publishingaims at making scientific knowledge accessible to both humans and machines, by adding semantic annotations to content, such as a publication’s contributions, methods, or application domains. However, despite the promises of better knowledge access, the manual annotation of existing research literature is prohibitively expensive for wide-spread adoption. We argue that a novel combination of three distinct methods can significantly advance this vision in a fully-automated way: (i) Natural Language Processing (NLP) forRhetorical Entity(RE) detection; (ii)Named Entity(NE) recognition based on the Linked Open Data (LOD) cloud; and (iii) automatic knowledge base construction for both NEs and REs using semantic web ontologies that interconnect entities in documents with the machine-readable LOD cloud.Results.We present a complete workflow to transform scientific literature into a semantic knowledge base, based on the W3C standards RDF and RDFS. A text mining pipeline, implemented based on the GATE framework, automatically extracts rhetorical entities of typeClaimsandContributionsfrom full-text scientific literature. These REs are further enriched with named entities, represented as URIs to the linked open data cloud, by integrating the DBpedia Spotlight tool into our workflow. Text mining results are stored in a knowledge base through a flexible export process that provides for a dynamic mapping of semantic annotations to LOD vocabularies through rules stored in the knowledge base. We created a gold standard corpus from computer science conference proceedings and journal articles, whereClaimandContributionsentences are manually annotated with their respective types using LOD URIs. The performance of the RE detection phase is evaluated against this corpus, where it achieves an averageF-measure of 0.73. We further demonstrate a number of semantic queries that show how the generated knowledge base can provide support for numerous use cases in managing scientific literature.Availability.All software presented in this paper is available under open source licenses athttp://www.semanticsoftware.info/semantic-scientific-literature-peerj-2015-supplements. Development releases of individual components are additionally available on our GitHub page athttps://github.com/SemanticSoftwareLab.
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Hiranyakorn, Methanee, Saeko Yanaka, Tadashi Satoh, Thunchanok Wilasri, Benchawan Jityuti, Maho Yagi-Utsumi, and Koichi Kato. "NMR Characterization of Conformational Interconversions of Lys48-Linked Ubiquitin Chains." International Journal of Molecular Sciences 21, no. 15 (July 28, 2020): 5351. http://dx.doi.org/10.3390/ijms21155351.

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Ubiquitin (Ub) molecules can be enzymatically connected through a specific isopeptide linkage, thereby mediating various cellular processes by binding to Ub-interacting proteins through their hydrophobic surfaces. The Lys48-linked Ub chains, which serve as tags for proteasomal degradation, undergo conformational interconversions between open and closed states, in which the hydrophobic surfaces are exposed and shielded, respectively. Here, we provide a quantitative view of such dynamic processes of Lys48-linked triUb and tetraUb in solution. The native and cyclic forms of Ub chains are prepared with isotope labeling by in vitro enzymatic reactions. Our comparative NMR analyses using monomeric Ub and cyclic diUb as reference molecules enabled the quantification of populations of the open and closed states for each Ub unit of the native Ub chains. The data indicate that the most distal Ub unit in the Ub chains is the most apt to expose its hydrophobic surface, suggesting its preferential involvement in interactions with the Ub-recognizing proteins. We also demonstrate that a mutational modification of the distal end of the Ub chain can remotely affect the solvent exposure of the hydrophobic surfaces of the other Ub units, suggesting that Ub chains could be unique design frameworks for the creation of allosterically controllable multidomain proteins.
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Voith von Voithenberg, Lena, Carolina Sánchez-Rico, Hyun-Seo Kang, Tobias Madl, Katia Zanier, Anders Barth, Lisa R. Warner, Michael Sattler, and Don C. Lamb. "Recognition of the 3′ splice site RNA by the U2AF heterodimer involves a dynamic population shift." Proceedings of the National Academy of Sciences 113, no. 46 (October 31, 2016): E7169—E7175. http://dx.doi.org/10.1073/pnas.1605873113.

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An essential early step in the assembly of human spliceosomes onto pre-mRNA involves the recognition of regulatory RNA cis elements in the 3′ splice site by the U2 auxiliary factor (U2AF). The large (U2AF65) and small (U2AF35) subunits of the U2AF heterodimer contact the polypyrimidine tract (Py-tract) and the AG-dinucleotide, respectively. The tandem RNA recognition motif domains (RRM1,2) of U2AF65 adopt closed/inactive and open/active conformations in the free form and when bound to bona fide Py-tract RNA ligands. To investigate the molecular mechanism and dynamics of 3′ splice site recognition by U2AF65 and the role of U2AF35 in the U2AF heterodimer, we have combined single-pair FRET and NMR experiments. In the absence of RNA, the RRM1,2 domain arrangement is highly dynamic on a submillisecond time scale, switching between closed and open conformations. The addition of Py-tract RNA ligands with increasing binding affinity (strength) gradually shifts the equilibrium toward an open conformation. Notably, the protein–RNA complex is rigid in the presence of a strong Py-tract but exhibits internal motion with weak Py-tracts. Surprisingly, the presence of U2AF35, whose UHM domain interacts with U2AF65 RRM1, increases the population of the open arrangement of U2AF65 RRM1,2 in the absence and presence of a weak Py-tract. These data indicate that the U2AF heterodimer promotes spliceosome assembly by a dynamic population shift toward the open conformation of U2AF65 to facilitate the recognition of weak Py-tracts at the 3′ splice site. The structure and RNA binding of the heterodimer was unaffected by cancer-linked myelodysplastic syndrome mutants.
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Eren, A. Murat, Özcan C. Esen, Christopher Quince, Joseph H. Vineis, Hilary G. Morrison, Mitchell L. Sogin, and Tom O. Delmont. "Anvi’o: an advanced analysis and visualization platform for ‘omics data." PeerJ 3 (October 8, 2015): e1319. http://dx.doi.org/10.7717/peerj.1319.

