Relevant bibliographies by topics / Data and metadata structures

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Data and metadata structures'

Author: Grafiati
Published: 10 March 2023
Last updated: 11 March 2023

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Journal articles on the topic "Data and metadata structures"

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Mincewicz, Wojciech. "Metadane – cichy zabójca prywatności." Studia Politologiczne 2019, no. 54 (November 20, 2019): 230–57. http://dx.doi.org/10.33896/spolit.2019.54.9.

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The article has a deeper reflection on the issue of metadata, that is, data which are defined or describe other data. The theoretical layer extracted three types of metadata: descriptive, structural, and administrative. Descriptive metadata is used to find and identify key information that allows the location of an object. Structured metadata describes the internal structure of the object, but administrative metadata refers to the technical information, where information is provided for example about the time and how the file was created. The purpose of the publication is to provide theoretical knowledge as well as practical. The second part of the article depicts the concepts of graphic and text files, and simple self-defense techniques are indicated, which allow you to remove metadata before sharing the file. The supplementing of article is: analysis the ability to extract meta information by Fingerprinting Organizations with Collected Archives (FOCA), which is used to mechanizedly extract metadata reflection on what the metadata includes the email header.
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Fong, Joseph, Qing Li, and Shi-Ming Huang. "Universal Data Warehousing Based on a Meta-Data Modeling Approach." International Journal of Cooperative Information Systems 12, no. 03 (September 2003): 325–63. http://dx.doi.org/10.1142/s0218843003000772.

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Data warehouse contains vast amount of data to support complex queries of various Decision Support Systems (DSSs). It needs to store materialized views of data, which must be available consistently and instantaneously. Using a frame metadata model, this paper presents an architecture of a universal data warehousing with different data models. The frame metadata model represents the metadata of a data warehouse, which structures an application domain into classes, and integrates schemas of heterogeneous databases by capturing their semantics. A star schema is derived from user requirements based on the integrated schema, catalogued in the metadata, which stores the schema of relational database (RDB) and object-oriented database (OODB). Data materialization between RDB and OODB is achieved by unloading source database into sequential file and reloading into target database, through which an object relational view can be defined so as to allow the users to obtain the same warehouse view in different data models simultaneously. We describe our procedures of building the relational view of star schema by multidimensional SQL query, and the object oriented view of the data warehouse by Online Analytical Processing (OLAP) through method call, derived from the integrated schema. To validate our work, an application prototype system has been developed in a product sales data warehousing domain based on this approach.
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Et.al, Nur Adila Azram. "Laboratory Instruments’ Produced Scientific Data Standardization through the Use of Metadata." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (April 10, 2021): 2146–51. http://dx.doi.org/10.17762/turcomat.v12i3.1157.

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The progression of scientific data from various laboratory instruments is increasing these days. As different laboratory instruments hold different structures and formats of data, it became a concern in the management and analysis of data because of the heterogeneity of data structure and format. This paper offered a metadata structure to standardize the laboratory instruments' -produced scientific data to attain a standard structure and format. This paper contains explanation regarding the methodology and the use of proposed metadata structure, before summarizing the implementation and its related result analysis. The proposed metadata structure extraction shows promising results based on conducted evaluation and validation.
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Wagner, Michael, Christin Henzen, and Ralph Müller-Pfefferkorn. "A Research Data Infrastructure Component for the Automated Metadata and Data Quality Extraction to Foster the Provision of FAIR Data in Earth System Sciences." AGILE: GIScience Series 2 (June 4, 2021): 1–7. http://dx.doi.org/10.5194/agile-giss-2-41-2021.

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Abstract. Metadata management is core to support discovery and reuse of data products, and to allow for reproducibility of the research data in Earth System Sciences (ESS). Thus, ensuring acquisition and provision of meaningful and quality assured metadata should become an integral part of data-driven ESS projects.We propose an open-source tool for the automated metadata and data quality extraction to foster the provision of FAIR data (Findable, Accessible, Interoperable Reusable). By enabling researchers to automatically extract and reuse structured and standardized ESS-specific metadata, in particular quality information, in several components of a research data infrastructure, we support researchers along the research data life cycle.
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Hoarfrost, Adrienne, Nick Brown, C. Titus Brown, and Carol Arnosti. "Sequencing data discovery with MetaSeek." Bioinformatics 35, no. 22 (June 21, 2019): 4857–59. http://dx.doi.org/10.1093/bioinformatics/btz499.

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Abstract Summary Sequencing data resources have increased exponentially in recent years, as has interest in large-scale meta-analyses of integrated next-generation sequencing datasets. However, curation of integrated datasets that match a user’s particular research priorities is currently a time-intensive and imprecise task. MetaSeek is a sequencing data discovery tool that enables users to flexibly search and filter on any metadata field to quickly find the sequencing datasets that meet their needs. MetaSeek automatically scrapes metadata from all publicly available datasets in the Sequence Read Archive, cleans and parses messy, user-provided metadata into a structured, standard-compliant database and predicts missing fields where possible. MetaSeek provides a web-based graphical user interface and interactive visualization dashboard, as well as a programmatic API to rapidly search, filter, visualize, save, share and download matching sequencing metadata. Availability and implementation The MetaSeek online interface is available at https://www.metaseek.cloud/. The MetaSeek database can also be accessed via API to programmatically search, filter and download all metadata. MetaSeek source code, metadata scrapers and documents are available at https://github.com/MetaSeek-Sequencing-Data-Discovery/metaseek/.
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Qin, Jian, Jeff Hemsley, and Sarah E. Bratt. "The structural shift and collaboration capacity in GenBank Networks: A longitudinal study." Quantitative Science Studies 3, no. 1 (2022): 174–93. http://dx.doi.org/10.1162/qss_a_00181.