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Advances in high-throughput sequencing and ‘omics technologies are revolutionizing studies of naturally occurring microbial communities. Comprehensive investigations of microbial lifestyles require the ability to interactively organize and visualize genetic information and to incorporate subtle differences that enable greater resolution of complex data. Here we introduce anvi’o, an advanced analysis and visualization platform that offers automated and human-guided characterization of microbial genomes in metagenomic assemblies, with interactive interfaces that can link ‘omics data from multiple sources into a single, intuitive display. Its extensible visualization approach distills multiple dimensions of information about each contig, offering a dynamic and unified work environment for data exploration, manipulation, and reporting. Using anvi’o, we re-analyzed publicly available datasets and explored temporal genomic changes within naturally occurring microbial populations throughde novocharacterization of single nucleotide variations, and linked cultivar and single-cell genomes with metagenomic and metatranscriptomic data. Anvi’o is an open-source platform that empowers researchers without extensive bioinformatics skills to perform and communicate in-depth analyses on large ‘omics datasets.
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Dissertations / Theses on the topic "Linked Open Dynamic Data"

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Jain, Prateek. "Linked Open Data Alignment & Querying." Wright State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1345575500.

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Pfeffer, Magnus, and Kai Eckert. "Linked Open Projects." Universitätsbibliothek Chemnitz, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-64786.

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Semantic Web und Linked Data sind in aller Munde. Nach fast einem Jahrzehnt der Entwicklung der Technologien und Erforschung der Möglichkeiten des Semantic Webs rücken nun die Daten in den Mittelpunk, denn ohne diese wäre das Semantic Web nicht mehr als ein theoretisches Konstrukt. Fast wie das World Wide Web ohne Websites. Bibliotheken besitzen mit Normdaten (PND, SWD) und Titelaufnahmen eine Fülle Daten, die sich zur Befüllung des Semantic Web eignen und teilweise bereits für das Semantic Web aufbereitet und zur Nutzung freigegeben wurden. Die Universitätsbibliothek Mannheim hat sich in zwei verschiedenen Projekten mit der Nutzung solcher Daten befasst – allerdings standen diese zu diesem Zeitpunkt noch nicht als Linked Data zur Verfügung. In einem Projekt ging es um die automatische Erschließung von Publikationen auf der Basis von Abstracts, im anderen Projekt um die automatische Klassifikation von Publikationen auf der Basis von Titeldaten. Im Rahmen dieses Beitrags stellen wir die Ergebnisse der Projekte kurz vor, möchten aber im Schwerpunkt auf einen Nebenaspekt eingehen, der sich erst im Laufe dieser Projekte herauskristallisiert hat: Wie kann man die gewonnenen Ergebnisse dauerhaft und sinnvoll zur Nachnutzung durch Dritte präsentieren? Soviel vorweg: Beide Verfahren können und wollen einen Bibliothekar nicht ersetzen. Die Einsatzmöglichkeiten der generierten Daten sind vielfältig. Konkrete Einsätze, zum Beispiel das Einspielen in einen Verbundkatalog, sind aber aufgrund der Qualität und mangelnden Kontrolle der Daten umstritten. Die Bereitstellung dieser Daten als Linked Data im Semantic Web ist da eine naheliegende Lösung – jeder, der die Ergebnisse nachnutzen möchte, kann das tun, ohne dass ein bestehender Datenbestand damit kompromittiert werden könnte. Diese Herangehensweise wirft aber neue Fragen auf, nicht zuletzt auch nach der Identifizierbarkeit der Ursprungsdaten über URIs, wenn diese (noch) nicht als Linked Data zur Verfügung stehen. Daneben erfordert die Bereitstellung von Ergebnisdaten aber auch weitere Maßnahmen, die über die gängige Praxis von Linked Data hinaus gehen: Die Bereitstellung von Zusatzinformationen, die die Quelle und das Zustandekommen dieser Daten näher beschreiben (Provenienzinformationen), aber auch weitere Informationen, die über das zugrunde liegende Metadatenschema meist hinausgehen, wie Konfidenzwerte im Falle eines automatischen Verfahrens der Datenerzeugung. Dazu präsentieren wir Ansätze auf Basis von RDF Reification und Named Graphs und schildern die aktuellen Entwicklungen auf diesem Gebiet, wie sie zum Beispiel in der Provenance Incubator Group des W3C und in Arbeitsgruppen der Dublin Core Metadaten-Initiative diskutiert werden.
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Felix, Juan Manuel. "Esplorando i Linked Open Data con RSLT." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20925/.

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Se è vero che i Linked Open Data accessibili sul Web sono ormai tantissimi, è vero anche che la fruizione di queste informazioni da parte di un pubblico umano è una questione quantomai spinoza. Questo lavoro si propone di esplorare le possibilità di creare applicazioni Web dinamiche con l'ausilio di RSLT, per la visualizzazione di Linked Open Data in formato RDF.
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Le, Xuan Dung. "Webové aplikace s využitím Linked Open Data." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-198433.