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Abstract Metadata in scientific data repositories such as GenBank contain links between data submissions and related publications. As a new data source for studying collaboration networks, metadata in data repositories compensate for the limitations of publication-based research on collaboration networks. This paper reports the findings from a GenBank metadata analytics project. We used network science methods to uncover the structures and dynamics of GenBank collaboration networks from 1992–2018. The longitudinality and large scale of this data collection allowed us to unravel the evolution history of collaboration networks and identify the trend of flattening network structures over time and optimal assortative mixing range for enhancing collaboration capacity. By incorporating metadata from the data production stage with the publication stage, we uncovered new characteristics of collaboration networks as well as developed new metrics for assessing the effectiveness of enablers of collaboration—scientific and technical human capital, cyberinfrastructure, and science policy.
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Jiang, L. Q., S. A. O'Connor, K. M. Arzayus, and A. R. Parsons. "A metadata template for ocean acidification data." Earth System Science Data 7, no. 1 (June 11, 2015): 117–25. http://dx.doi.org/10.5194/essd-7-117-2015.

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Abstract. This paper defines the best practices for documenting ocean acidification (OA) data and presents a framework for an OA metadata template. Metadata is structured information that describes and locates an information resource. It is the key to ensuring that a data set will be accessible into the future. With the rapid expansion of studies on biological responses to OA, the lack of a common metadata template to document the resulting data poses a significant hindrance to effective OA data management efforts. In this paper, we present a metadata template that can be applied to a broad spectrum of OA studies, including those studying the biological responses to OA. The "variable metadata section", which includes the variable name, observation type, whether the variable is a manipulation condition or response variable, and the biological subject on which the variable is studied, forms the core of this metadata template. Additional metadata elements, such as investigators, temporal and spatial coverage, and data citation, are essential components to complete the template. We explain the structure of the template, and define many metadata elements that may be unfamiliar to researchers.
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Lassi, Monica, Maria Johnsson, and Koraljka Golub. "Research data services." IFLA Journal 42, no. 4 (November 30, 2016): 266–77. http://dx.doi.org/10.1177/0340035216671963.

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The paper reports on an exploratory study of researchers’ needs for effective research data management at two Swedish universities, conducted in order to inform the ongoing development of research data services. Twelve researchers from diverse fields have been interviewed, including biology, cultural studies, economics, environmental studies, geography, history, linguistics, media and psychology. The interviews were structured, guided by the Data Curation Profiles Toolkit developed at Purdue University, with added questions regarding subject metadata. The preliminary analysis indicates that the research data management practices vary greatly among the respondents, and therefore so do the implications for research data services. The added questions on subject metadata indicate needs of services guiding researchers in describing their datasets with adequate metadata.
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Jiang, L. Q., S. A. O'Connor, K. M. Arzayus, A. Kozyr, and A. R. Parsons. "A metadata template for ocean acidification data." Earth System Science Data Discussions 8, no. 1 (January 13, 2015): 1–21. http://dx.doi.org/10.5194/essdd-8-1-2015.

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Abstract. This paper defines the best practices for documenting ocean acidification (OA) metadata and presents a framework for an OA metadata template. Metadata is structured information that describes and locates an information resource. It is the key to ensuring that a data set will survive and continue to be accessible into the future. With the rapid expansion of studies on biological responses of organisms to OA, the lack of a common metadata template to document the resulting data poses a significant hindrance to effective OA data management efforts. In this paper, we present a metadata template that can be applied to a broad spectrum of OA studies, including those studying the biological responses of organisms to OA. The "variable metadata section", which includes the variable name, observation type, whether the variable is a manipulation condition or response variable, and the biological subject on which the variable is studied, forms the core of this metadata template. Additional metadata elements, such as investigators, temporal and spatial coverage, platforms for the sampling, data citation, are essential components to complete the template. We also explain the structure of the template, and define many metadata elements that may be unfamiliar to researchers. Template availability. - Available at: http://ezid.cdlib.org/id/doi:10.7289/V5C24TCK. - DOI: doi:10.7289/V5C24TCK. - NOAA Institutional Repository Accession number: ocn881471371.
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Vanags, Mikus, and Rudite Cevere. "Type Safe Metadata Combining." Computer and Information Science 10, no. 2 (April 30, 2017): 97. http://dx.doi.org/10.5539/cis.v10n2p97.

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Type safety is an important property of any type system. Modern programming languages support different mechanisms to work in type safe manner, e.g., properties, methods, events, attributes (annotations) and other structures. Some programming languages allow access to metadata: type information, type member information and information about applied attributes. But none of the existing mainstream programming languages which support reflection provides fully type safe metadata combining mechanism built in the programming language. Combining of metadata means a class member metadata combining with data, type metadata and constraints. Existing solutions provide no or limited type safe metadata combining mechanism; they are complex and processed at runtime, which by definition is not built-in type-safe metadata combining. Problem can be solved by introducing syntax and methods for type safe metadata combining so that, metadata could be processed at compile time in a fully type safe way. Common metadata combining use cases are data abstraction layer creation and database querying.
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Dissertations / Theses on the topic "Data and metadata structures"

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Kruse, Sebastian [Verfasser], and Felix [Akademischer Betreuer] Naumann. "Scalable data profiling : distributed discovery and analysis of structural metadata / Sebastian Kruse ; Betreuer: Felix Naumann." Potsdam : Universität Potsdam, 2018. http://d-nb.info/1217717854/34.

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Wu, Qinyi. "Partial persistent sequences and their applications to collaborative text document editing and processing." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/44916.