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This thesis deals with the issue of open data. The aim is to introduce to reader the currently very popular topic. Linking these data together gives us more advantages and opportuni-ties, however a large number of open data datasets are published in the format that cannot be linked together. Therefore, the author put great emphasis into his work on Linked Data. Emphasis is not placed only on the emergence, current status and future development, but also on the technical aspect. First, readers will be familiar with theoretical concepts, principles of Linked Open Data, expansion of open government data in the Czech Republic and abroad. In the next chapter, the author aimed at the data formats RDF, SPARQL language, etc. In the last section, the author introduce to readers the tools to work with Linked Open Data and design sample application using the Linked Open Data. The benefit of the whole work is a comprehensive view of the Linked Open Data both from a theoretical and from a practical part. The main goal is to provide to readers quality introduction to the issue.
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Sánchez, Adam. "Big Data, Linked Data y Web semántica." Universidad Peruana de Ciencias Aplicadas (UPC), 2016. http://hdl.handle.net/10757/620705.

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Conferencia realizada en el marco de la Semana del Acceso Abierto Perú, llevada a cabo del 24 al 26 de Octubre de 2016 en Lima, Peru. Las instituciones organizadoras: Universidad Peruana de Ciencias aplciadasd (UPC), Pontificia Universidad Católica del Perú (PUCP) y Universidad Peruana Cayetano Heredia (UPCH).
Conferencia que aborda aspectos del protocolo Linked Data, temas de Big Data y Web Semantica,
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Gu, Chen. "Ontology Alignment Techniques for Linked Open Data Ontologies." Miami University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=miami1386858615.

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Minier, Thomas. "Web preemption for querying the linked data open." Thesis, Nantes, 2020. http://www.theses.fr/2020NANT4047.

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En suivant les principes du Linked Open Data, les fournisseurs de données ont publié des milliards de documents RDF via des services publics d’évaluation de requêtes SPARQL. Pour garantir la disponibilité et la stabilité de ces services, ils appliquent des politiques de quotas sur l’utilisation des serveurs. Les requêtes qui excèdent ces quotas sont interrompues et ne renvoient que des résultats partiels. Cette interruption n’est pas un problème s’il est possible de reprendre l’exécution des requêtes ultérieurement, mais il n’existe aucun modèle de préemption le permettant. Dans cette thèse, nous proposons de résoudre le problème relatif à la construction des services qui permettent à n’importe quel utilisateur d’exécuter n’importe quelle requête SPARQL en obtenant des résultats complets. Nous proposons la préemption Web, un nouveau modèle d’exécution qui permet l’interruption de requêtes SPARQL après un quantum de temps, ainsi que leur reprise sur demande des clients. Nous proposons également SaGe, un moteur d’évaluation de requêtes SPARQL qui implémente la préemption Web tout en garantissant un surcoût de préemption minimal. Nos résultats expérimentaux démontrent que SaGe est plus performant que les approches existantes, en termes de temps moyen d’exécution des requêtes et d’obtention des premiers résultats
Following the Linked Open Data principles, data providers have published billions of RDF documents using public SPARQL query services. To ensure these services remains stable and responsive, they enforce quotas on server usage. Queries which exceed these quotas are interrupted and deliver partial results. Such interruption is not an issue if it is possible to resume queries execution afterward. Unfortunately, there is no preemption model for the Web that allows for suspending and resuming SPARQL queries. In this thesis, we propose to tackle the issue of building public SPARQL query servers that allow any data consumer to execute any SPARQL query with complete results. First, we propose a new query execution model called Web Preemption. It allows SPARQL queries to be suspended by the Web server after a fixed time quantum and resumed upon client request. Web preemption is tractable only if its cost in time is negligible compared to the time quantum. Thus, we propose SaGe: a SPARQL query engine that implements Web Preemption with minimal overhead. Experimental results demonstrate that SaGe outperforms existing SPARQL query processing approaches by several orders of magnitude in term of the average total query execution time and the time for first results
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Budka, Michal. "Návrh postupu tvorby aplikace pro Linked Open Data." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-193918.

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This thesis deals with the issue of Linked Open Data. The goal of this thesis is to introduce the reader to this issue as a whole and to the possibility of using Linked Open Data for developing useful applications by proposing a new development process focusing on such applications. The theoretical part offers an insight into the issue of Open Data, Linked Open Data and the NoSQL database systems and their usability in this field. It focuses mainly on graph database systems and compares them with relational database systems using predefined criteria. Additionally, the goal of this thesis is to develop an application using the proposed development process, which provides a tool for data presentation and statistical visualisation for open data sets published by the Supreme Audit Office and the Czech Trade Inspection. The application is mainly developed for the purpose of verifying the proposed development process and to demonstrate the connectivity of open data published by two different organizations.The thesis includes the process of selecting a development methodology, which is then used for optimising work on the implementation of the resulting application and the process of selecting a graph database system, that is used to store and modify open data for the purposes of the application.
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Passerini, Serena. "Analisi Empirica delle Distinzioni Fondazionali in Linked Open Data." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18442/.

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Analisi delle distinzioni fondazionali nei Linked Open Data. Sono state analizzate 4,5 milioni di entità DBPedia, successivamente classificate tramite metodi di classificazione basati sull'apprendimento automatico. I risultati sono stati validati tramite Crowdsourcing. I risultati sono stati confrontati con quelli della ricerca presentata nell'articolo "Empirical Analysis of Foundational Distinctions in Linked Open Data” scritto da Luigi Asprino, Valerio Basile, Paolo Ciancarini e Valentina Presutti.
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RODRIGUES, LIVIA COUTO RUBACK. "ENRICHING AND ANALYZING SEMANTIC TRAJECTORIES WITH LINKED OPEN DATA." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33109@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
Os últimos anos testemunharam o uso crescente de dispositivos que rastreiam objetos móveis: equipamentos com GPS e telefones móveis, veículos ou outros sensores da Internet das Coisas, além de dados de localização de check-ins de redes sociais. Estes dados de mobilidade são representados como trajetórias, e armazenam a sequência de posições de um objeto móvel. Porém, estas sequências representam somente os dados de posição originais, que precisam ser semanticamente enriquecidos para permitir tarefas de análise e apoiar um entendimento profundo sobre o comportamento do movimento. Um outro espaço de dados global sem precedentes tem crescido rapidamente, a Web de Dados, graças à iniciativa de Dados Interligados. Estes dados semânticos ricos e livremente disponíveis fornecem uma nova maneira de enriquecer dados de trajetória. Esta tese apresenta contribuições para os desafios que surgem considerando este cenário. Em primeiro lugar, a tese investiga como dados de trajetória podem se beneficiar da iniciativa de dados interligados, guiando todo o processo de enriquecimento semântico utilizando fontes de dados externas. Em segundo lugar, aborda o tópico de computação de similaridade entre entidades representadas como dados interligados com o objetivo de computar a similaridade entre trajetórias semanticamente enriquecidas. A novidade da abordagem apresentada nesta tese consiste em considerar as características relevantes das entidades como listas ranqueadas. Por último, a tese aborda a computação da similaridade entre trajetórias enriquecidas comparando a similaridade entre todas as entidades representadas como dados interligados que representam as trajetórias enriquecidas.
The last years witnessed a growing number of devices that track moving objects: personal GPS equipped devices and GSM mobile phones, vehicles or other sensors from the Internet of Things but also the location data deriving from the Social Networks check-ins. These mobility data are represented as trajectories, recording the sequence of locations of the moving object. However, these sequences only represent the raw location data and they need to be semantically enriched to be meaningful in the analysis tasks and to support a deep understanding of the movement behavior. Another unprecedented global space that is also growing at a fast pace is the Web of Data, thanks to the emergence of the Linked Data initiative. These freely available semantic rich datasets provide a novel way to enhance trajectory data. This thesis presents a contribution to the many challenges that arise from this scenario. First, it investigates how trajectory data may benefit from the Linked Data Initiative by guiding the whole trajectory enrichment process with the use of external datasets. Then, it addresses the pivotal topic of the similarity computation between Linked Data entities with the final objective of computing the similarity between semantically enriched trajectories. The novelty of our approach is that the thesis considers the relevant entity features as a ranked list. Finally, the thesis targets the computation of the similarity between enriched trajectories by comparing the similarity of the Linked Data entities that represent the enriched trajectories.
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Books on the topic "Linked Open Dynamic Data"

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Trandabăţ, Diana, and Daniela Gîfu, eds. Linguistic Linked Open Data. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32942-0.

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Węcel, Krzysztof. Big, Open and Linked Data. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07147-8.

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Auer, Sören, Volha Bryl, and Sebastian Tramp, eds. Linked Open Data -- Creating Knowledge Out of Interlinked Data. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09846-3.

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Pablos, Patricia Ordóñez de. Cases on open-linked data and semantic web applications. Hershey: Information Science Reference, 2013.

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Lo stato trasparente: Linked open data e cittadinanza attiva. Pisa: ETS, 2010.

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Auer, Sören. Linked Open Data - Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project. Cham: Springer Nature, 2014.

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Bergstrom, A. R. The estimation of open higher order continuous time dynamic models with mixed stock and flow data. [Colchester]: University of Essex, Dept. of Economics, 1986.

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Nowman, K. B. Open higher order continuous time dynamic model with mixed stock and flow data: Some further results. [Colchester]: University of Essex, Dept. of Economics, 1990.

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Standardization, International Organization for, Canadian General Standards Board, and Standards Council of Canada, eds. Liquid flow measurement in open channels: Velocity-area methods, collection and processing of data for determination of errors in measurement. Ottawa, Canada: Canadian General Standards Board, 1991.

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Nowman, K. B. Finite sample properties of the Gaussian estimation of an open higher order continuous time dynamic model with mixed stock and flow data. [Colchester]: University of Essex, Dept. of Economics, 1990.

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Book chapters on the topic "Linked Open Dynamic Data"

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Reformat, Marek Z., Ronald R. Yager, and Jesse Xi Chen. "Dynamic Analysis of Participatory Learning in Linked Open Data: Certainty and Adaptation." In Information Processing and Management of Uncertainty in Knowledge-Based Systems, 667–77. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40581-0_54.

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Vesyropoulos, Nikolaos, Christos K. Georgiadis, and Elias Pimenidis. "An Approach for Web Service Selection and Dynamic Composition Based on Linked Open Data." In Transactions on Computational Collective Intelligence XXX, 54–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99810-7_3.

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De Donato, Renato, Martina Garofalo, Delfina Malandrino, Maria Angela Pellegrino, Andrea Petta, and Vittorio Scarano. "QueDI: From Knowledge Graph Querying to Data Visualization." In Semantic Systems. In the Era of Knowledge Graphs, 70–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59833-4_5.

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Abstract While Open Data (OD) publishers are spur in providing data as Linked Open Data (LOD) to boost innovation and knowledge creation, the complexity of RDF querying languages, such as SPARQL, threatens their exploitation. We aim to help lay users (by focusing on experts in table manipulation, such as OD experts) in querying and exploiting LOD by taking advantage of our target users’ expertise in table manipulation and chart creation. We propose QueDI (Query Data of Interest), a question-answering and visualization tool that implements a scaffold transitional approach to 1) query LOD without being aware of SPARQL and representing results by data tables; 2) once reached our target user comfort zone, users can manipulate and 3) visually represent data by exportable and dynamic visualizations. The main novelty of our approach is the split of the querying phase in SPARQL query building and data table manipulation. In this article, we present the QueDI operating mechanism, its interface supported by a guided use-case over DBpedia, and the evaluation of its accuracy and usability level.
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Yu, Liyang. "Linked Open Data." In A Developer’s Guide to the Semantic Web, 409–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15970-1_11.