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In a variety of text document editing and processing applications, it is necessary to keep track of the revision history of text documents by recording changes and the metadata of those changes (e.g., user names and modification timestamps). The recent Web 2.0 document editing and processing applications, such as real-time collaborative note taking and wikis, require fine-grained shared access to collaborative text documents as well as efficient retrieval of metadata associated with different parts of collaborative text documents. Current revision control techniques only support coarse-grained shared access and are inefficient to retrieve metadata of changes at the sub-document granularity. In this dissertation, we design and implement partial persistent sequences (PPSs) to support real-time collaborations and manage metadata of changes at fine granularities for collaborative text document editing and processing applications. As a persistent data structure, PPSs have two important features. First, items in the data structure are never removed. We maintain necessary timestamp information to keep track of both inserted and deleted items and use the timestamp information to reconstruct the state of a document at any point in time. Second, PPSs create unique, persistent, and ordered identifiers for items of a document at fine granularities (e.g., a word or a sentence). As a result, we are able to support consistent and fine-grained shared access to collaborative text documents by detecting and resolving editing conflicts based on the revision history as well as to efficiently index and retrieve metadata associated with different parts of collaborative text documents. We demonstrate the capabilities of PPSs through two important problems in collaborative text document editing and processing applications: data consistency control and fine-grained document provenance management. The first problem studies how to detect and resolve editing conflicts in collaborative text document editing systems. We approach this problem in two steps. In the first step, we use PPSs to capture data dependencies between different editing operations and define a consistency model more suitable for real-time collaborative editing systems. In the second step, we extend our work to the entire spectrum of collaborations and adapt transactional techniques to build a flexible framework for the development of various collaborative editing systems. The generality of this framework is demonstrated by its capabilities to specify three different types of collaborations as exemplified in the systems of RCS, MediaWiki, and Google Docs respectively. We precisely specify the programming interfaces of this framework and describe a prototype implementation over Oracle Berkeley DB High Availability, a replicated database management engine. The second problem of fine-grained document provenance management studies how to efficiently index and retrieve fine-grained metadata for different parts of collaborative text documents. We use PPSs to design both disk-economic and computation-efficient techniques to index provenance data for millions of Wikipedia articles. Our approach is disk economic because we only save a few full versions of a document and only keep delta changes between those full versions. Our approach is also computation-efficient because we avoid the necessity of parsing the revision history of collaborative documents to retrieve fine-grained metadata. Compared to MediaWiki, the revision control system for Wikipedia, our system uses less than 10% of disk space and achieves at least an order of magnitude speed-up to retrieve fine-grained metadata for documents with thousands of revisions.
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Lima, João Alberto de Oliveira. "Modelo Genérico de Relacionamentos na Organização da Informação Legislativa e Jurídica." Thesis, reponame:Repositório Institucional da UnB, 2008. http://eprints.rclis.org/11352/1/tese_Joao_Lima_FINAL.pdf.

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In most of the time information does not work in an isolate form and it always belongs to one context, making relationships with other entities. Legislative and legal information, in a certain way, is characterized by their high degree of relationships. Laws, bills, legal cases and doctrine are connected by several forms, creating a rich network of information. Efforts done for the organization of information generate artificial models that try to represent the real world, creating systems and schemes of concepts used in the classification processes and indexing of information resources. This research had the main objective of proposing a Generic Model of Relationship (GMR), based in a simple constructs which permitted the establishment of relationships between concepts and information units. In the conception of GMR were used Ingetraut Dahlberg’s Theory of Concept and the models CIDOC CRM (ISO 21.117:2006), FRBROO and Topic Maps (ISO 13.250:1999). The identification of relationship and the characteristics of information units in a legal domain were collected in the project "Coletânea Brasileira de Normas e Julgados de Telecomunicações", using the methodology of Action Research. Besides the development of GMR and its application in the legislative and legal information domains, the research also contributed with the definitions of one identification system of documents versions and a new meaning for the term “information unit”.
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Da, Silva Carvalho Paulo. "Plateforme visuelle pour l'intégration de données faiblement structurées et incertaines." Thesis, Tours, 2017. http://www.theses.fr/2017TOUR4020/document.

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Nous entendons beaucoup parler de Big Data, Open Data, Social Data, Scientific Data, etc. L’importance qui est apportée aux données en général est très élevée. L’analyse de ces données est importante si l’objectif est de réussir à en extraire de la valeur pour pouvoir les utiliser. Les travaux présentés dans cette thèse concernent la compréhension, l’évaluation, la correction/modification, la gestion et finalement l’intégration de données, pour permettre leur exploitation. Notre recherche étudie exclusivement les données ouvertes (DOs - Open Data) et plus précisément celles structurées sous format tabulaire (CSV). Le terme Open Data est apparu pour la première fois en 1995. Il a été utilisé par le groupe GCDIS (Global Change Data and Information System) (États-Unis) pour encourager les entités, possédant les mêmes intérêts et préoccupations, à partager leurs données [Data et System, 1995]. Le mouvement des données ouvertes étant récent, il s’agit d’un champ qui est actuellement en grande croissance. Son importance est actuellement très forte. L’encouragement donné par les gouvernements et institutions publiques à ce que leurs données soient publiées a sans doute un rôle important à ce niveau
We hear a lot about Big Data, Open Data, Social Data, Scientific Data, etc. The importance currently given to data is, in general, very high. We are living in the era of massive data. The analysis of these data is important if the objective is to successfully extract value from it so that they can be used. The work presented in this thesis project is related with the understanding, assessment, correction/modification, management and finally the integration of the data, in order to allow their respective exploitation and reuse. Our research is exclusively focused on Open Data and, more precisely, Open Data organized in tabular form (CSV - being one of the most widely used formats in the Open Data domain). The first time that the term Open Data appeared was in 1995 when the group GCDIS (Global Change Data and Information System) (from United States) used this expression to encourage entities, having the same interests and concerns, to share their data [Data et System, 1995]. However, the Open Data movement has only recently undergone a sharp increase. It has become a popular phenomenon all over the world. Being the Open Data movement recent, it is a field that is currently growing and its importance is very strong. The encouragement given by governments and public institutions to have their data published openly has an important role at this level
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Nadal, Francesch Sergi. "Metadata-driven data integration." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/666947.

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Data has an undoubtable impact on society. Storing and processing large amounts of available data is currently one of the key success factors for an organization. Nonetheless, we are recently witnessing a change represented by huge and heterogeneous amounts of data. Indeed, 90% of the data in the world has been generated in the last two years. Thus, in order to carry on these data exploitation tasks, organizations must first perform data integration combining data from multiple sources to yield a unified view over them. Yet, the integration of massive and heterogeneous amounts of data requires revisiting the traditional integration assumptions to cope with the new requirements posed by such data-intensive settings. This PhD thesis aims to provide a novel framework for data integration in the context of data-intensive ecosystems, which entails dealing with vast amounts of heterogeneous data, from multiple sources and in their original format. To this end, we advocate for an integration process consisting of sequential activities governed by a semantic layer, implemented via a shared repository of metadata. From an stewardship perspective, this activities are the deployment of a data integration architecture, followed by the population of such shared metadata. From a data consumption perspective, the activities are virtual and materialized data integration, the former an exploratory task and the latter a consolidation one. Following the proposed framework, we focus on providing contributions to each of the four activities. We begin proposing a software reference architecture for semantic-aware data-intensive systems. Such architecture serves as a blueprint to deploy a stack of systems, its core being the metadata repository. Next, we propose a graph-based metadata model as formalism for metadata management. We focus on supporting schema and data source evolution, a predominant factor on the heterogeneous sources at hand. For virtual integration, we propose query rewriting algorithms that rely on the previously proposed metadata model. We additionally consider semantic heterogeneities in the data sources, which the proposed algorithms are capable of automatically resolving. Finally, the thesis focuses on the materialized integration activity, and to this end, proposes a method to select intermediate results to materialize in data-intensive flows. Overall, the results of this thesis serve as contribution to the field of data integration in contemporary data-intensive ecosystems.
Les dades tenen un impacte indubtable en la societat. La capacitat d’emmagatzemar i processar grans quantitats de dades disponibles és avui en dia un dels factors claus per l’èxit d’una organització. No obstant, avui en dia estem presenciant un canvi representat per grans volums de dades heterogenis. En efecte, el 90% de les dades mundials han sigut generades en els últims dos anys. Per tal de dur a terme aquestes tasques d’explotació de dades, les organitzacions primer han de realitzar una integració de les dades, combinantles a partir de diferents fonts amb l’objectiu de tenir-ne una vista unificada d’elles. Per això, aquest fet requereix reconsiderar les assumpcions tradicionals en integració amb l’objectiu de lidiar amb els requisits imposats per aquests sistemes de tractament massiu de dades. Aquesta tesi doctoral té com a objectiu proporcional un nou marc de treball per a la integració de dades en el context de sistemes de tractament massiu de dades, el qual implica lidiar amb una gran quantitat de dades heterogènies, provinents de múltiples fonts i en el seu format original. Per això, proposem un procés d’integració compost d’una seqüència d’activitats governades per una capa semàntica, la qual és implementada a partir d’un repositori de metadades compartides. Des d’una perspectiva d’administració, aquestes activitats són el desplegament d’una arquitectura d’integració de dades, seguit per la inserció d’aquestes metadades compartides. Des d’una perspectiva de consum de dades, les activitats són la integració virtual i materialització de les dades, la primera sent una tasca exploratòria i la segona una de consolidació. Seguint el marc de treball proposat, ens centrem en proporcionar contribucions a cada una de les quatre activitats. La tesi inicia proposant una arquitectura de referència de software per a sistemes de tractament massiu de dades amb coneixement semàntic. Aquesta arquitectura serveix com a planell per a desplegar un conjunt de sistemes, sent el repositori de metadades al seu nucli. Posteriorment, proposem un model basat en grafs per a la gestió de metadades. Concretament, ens centrem en donar suport a l’evolució d’esquemes i fonts de dades, un dels factors predominants en les fonts de dades heterogènies considerades. Per a l’integració virtual, proposem algorismes de rescriptura de consultes que usen el model de metadades previament proposat. Com a afegitó, considerem heterogeneïtat semàntica en les fonts de dades, les quals els algorismes de rescriptura poden resoldre automàticament. Finalment, la tesi es centra en l’activitat d’integració materialitzada. Per això proposa un mètode per a seleccionar els resultats intermedis a materialitzar un fluxes de tractament intensiu de dades. En general, els resultats d’aquesta tesi serveixen com a contribució al camp d’integració de dades en els ecosistemes de tractament massiu de dades contemporanis
Les données ont un impact indéniable sur la société. Le stockage et le traitement de grandes quantités de données disponibles constituent actuellement l’un des facteurs clés de succès d’une entreprise. Néanmoins, nous assistons récemment à un changement représenté par des quantités de données massives et hétérogènes. En effet, 90% des données dans le monde ont été générées au cours des deux dernières années. Ainsi, pour mener à bien ces tâches d’exploitation des données, les organisations doivent d’abord réaliser une intégration des données en combinant des données provenant de sources multiples pour obtenir une vue unifiée de ces dernières. Cependant, l’intégration de quantités de données massives et hétérogènes nécessite de revoir les hypothèses d’intégration traditionnelles afin de faire face aux nouvelles exigences posées par les systèmes de gestion de données massives. Cette thèse de doctorat a pour objectif de fournir un nouveau cadre pour l’intégration de données dans le contexte d’écosystèmes à forte intensité de données, ce qui implique de traiter de grandes quantités de données hétérogènes, provenant de sources multiples et dans leur format d’origine. À cette fin, nous préconisons un processus d’intégration constitué d’activités séquentielles régies par une couche sémantique, mise en oeuvre via un dépôt partagé de métadonnées. Du point de vue de la gestion, ces activités consistent à déployer une architecture d’intégration de données, suivies de la population de métadonnées partagées. Du point de vue de la consommation de données, les activités sont l’intégration de données virtuelle et matérialisée, la première étant une tâche exploratoire et la seconde, une tâche de consolidation. Conformément au cadre proposé, nous nous attachons à fournir des contributions à chacune des quatre activités. Nous commençons par proposer une architecture logicielle de référence pour les systèmes de gestion de données massives et à connaissance sémantique. Une telle architecture consiste en un schéma directeur pour le déploiement d’une pile de systèmes, le dépôt de métadonnées étant son composant principal. Ensuite, nous proposons un modèle de métadonnées basé sur des graphes comme formalisme pour la gestion des métadonnées. Nous mettons l’accent sur la prise en charge de l’évolution des schémas et des sources de données, facteur prédominant des sources hétérogènes sous-jacentes. Pour l’intégration virtuelle, nous proposons des algorithmes de réécriture de requêtes qui s’appuient sur le modèle de métadonnées proposé précédemment. Nous considérons en outre les hétérogénéités sémantiques dans les sources de données, que les algorithmes proposés sont capables de résoudre automatiquement. Enfin, la thèse se concentre sur l’activité d’intégration matérialisée et propose à cette fin une méthode de sélection de résultats intermédiaires à matérialiser dans des flux des données massives. Dans l’ensemble, les résultats de cette thèse constituent une contribution au domaine de l’intégration des données dans les écosystèmes contemporains de gestion de données massives
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Flamino, Adriana Nascimento. "MARCXML: um padrão de descrição para recursos informacionais em Open Archives." Thesis, Marília : [s.n], 2006. http://eprints.rclis.org/16623/1/FLAMINO_AN_DISSERTACAO.pdf.