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Sikos, Leslie F. "Linked Open Data." In Mastering Structured Data on the Semantic Web, 59–77. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-1049-9_3.

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Bizer, Christian, Maria-Esther Vidal, and Hala Skaf-Molli. "Linked Open Data." In Encyclopedia of Database Systems, 1–5. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_80603-2.

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Gottron, Thomas, and Steffen Staab. "Linked Open Data." In Encyclopedia of Social Network Analysis and Mining, 1–3. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_111-1.

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Yu, Liyang. "Linked Open Data." In A Developer’s Guide to the Semantic Web, 415–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43796-4_9.

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Gottron, Thomas, and Steffen Staab. "Linked Open Data." In Encyclopedia of Social Network Analysis and Mining, 811–13. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_111.

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Gottron, Thomas, and Steffen Staab. "Linked Open Data." In Encyclopedia of Social Network Analysis and Mining, 1211–13. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7131-2_111.

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Conference papers on the topic "Linked Open Dynamic Data"

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Nishioka, Chifumi, and Ansgar Scherp. "Temporal Patterns and Periodicity of Entity Dynamics in the Linked Open Data Cloud." In K-CAP 2015: Knowledge Capture Conference. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2815833.2816948.

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Ríos Hilario, Ana B., Tránsito Ferreras Fernández, and Diego Martín Campo. "Linked open bibliographic data." In the First International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2536536.2536587.

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Piccioli, Alessio, Francesca Di Donato, Danilo Giacomi, Romeo Zitarosa, and Chiara Aiola. "Linked Open Data Portal." In the Third AIUCD Annual Conference. New York, New York, USA: ACM Press, 2015. http://dx.doi.org/10.1145/2802612.2802642.

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Staab, Steffen. "Accessing linked open data." In 2015 12th International Symposium on Programming and Systems (ISPS). IEEE, 2015. http://dx.doi.org/10.1109/isps.2015.7244956.

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Azad, Hiteshwar Kumar, Akshay Deepak, and Kumar Abhishek. "Linked Open Data Search Engine." In the Second International Conference. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/2905055.2905075.

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Ruback, Livia, Marco Antonio Casanova, Alessandra Raffaetà, Chiara Renso, and Vania Vidal. "Enriching Mobility Data with Linked Open Data." In the 20th International Database Engineering & Applications Symposium. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/2938503.2938550.

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Bohm, Christoph, Felix Naumann, Ziawasch Abedjan, Dandy Fenz, Toni Grutze, Daniel Hefenbrock, Matthias Pohl, and David Sonnabend. "Profiling linked open data with ProLOD." In 2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010). IEEE, 2010. http://dx.doi.org/10.1109/icdew.2010.5452762.

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Kozák, Jakub, Martin Nečaský, Jan Dědek, Jakub Klímek, and Jaroslav Pokorný. "Linked Open Data for Healthcare Professionals." In International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2539150.2539195.

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Hagedorn, Stefan, and Kai-Uwe Sattler. "Discovery querying in linked open data." In the Joint EDBT/ICDT 2013 Workshops. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2457317.2457324.

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Marden, Julia, Carolyn Li-Madeo, Noreen Whysel, and Jeffrey Edelstein. "Linked open data for cultural heritage." In the 31st ACM international conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2507065.2507103.

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Reports on the topic "Linked Open Dynamic Data"

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Borchmann, Daniel, Felix Distel, and Francesco Kriegel. Axiomatization of General Concept Inclusions from Finite Interpretations. Technische Universität Dresden, 2015. http://dx.doi.org/10.25368/2022.219.

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Description logic knowledge bases can be used to represent knowledge about a particular domain in a formal and unambiguous manner. Their practical relevance has been shown in many research areas, especially in biology and the semantic web. However, the tasks of constructing knowledge bases itself, often performed by human experts, is difficult, time-consuming and expensive. In particular the synthesis of terminological knowledge is a challenge every expert has to face. Because human experts cannot be omitted completely from the construction of knowledge bases, it would therefore be desirable to at least get some support from machines during this process. To this end, we shall investigate in this work an approach which shall allow us to extract terminological knowledge in the form of general concept inclusions from factual data, where the data is given in the form of vertex and edge labeled graphs. As such graphs appear naturally within the scope of the Semantic Web in the form of sets of RDF triples, the presented approach opens up the possibility to extract terminological knowledge from the Linked Open Data Cloud. We shall also present first experimental results showing that our approach has the potential to be useful for practical applications.
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Eylander, John, Michael Lewis, Maria Stevens, John Green, and Joshua Fairley. An investigation of the feasibility of assimilating COSMOS soil moisture into GeoWATCH. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41966.

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This project objective evaluated the potential of improving linked weather-and-mobility model predictions by blending soil moisture observations from a Cosmic-ray Soil Moisture Observing System (COSMOS) sensor with weather-informed predictions of soil moisture and soil strength from the Geospatial Weather-Affected Terrain Conditions and Hazards (GeoWATCH). Assimilating vehicle-borne COSMOS observations that measure local effects model predictions of soil moisture offered potential to produce more accurate soil strength and vehicle mobility forecast was the hypothesis. This project compared soil moisture observations from a COSMOS mobile sensor driven around an area near Iowa Falls, IA, with both GeoWATCH soil moisture predictions and in situ probe observations. The evaluation of the COSMOS rover data finds that the soil moisture measurements contain a low measurement bias while the GeoWATCH estimates more closely matched the in situ data. The COSMOS rover captured a larger dynamic range of soil moisture conditions as compared to GeoWATCH, capturing both very wet and very dry soil conditions, which may better flag areas of high risk for mobility considerations. Overall, more study of the COSMOS rover is needed to better understand sensor performance in a variety of soil conditions to determine the feasibility of assimilating the COSMOS rover estimates into GeoWATCH.
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Johnson, Sarah, Michael Sinclair, Emily Leonard, and Forrest Rosenbower. Development of strategies for monitoring and managing sandscape vegetation, with an assessment of declining vegetation in the Apostle Islands National Lakeshore. National Park Service, April 2022. http://dx.doi.org/10.36967/nrr-2293187.

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Coastal dune habitats such as those of the Apostle Islands National Lakeshore (APIS) are regionally rare habitats of global and state-wide concern. Their dynamic, sandy landforms provide habitat for unique species specifically adapted to frequent disturbance, drought, and other stresses. Despite having disturbance-driven life histories, these species are at risk due to increased visitor use of sandscape habitats and environmental change. Resource managers at APIS have long understood the values of these sandscapes and threats presented by recreational trampling, but more recently they have recognized the precarious position that these coastal habitats are in due to their proximity to the lake and exposure to weather-related phenomena linked with long-term climate change. In recognition of emerging threats and the need to track impacts of these threats, park managers initiated a revision of their methods for monitoring sandscape vegetation. We applied these methods to 15 sandscape locations within the national lakeshore in 2014. Here, we outline what these revisions to the methods were, assess the current status of sandscape structure and composition, assess the utility of data collected with these methods, provide suggestions for further revisions of the sampling method, outline a two-tiered sampling approach for future monitoring, and we provide management recommendations. In a second section of the report, we provide a focused assessment of the size and health of Juniperus communis (common juniper), a target species of concern in these sandscape communities after it was observed by park managers to be dying or stressed on Michigan Island. Our assessments include the status of J. communis across all sandscapes monitored in 2014, and an analysis of change over time since 2012 in the health of J. communis on Michigan, Outer, and Stockton Islands. We provide evidence of impacts by rodents on foliar dieback, primarily on Michigan Island, and we discuss possible interactions with the non-native pale juniper web-worm (Aethes rutilana) and with climate change.
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Johnson, Sarah, Michael Sinclair, Emily Leonard, and Forrest Rosenbower. Development of strategies for monitoring and managing sandscape vegetation, with an assessment of declining vegetation in the Apostle Islands National Lakeshore. National Park Service, April 2022. http://dx.doi.org/10.36967/nrr-2293187.

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Coastal dune habitats such as those of the Apostle Islands National Lakeshore (APIS) are regionally rare habitats of global and state-wide concern. Their dynamic, sandy landforms provide habitat for unique species specifically adapted to frequent disturbance, drought, and other stresses. Despite having disturbance-driven life histories, these species are at risk due to increased visitor use of sandscape habitats and environmental change. Resource managers at APIS have long understood the values of these sandscapes and threats presented by recreational trampling, but more recently they have recognized the precarious position that these coastal habitats are in due to their proximity to the lake and exposure to weather-related phenomena linked with long-term climate change. In recognition of emerging threats and the need to track impacts of these threats, park managers initiated a revision of their methods for monitoring sandscape vegetation. We applied these methods to 15 sandscape locations within the national lakeshore in 2014. Here, we outline what these revisions to the methods were, assess the current status of sandscape structure and composition, assess the utility of data collected with these methods, provide suggestions for further revisions of the sampling method, outline a two-tiered sampling approach for future monitoring, and we provide management recommendations. In a second section of the report, we provide a focused assessment of the size and health of Juniperus communis (common juniper), a target species of concern in these sandscape communities after it was observed by park managers to be dying or stressed on Michigan Island. Our assessments include the status of J. communis across all sandscapes monitored in 2014, and an analysis of change over time since 2012 in the health of J. communis on Michigan, Outer, and Stockton Islands. We provide evidence of impacts by rodents on foliar dieback, primarily on Michigan Island, and we discuss possible interactions with the non-native pale juniper web-worm (Aethes rutilana) and with climate change.
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Newman-Toker, David E., Susan M. Peterson, Shervin Badihian, Ahmed Hassoon, Najlla Nassery, Donna Parizadeh, Lisa M. Wilson, et al. Diagnostic Errors in the Emergency Department: A Systematic Review. Agency for Healthcare Research and Quality (AHRQ), December 2022. http://dx.doi.org/10.23970/ahrqepccer258.