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The scientific communication is suffering considerable alterations so much in its process as in its structure and philosophy. The open archives and open access initiatives are contributing significantly for the undoing of the traditional model of scientific communication and for the construction of a new disaggregated model and with interoperability, fairer and efficient to disseminate the research results and like this, the knowledge generated by the scientific communities. However, due to the progresses of the information and communication technologies, not only the structure and the flow of the scientific communication is suffering considerable alterations, as well as the own concept and support of the scientific documents. This has been generating the need of the development of tools to optimize the organization, description, exchange and information retrieval processes, besides the digital preservation, among others. Highlight that the MARC format it has been allowing per decades the description and the exchange of bibliographical and cataloging registrations to the institutions, favoring the access to the contents informacionais contained in several collections. However, with the exponential growth of information and of the documents generation (above all digital), this has been demanding larger flexibility and interoperability among the several information systems available. In this scenery, the XML markup language is presented as one of the current developments that has as purpose to facilitate and to optimize the administration, storage and transmission of contents through Internet, it being incorporate for several sections and areas of the knowledge for the handling easiness and operational flexibility. Front to that, an exploratory study of theoretical analysis was accomplished, identifying the adaptation of the MARCXML format in the construction in ways of descriptive representation for information resources in open archives, as a complex and flexible standard of metadata, that will make possible the interoperability among information systems heterogeneous, besides the access to the information. As result of this research, It's considered that MARCXML is an appropriate format for description of data in a complex structure. It’s ended that the measure that increases the complexity of the documents in the repositories and open archives, plus it’s justified a structure of metadata, as the MARCXML format, that support the description of the pecificities of the informational resources, once this initiative is not and nor it will be if restricting to scientific documents, but expanding the other types of informational resources more and more complex and specific, also demanding an appropriate description for the specificities of the bibliographical entities.
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Park, June Young. "Data-driven Building Metadata Inference." Research Showcase @ CMU, 2016. http://repository.cmu.edu/theses/127.

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Building technology has been developed due to the improvement of information technology. Specifically, a human can control and monitor the building operation by a number of sensors and actuators. The sensors and actuators are installed on every single element in a building. Thus, the large stream of building data allows us to implement both quantitative and qualitative improvements. However, there are still limitations to mapping between the physical building element and cyber system. To solve this mapping issue, last summer, a text mining methodology was developed as part of a project conducted by the Consortium for Building Energy Innovation. Building data was extracted from building 661, in Philadelphia, PA. The ground truth of the building data point with semantic information was labeled by manual inspection. And a Support Vector Machine was implemented to investigate the relationship between the data point name and the semantic information. This algorithm achieves 93% accuracy with unseen building 661 data points. Techniques and lessons were gained from this project, and this knowledge was used to develop the framework for analyzing the building data from the Gates Hillman Center (GHC) building, Pittsburgh PA. This new framework consists of two stages. In the first stage, we initially tried to cluster the data points by similar semantic information, using the hierarchical clustering method. However, the effectiveness and accuracy of the clustering method is not adequate for this framework. Thus, the filtering and classification model is developed to identify the semantic information of the data points. From the filtering and classification method, it correctly identifies the damper position and supply air duct pressure data point with 90% accuracy by daily statistical features. Having the semantic information from the first stage, the second stage figures out the relationship between Variable Air Volume (VAV) terminal units and Air Handling Units (AHU). The intuitive thermal and flow relationship between VAVs and AHUs are investigated at the beginning, and the statistical features clustering method is applied from the VAV discharge temperature data. However, the control strategy of this building makes this relationship invisible. Alternatively we then compared the similarity between damper position at VAVs and supply air duct pressure at AHUs by calculating the cross correlation. Finally, this similarity scoring method achieved 80% accuracy to map the relationship between VAVs and AHUs. The suggested framework will guide the user to find the desired information such as the VAVs – AHUs relationship from the problem generated by a large number of heterogeneous sensor networks by using data-driven methodology.
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Kumar, Aman. "Metadata-Driven Management of Scientific Data." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1243898671.