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Objectives. Diagnostic errors are a known patient safety concern across all clinical settings, including the emergency department (ED). We conducted a systematic review to determine the most frequent diseases and clinical presentations associated with diagnostic errors (and resulting harms) in the ED, measure error and harm frequency, as well as assess causal factors. Methods. We searched PubMed®, Cumulative Index to Nursing and Allied Health Literature (CINAHL®), and Embase® from January 2000 through September 2021. We included research studies and targeted grey literature reporting diagnostic errors or misdiagnosis-related harms in EDs in the United States or other developed countries with ED care deemed comparable by a technical expert panel. We applied standard definitions for diagnostic errors, misdiagnosis-related harms (adverse events), and serious harms (permanent disability or death). Preventability was determined by original study authors or differences in harms across groups. Two reviewers independently screened search results for eligibility; serially extracted data regarding common diseases, error/harm rates, and causes/risk factors; and independently assessed risk of bias of included studies. We synthesized results for each question and extrapolated U.S. estimates. We present 95 percent confidence intervals (CIs) or plausible range (PR) bounds, as appropriate. Results. We identified 19,127 citations and included 279 studies. The top 15 clinical conditions associated with serious misdiagnosis-related harms (accounting for 68% [95% CI 66 to 71] of serious harms) were (1) stroke, (2) myocardial infarction, (3) aortic aneurysm and dissection, (4) spinal cord compression and injury, (5) venous thromboembolism, (6/7 – tie) meningitis and encephalitis, (6/7 – tie) sepsis, (8) lung cancer, (9) traumatic brain injury and traumatic intracranial hemorrhage, (10) arterial thromboembolism, (11) spinal and intracranial abscess, (12) cardiac arrhythmia, (13) pneumonia, (14) gastrointestinal perforation and rupture, and (15) intestinal obstruction. Average disease-specific error rates ranged from 1.5 percent (myocardial infarction) to 56 percent (spinal abscess), with additional variation by clinical presentation (e.g., missed stroke average 17%, but 4% for weakness and 40% for dizziness/vertigo). There was also wide, superimposed variation by hospital (e.g., missed myocardial infarction 0% to 29% across hospitals within a single study). An estimated 5.7 percent (95% CI 4.4 to 7.1) of all ED visits had at least one diagnostic error. Estimated preventable adverse event rates were as follows: any harm severity (2.0%, 95% CI 1.0 to 3.6), any serious harms (0.3%, PR 0.1 to 0.7), and deaths (0.2%, PR 0.1 to 0.4). While most disease-specific error rates derived from mainly U.S.-based studies, overall error and harm rates were derived from three prospective studies conducted outside the United States (in Canada, Spain, and Switzerland, with combined n=1,758). If overall rates are generalizable to all U.S. ED visits (130 million, 95% CI 116 to 144), this would translate to 7.4 million (PR 5.1 to 10.2) ED diagnostic errors annually; 2.6 million (PR 1.1 to 5.2) diagnostic adverse events with preventable harms; and 371,000 (PR 142,000 to 909,000) serious misdiagnosis-related harms, including more than 100,000 permanent, high-severity disabilities and 250,000 deaths. Although errors were often multifactorial, 89 percent (95% CI 88 to 90) of diagnostic error malpractice claims involved failures of clinical decision-making or judgment, regardless of the underlying disease present. Key process failures were errors in diagnostic assessment, test ordering, and test interpretation. Most often these were attributed to inadequate knowledge, skills, or reasoning, particularly in “atypical” or otherwise subtle case presentations. Limitations included use of malpractice claims and incident reports for distribution of diseases leading to serious harms, reliance on a small number of non-U.S. studies for overall (disease-agnostic) diagnostic error and harm rates, and methodologic variability across studies in measuring disease-specific rates, determining preventability, and assessing causal factors. Conclusions. Although estimated ED error rates are low (and comparable to those found in other clinical settings), the number of patients potentially impacted is large. Not all diagnostic errors or harms are preventable, but wide variability in diagnostic error rates across diseases, symptoms, and hospitals suggests improvement is possible. With 130 million U.S. ED visits, estimated rates for diagnostic error (5.7%), misdiagnosis-related harms (2.0%), and serious misdiagnosis-related harms (0.3%) could translate to more than 7 million errors, 2.5 million harms, and 350,000 patients suffering potentially preventable permanent disability or death. Over two-thirds of serious harms are attributable to just 15 diseases and linked to cognitive errors, particularly in cases with “atypical” manifestations. Scalable solutions to enhance bedside diagnostic processes are needed, and these should target the most commonly misdiagnosed clinical presentations of key diseases causing serious harms. New studies should confirm overall rates are representative of current U.S.-based ED practice and focus on identified evidence gaps (errors among common diseases with lower-severity harms, pediatric ED errors and harms, dynamic systems factors such as overcrowding, and false positives). Policy changes to consider based on this review include: (1) standardizing measurement and research results reporting to maximize comparability of measures of diagnostic error and misdiagnosis-related harms; (2) creating a National Diagnostic Performance Dashboard to track performance; and (3) using multiple policy levers (e.g., research funding, public accountability, payment reforms) to facilitate the rapid development and deployment of solutions to address this critically important patient safety concern.
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Monetary Policy Report - July 2022. Banco de la República, October 2022. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr3-2022.