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Kyhlberg, Erik. "Data om Data : Metadata för geodata inom kommunal översiktsplanering." Thesis, Uppsala universitet, Kulturgeografiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-158528.

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Pradhan, Anup. "The Geospatial Metadata Server : on-line metadata database, data conversion and GIS processing." Thesis, University of Edinburgh, 2000. http://hdl.handle.net/1842/30655.

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This research proposes an on-line software demonstrator called the Geospatial Metadata Server (GMS), which is designed to catalogue, enter, maintain and query metadata using a centralised metadatabase. The system also converts geospatial data to and from a variety of different formats as well as proactively searches for data throughout the Web using an automated hyperlinks retrieval program. GMS is divided into six components, three of which constitute a Metadata Cataloguing tool. The metadatabase is implemented within an RDBMS, which is capable of querying large quantities of on-line metadata in standardised format. The database schema used to store the metadata was patterned in part off of the Content Standard for Digital Geographic Metadata, which provides geospatial data providers and users a common assemblage of descriptive terminology. Because of the excessive length of metadata records, GMS is equipped with a parsing algorithm and database entry utility that is used to enter delimited on-line metadata text files into the metadatabase. Alternatively the system provides a metadata entry and update utility, which is divided into a series of HTML forms each corresponding to a metadatabase table. The utility cleverly allows users to maintain their personal metadata records over the Web. The other three GMS components constitute a Metadata Querying tool. GMS consists of a search engine that can access its metadatabase, examine retrieved information and use the information within on-line server side software. The search engine integrates the metadatabase, on-line geospatial data and GIS software (i.e. the GMS conversion utilities) over the Web. The on-line conversion utilities are capable of converting geospatial data from anywhere on the Web solving many of the problems associated with the interoperability of vendor specific GIS data formats. Because the conversion utilities operate over the Web, the technology is easier to use and more accessible to a greater number of GIS users. Also integrated into the search engine is a Web robot designed to automatically seek out geospatial data from remote Web sites and index their hypertext links within a file or database.
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Books on the topic "Data and metadata structures"

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Chiarcos, Christian, and Sebastian Hellmann. Linked data in linguistics: Representing and connecting language data and language metadata. Edited by Nordoff Sebastian. Heidelberg: Springer, 2012.

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Sebastian, Nordhoff, Hellmann Sebastian, and SpringerLink (Online service), eds. Linked Data in Linguistics: Representing and Connecting Language Data and Language Metadata. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Data model patterns: Conventions of thought. New York: Dorset House Pub., 1996.

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Lyytikäinen, Virps. Contextual and structural metadata in enterprise document management. Edited by Jyväskylän yliopisto. Jyväskylä, Finland: University of Jyväskylä, 2004.

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1961-, Shane Darrell, Ram Prasad, and United States. Defense Advanced Research Projects Agency., eds. IID: An intelligent information dictionary for managing semantic metadata. Santa Monica, CA: Rand, 1991.

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Baofu, Peter. The future of post-human meta-data: Towards a new theory of structure and process in information science. Brisbane, Australia: Primrose Hall Publishing Group, 2015.

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missing], [name. Fundamentals of data warehouses. 2nd ed. Berlin: Springer, 2003.

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Ontology Learning for the Semantic Web. Boston, MA: Springer US, 2002.

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National Information Standards Organization (U.S.). Understanding metadata. Bethesda, MD: NISO Press, 2004.

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Gail, Hodge, and National Information Standards Organization (U.S.), eds. Understanding metadata. Bethesda, MD: NISO Press, 2004.

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Book chapters on the topic "Data and metadata structures"

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Zinke-Wehlmann, Christian, Amit Kirschenbaum, Raul Palma, Soumya Brahma, Karel Charvát, Karel Charvát, and Tomas Reznik. "Linked Data and Metadata." In Big Data in Bioeconomy, 79–90. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_7.

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AbstractData is the basis for creating information and knowledge. Having data in a structured and machine-readable format facilitates the processing and analysis of the data. Moreover, metadata—data about the data, can help discovering data based on features as, e.g., by whom they were created, when, or for which purpose. These associated features make the data more interpretable and assist in turning it into useful information. This chapter briefly introduces the concepts of metadata and Linked Data—highly structured and interlinked data, their standards and their usages, with some elaboration on the role of Linked Data in bioeconomy.
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Nadkarni, Prakash M. "Representing Structured Clinical Data." In Metadata-driven Software Systems in Biomedicine, 55–73. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-510-1_4.

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Khalid, Hiba, Esteban Zimanyi, and Robert Wrembel. "Metadata Reconciliation for Improved Data Binding and Integration." In Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety, 271–82. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99987-6_21.

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Inizan, Olivier, Vincent Fromion, Anne Goelzer, Fatiha Saïs, and Danai Symeonidou. "An Ontology to Structure Biological Data: The Contribution of Mathematical Models." In Metadata and Semantic Research, 57–64. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98876-0_5.

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Sanchez-Alonso, Salvador, Miguel A. Sicilia, Enayat Rajabi, Marçal Mora-Cantallops, and Elena Garcia-Barriocanal. "Class and Instance Equivalences in the Web of Linked Data: Distribution and Graph Structure." In Metadata and Semantic Research, 13–21. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71903-6_2.

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Nadkarni, Prakash M. "Building the User Interface for Structured Clinical Data Capture." In Metadata-driven Software Systems in Biomedicine, 75–108. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-510-1_5.

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Pomares-Quimbaya, Alexandra, Miguel Eduardo Torres-Moreno, and Fabián Roldán. "MetaExtractor: A System for Metadata Extraction from Structured Data Sources." In Availability, Reliability, and Security in Information Systems and HCI, 84–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40511-2_7.

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Leite Cavalcanti, Welchy, Elli Moutsompegka, Konstantinos Tserpes, Paweł H. Malinowski, Wiesław M. Ostachowicz, Romain Ecault, Neele Grundmann, et al. "Integrating Extended Non-destructive Testing in the Life Cycle Management of Bonded Products—Some Perspectives." In Adhesive Bonding of Aircraft Composite Structures, 331–50. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-92810-4_6.

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AbstractIn this chapter, we outline some perspectives on embracing the datasets gathered using Extended Non-destructive Testing (ENDT) during manufacturing or repair process steps within the life cycle of bonded products. Ensuring that the ENDT data and metadata are FAIR, i.e. findable, accessible, interoperable and re-usable, will support the relevant stakeholders in exploiting the contained material-related information far beyond a stop/go decision, while a shorter time-to-information will facilitate a prompter time-to-decision in process and product management. Exploiting the value of ENDT (meta)data will contribute to increased performance by integrating all defined, measured, analyzed and controlled aspects of material transformation across process and company boundaries. This will facilitate the optimization of manufacturing and repair operations, boosting their energy efficiency and productivity. In this regard, some aspects that are currently driving activities in the field of pre-process, in-process and post-process quality assessment will be addressed in the following. Furthermore, some requirements will be contemplated for harmonized and conjoint data transfer ranging from a bonded product’s beginning-of-life through its end-of-life, the customization of stand-alone or linked ENDT tools, and the implementation of sensor arrays and networks in joints, devices and structural parts to gather material-related data during a product’s middle-of-life application phase, thereby fostering structural health monitoring (SHM).
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Bernasconi, Anna. "Model, Integrate, Search... Repeat: A Sound Approach to Building Integrated Repositories of Genomic Data." In Special Topics in Information Technology, 89–99. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85918-3_8.

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AbstractA wealth of public data repositories is available to drive genomics and clinical research. However, there is no agreement among the various data formats and models; in the common practice, data sources are accessed one by one, learning their specific descriptions with tedious efforts. In this context, the integration of genomic data and of their describing metadata becomes—at the same time—an important, difficult, and well-recognized challenge. In this chapter, after overviewing the most important human genomic data players, we propose a conceptual model of metadata and an extended architecture for integrating datasets, retrieved from a variety of data sources, based upon a structured transformation process; we then describe a user-friendly search system providing access to the resulting consolidated repository, enriched by a multi-ontology knowledge base. Inspired by our work on genomic data integration, during the COVID-19 pandemic outbreak we successfully re-applied the previously proposed model-build-search paradigm, building on the analogies among the human and viral genomics domains. The availability of conceptual models, related databases, and search systems for both humans and viruses will provide important opportunities for research, especially if virus data will be connected to its host, provider of genomic and phenotype information.
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Cui, Zhan, Ernesto Damiani, Marcello Leida, and Marco Viviani. "OntoExtractor: A Fuzzy-Based Approach in Clustering Semi-structured Data Sources and Metadata Generation." In Lecture Notes in Computer Science, 112–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11552413_17.

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Conference papers on the topic "Data and metadata structures"

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Mayernik, Matthew S. "Institutional structures for research data and metadata curation." In the 13th ACM/IEEE-CS joint conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2467696.2467755.

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Allen, Robert B., and John Schalow. "Metadata and data structures for the historical newspaper digital library." In the eighth international conference. New York, New York, USA: ACM Press, 1999. http://dx.doi.org/10.1145/319950.319971.

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Klymash, Mykhailo, Ivan Demydov, Mykola Beshley, and Orest Kostiv. "Structures Assessment of Data-Centers’ Telecommunication Systems for Metadata Fixation." In 2018 International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo). IEEE, 2018. http://dx.doi.org/10.1109/ukrmico43733.2018.9047612.

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Guntupally, Kavya, Kyle Dumas, Wade Darnell, Michael Crow, Ranjeet Devarakonda, and Prakash Giri. "Automated Indexing of Structured Scientific Metadata Using Apache Solr." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9378448.

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Wong, John-Michael, and Bozidar Stojadinovic. "Metadata and network API aspects of a framework for storing and retrieving civil infrastructure monitoring data." In Smart Structures and Materials, edited by Masayoshi Tomizuka. SPIE, 2005. http://dx.doi.org/10.1117/12.599803.

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Labban, Ramzi Roy, Stephen Hague, Elyar Pourrahimian, and Simaan AbouRizk. "Dynamic, Data-Driven Simulation In Construction Using Advanced Metadata Structures and Bayesian Inference." In 2021 Winter Simulation Conference (WSC). IEEE, 2021. http://dx.doi.org/10.1109/wsc52266.2021.9715346.

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Li, Shuangyin, Rong Pan, and Jun Yan. "Self-paced Compensatory Deep Boltzmann Machine for Semi-Structured Document Embedding." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/304.