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In the second quarter, annual inflation (9.67%), the technical staff’s projections and its expectations continued to increase, remaining above the target. International cost shocks, accentuated by Russia's invasion of Ukraine, have been more persistent than projected, thus contributing to higher inflation. The effects of indexation, higher than estimated excess demand, a tighter labor market, inflation expectations that continue to rise and currently exceed 3%, and the exchange rate pressures add to those described above. High core inflation measures as well as in the producer price index (PPI) across all baskets confirm a significant spread in price increases. Compared to estimates presented in April, the new forecast trajectory for headline and core inflation increased. This was partly the result of greater exchange rate pressure on prices, and a larger output gap, which is expected to remain positive for the remainder of 2022 and which is estimated to close towards yearend 2023. In addition, these trends take into account higher inflation rate indexation, more persistent above-target inflation expectations, a quickening of domestic fuel price increases due to the correction of lags versus the parity price and higher international oil price forecasts. The forecast supposes a good domestic supply of perishable foods, although it also considers that international prices of processed foods will remain high. In terms of the goods sub-basket, the end of the national health emergency implies a reversal of the value-added tax (VAT) refund applied to health and personal hygiene products, resulting in increases in the prices of these goods. Alternatively, the monetary policy adjustment process and the moderation of external shocks would help inflation and its expectations to begin to decrease over time and resume their alignment with the target. Thus, the new projection suggests that inflation could remain high for the second half of 2022, closing at 9.7%. However, it would begin to fall during 2023, closing the year at 5.7%. These forecasts are subject to significant uncertainty, especially regarding the future behavior of external cost shocks, the degree of indexation of nominal contracts and decisions made regarding the domestic price of fuels. Economic activity continues to outperform expectations, and the technical staff’s growth projections for 2022 have been revised upwards from 5% to 6.9%. The new forecasts suggest higher output levels that would continue to exceed the economy’s productive capacity for the remainder of 2022. Economic growth during the first quarter was above that estimated in April, while economic activity indicators for the second quarter suggest that the GDP could be expected to remain high, potentially above that of the first quarter. Domestic demand is expected to maintain a positive dynamic, in particular, due to the household consumption quarterly growth, as suggested by vehicle registrations, retail sales, credit card purchases and consumer loan disbursement figures. A slowdown in the machinery and equipment imports from the levels observed in March contrasts with the positive performance of sales and housing construction licenses, which indicates an investment level similar to that registered for the first three months of the year. International trade data suggests the trade deficit would be reduced as a consequence of import levels that would be lesser than those observed in the first quarter, and stable export levels. For the remainder of the year and 2023, a deceleration in consumption is expected from the high levels seen during the first half of the year, partially as a result of lower repressed demand, tighter domestic financial conditions and household available income deterioration due to increased inflation. Investment is expected to continue its slow recovery while remaining below pre-pandemic levels. The trade deficit is expected to tighten due to projected lower domestic demand dynamics, and high prices of oil and other basic goods exported by the country. Given the above, economic growth in the second quarter of 2022 would be 11.5%, and for 2022 and 2023 an annual growth of 6.9% and 1.1% is expected, respectively. Currently, and for the remainder of 2022, the output gap would be positive and greater than that estimated in April, and prices would be affected by demand pressures. These projections continue to be affected by significant uncertainty associated with global political tensions, the expected adjustment of monetary policy in developed countries, external demand behavior, changes in country risk outlook, and the future developments in domestic fiscal policy, among others. The high inflation levels and respective expectations, which exceed the target of the world's main central banks, largely explain the observed and anticipated increase in their monetary policy interest rates. This environment has tempered the growth forecast for external demand. Disruptions in value chains, rising international food and energy prices, and expansionary monetary and fiscal policies have contributed to the rise in inflation and above-target expectations seen by several of Colombia’s main trading partners. These cost and price shocks, heightened by the effects of Russia's invasion of Ukraine, have been more prevalent than expected and have taken place within a set of output and employment recovery, variables that in some countries currently equal or exceed their projected long-term levels. In response, the U.S. Federal Reserve accelerated the pace of the benchmark interest rate increase and rapidly reduced liquidity levels in the money market. Financial market actors expect this behavior to continue and, consequently, significantly increase their expectations of the average path of the Fed's benchmark interest rate. In this setting, the U.S. dollar appreciated versus the peso in the second quarter and emerging market risk measures increased, a behavior that intensified for Colombia. Given the aforementioned, for the remainder of 2022 and 2023, the Bank's technical staff increased the forecast trajectory for the Fed's interest rate and reduced the country's external demand growth forecast. The projected oil price was revised upward over the forecast horizon, specifically due to greater supply restrictions and the interruption of hydrocarbon trade between the European Union and Russia. Global geopolitical tensions, a tightening of monetary policy in developed economies, the increase in risk perception for emerging markets and the macroeconomic imbalances in the country explain the increase in the projected trajectory of the risk premium, its trend level and the neutral real interest rate1. Uncertainty about external forecasts and their consequent impact on the country's macroeconomic scenario remains high, given the unpredictable evolution of the conflict between Russia and Ukraine, geopolitical tensions, the degree of the global economic slowdown and the effect the response to recent outbreaks of the pandemic in some Asian countries may have on the world economy. This macroeconomic scenario that includes high inflation, inflation forecasts, and expectations above 3% and a positive output gap suggests the need for a contractionary monetary policy that mitigates the risk of the persistent unanchoring of inflation expectations. In contrast to the forecasts of the April report, the increase in the risk premium trend implies a higher neutral real interest rate and a greater prevailing monetary stimulus than previously estimated. For its part, domestic demand has been more dynamic, with a higher observed and expected output level that exceeds the economy’s productive capacity. The surprising accelerations in the headline and core inflation reflect stronger and more persistent external shocks, which, in combination with the strength of aggregate demand, indexation, higher inflation expectations and exchange rate pressures, explain the upward projected inflation trajectory at levels that exceed the target over the next two years. This is corroborated by the inflation expectations of economic analysts and those derived from the public debt market, which continued to climb and currently exceed 3%. All of the above increase the risk of unanchoring inflation expectations and could generate widespread indexation processes that may push inflation away from the target for longer. This new macroeconomic scenario suggests that the interest rate adjustment should continue towards a contractionary monetary policy landscape. 1.2. Monetary policy decision Banco de la República’s Board of Directors (BDBR), at its meetings in June and July 2022, decided to continue adjusting its monetary policy. At its June meeting, the BDBR decided to increase the monetary policy rate by 150 basis points (b.p.) and its July meeting by majority vote, on a 150 b.p. increase thereof at its July meeting. Consequently, the monetary policy interest rate currently stands at 9.0% . 1 The neutral real interest rate refers to the real interest rate level that is neither stimulative nor contractionary for aggregate demand and, therefore, does not generate pressures that lead to the close of the output gap. In a small, open economy like Colombia, this rate depends on the external neutral real interest rate, medium-term components of the country risk premium, and expected depreciation. Box 1: A Weekly Indicator of Economic Activity for Colombia Juan Pablo Cote Carlos Daniel Rojas Nicol Rodriguez Box 2: Common Inflationary Trends in Colombia Carlos D. Rojas-Martínez Nicolás Martínez-Cortés Franky Juliano Galeano-Ramírez Box 3: Shock Decomposition of 2021 Forecast Errors Nicolás Moreno Arias
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