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In the last decade, there has been a huge amount of documents with different types of rich metadata information, which belongs to the Semi-Structured Documents (SSDs), appearing in many real applications. It is an interesting research work to model this type of text data following the way how humans understand text with informative metadata. In the paper, we introduce a Self-paced Compensatory Deep Boltzmann Machine (SCDBM) architecture that learns a deep neural network by using metadata information to learn deep structure layer-wisely for Semi-Structured Documents (SSDs) embedding in a self-paced way. Inspired by the way how humans understand text, the model defines a deep process of document vector extraction beyond the space of words by jointing the metadata where each layer selects different types of metadata. We present efficient learning and inference algorithms for the SCDBM model and empirically demonstrate that using the representation discovered by this model has better performance on semi-structured document classification and retrieval, and tag prediction comparing with state-of-the-art baselines.
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Liem, Inggriani, and Fazat Nur Azizah. "Metadata approach in modeling multi structured data collection using object oriented concepts." In 2010 International Conference on Networking and Information Technology (ICNIT 2010). IEEE, 2010. http://dx.doi.org/10.1109/icnit.2010.5508560.

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Kuznetcov, Yevgeni, Maxim Fomin, and Andrei Vinogradov. "Multidimensional Information Systems Metadata Repository Development with a Data Warehouse Structure Using "Data Vault" Methodology." In CSIS'2019: XI INTERNATIONAL SCIENTIFIC CONFERENCE COMMUNICATIVE STRATEGIES OF THE INFORMATION SOCIETY. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3373722.3373777.

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Drakopoulos, Georgios, Evaggelos Spyrou, Yorghos Voutos, and Phivos Mylonas. "A semantically annotated JSON metadata structure for open linked cultural data in Neo4j." In PCI '19: 23rd Pan-Hellenic Conference on Informatics. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3368640.3368659.

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Reports on the topic "Data and metadata structures"

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Lingner, Stefan, Karl Heger, and Claas Faber. MAMS Image Broker. GEOMAR, December 2022. http://dx.doi.org/10.3289/sw_3_2022.

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The GEOMAR Helmhotz Centre for Ocean Research Kiel is operating a Media Asset Management System (MAMS) which manages large amounts image- and video data. Similar systems are operated by the Helmholtz Centre HEREON and by the Alfred Wegener Institute (AWI). Although the MAMS system provides access to data and metadata using an API, it is not possible to directly request image data without prior knowledge of the internal MAMS data structure. The image broker is a web service which brokers between a client (e.g. web-browser) and the MAMS. It allows users to request images by metadata values (e.g. image uuid). The broker uses the [IIIF](https://iiif.io/) standard which allows users to request the images in different formats, scaled copies or only specific parts of the image.
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Andersson, Jacob, Marie Gustafsson Friberger, Jessica Lindholm, and Julian Togelius. Gamification of publication metadata : to playfully explore our data. Malmö University Library, January 2015. http://dx.doi.org/10.24834/2043/20256.

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Gaylord, J. M., D. A. Dodge, S. A. Magana-Zook, J. G. Barno, D. R. Knapp, J. M. Thomas, D. S. Sullivan, S. D. Ruppert, and R. J. Mellors. Scalable Metadata Management for a Large Multi-Source Seismic Data Repository. Office of Scientific and Technical Information (OSTI), May 2017. http://dx.doi.org/10.2172/1389997.

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Roch, Marie A., Simone Baumann-Pickering, John A. Hildebrand, Catherine L. Berchok, Erin M. Oleson, and Sofie M. Van Parijs. Acoustic Metadata Management and Transparent Access to Networked Oceanographic Data Sets. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada605082.

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Gaylord, J. M., D. A. Dodge, S. A. Magana-Zook, J. G. Barno, and D. R. Knapp. Scalable Metadata Management for a Large Multi-Source Seismic Data Repository. Office of Scientific and Technical Information (OSTI), April 2017. http://dx.doi.org/10.2172/1357348.

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Roch, Marie A., Simone Baumann-Pickering, Catherine L. Berchok, John A. Hildebrand, Erin M. Oleson, and Sofie M. Van Parijs. Acoustic Metadata Management and Transparent Access to Networked Oceanographic Data Sets. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada571556.

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Roch, Marie A., Simone Baumann-Pickering, John A. Hildebrand, and Catherine L. Berchok. Acoustic Metadata Management and Transparent Access to Networked Oceanographic Data Sets. Fort Belvoir, VA: Defense Technical Information Center, September 2014. http://dx.doi.org/10.21236/ada623424.

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Mix, Scott, Mark Rice, Siddharth Sridhar, Charles Schmidt, Srini Raju, Carlos Gonzales-Perez, and Debraj Bharadwaj. Universal Utility Data Exchange (UUDEV) - Data Structures. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1778856.

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Fadaie, K., M. Habbane, and C. D. O'Brien. Extensions to ISO/TC 211 - 19115.3 Metadata to Support Imagery and Gridded Data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2000. http://dx.doi.org/10.4095/219709.

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Arndt, Witold. A survey on research data management practices among researchers in the Helmholtz Association. HMC Office, GEOMAR Helmholtz Centre for Ocean Research Kiel, 2022. http://dx.doi.org/10.3289/hmc_publ_05.

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Annotation of research data with rich metadata is important to make that data findable, accessible, interoperable, and reusable (Wilkinson et al. [2016]). This ensures the conducted research data is durable. Within the Helmholtz Association, the Helmholtz Metadata Collaboration (HMC) coordinates the mission to enrich Helmholtz-based research data with metadata by providing (information about) technical solutions, advice and ensuring uniform scientific standards for the use of metadata. In 2021, HMC conducted its first community survey to align its services with the needs of Helmholtz researchers. A question catalogue with 49 (sub-)questions was designed and disseminated among researchers in all six Helmholtz research fields. The conditional succession of the questions was aligned with predetermined expertise levels ("no prior knowledge", "intermediate prior knowledge", "high level of prior knowledge"). 631 completed survey replies were obtained for analysis. The HMC Community Survey 2021 provides insight into the management of research data as well as the data publication practices of researchers in the Helmholtz Association. The characterization of research-field-dependent communities will enable HMC to further develop targeted, community-directed support for the documentation of research data with metadata.
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