Dieter Pfoser, Athens Hellas · 2008
Emerging computational paradigms such as global and ubiquitous computing require some rethinking and innovative research ideas in many computer science areas. In this work, we aim at studying a mobile computing scenario from the database perspective. Given a global computing environment in which data is kept in a number of small-scale, data-charged, mobile devices that use, e.g., wireless networks, for communication, we want to assess the overall data scenario. We use an example to abstract the requirements to such a computing environment and to outline the various existing types of data. Included here are some metadata proposals related to the actual data stored in the device (content data) as well as to the data necessary to the functioning of the device within the computing environment (profile data). The metadata proposals are based on well-known languages and tools such as XML, RDF, UML, and ontologies.
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Apress eBooks · 2006
In this chapter you considered the nature of metadata, which is becoming ever more crucial. If you take the example of an order entry system, you now know that metadata isn’t the orders in the order entry system but rather the following: Statistics about the orders Information regarding an order’s makeup The manner in which orders are organized and stored Who can access the order data What users can do with orders Where the order data flows to and from How the order data gets there What the origins of the structure of an order are Who created the order entry system What project created the order entry system What problem the order entry system solves
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Martínez-Durive, Orlando Eduardo, Bakirtzis, Stefanos, ZIEMLICKI, Cezary et al. · Zenodo (CERN European Organization for Nuclear Research) · 2025
Metadata geolocation, i.e., mapping information collected at a cellular Base Station (BS) to the geographical area it covers, is a central operation in producing statistics from mobile network measurements. This task requires modeling the probability that a device attached to a BS is at a specific location, and it is currently accomplished via simplistic approximations based on Voronoi tessellations. However, Voronoi cells exhibit poor accuracy compared to real-world geolocation data, which can reduce the reliability of downstream research pipelines. To overcome this limitation, DEEPMEND proposes a new data-driven approach relying on a teacher-student paradigm that combines probabilistic inference and deep learning. Similar to other benchmarks, DEEPMEND can produce geolocation maps using only the BS positions, yielding a 56% accuracy gain compared to Voronoi tessellations. Our demonstrator will show visual and qualitative comparisons between DEEPMEND and several competitor approaches, allowing users to explore BS deployments from different geographical regions and operators.
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Martínez-Durive, Orlando Eduardo, Bakirtzis, Stefanos, ZIEMLICKI, Cezary et al. · Zenodo (CERN European Organization for Nuclear Research) · 2025
Metadata geolocation, i.e., mapping information collected at a cellular Base Station (BS) to the geographical area it covers, is a central operation in producing statistics from mobile network measurements. This task requires modeling the probability that a device attached to a BS is at a specific location, and it is currently accomplished via simplistic approximations based on Voronoi tessellations. However, Voronoi cells exhibit poor accuracy compared to real-world geolocation data, which can reduce the reliability of downstream research pipelines. To overcome this limitation, DEEPMEND proposes a new data-driven approach relying on a teacher-student paradigm that combines probabilistic inference and deep learning. Similar to other benchmarks, DEEPMEND can produce geolocation maps using only the BS positions, yielding a 56% accuracy gain compared to Voronoi tessellations. Our demonstrator will show visual and qualitative comparisons between DEEPMEND and several competitor approaches, allowing users to explore BS deployments from different geographical regions and operators.
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Chari, Tara · CaltechDATA · 2024
Metadata for the ClickTag multiplexed mouse NSCs used in analysis.
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Maria Vardaki · IGI Global eBooks · 2011
The term metadata is frequently used in many different sciences. Statistical metadata generally used to denote “every piece of information required by a data user to properly understand and use statistical data.” Modern statistical information systems (SIS) use metadata in relational or complex object-oriented metadata models, making an extensive and active usage of metadata. Early phases of many software development projects emphasize the design of a conceptual data/metadata model. Such a design can be detailed into a logical data/metadata model. In later stages, this model may be translated into physical data/metadata model. Organisations aspects, user requirements and constraints created by existing data warehouse architecture lead to a conceptual architecture for metadata management, based on a common, semantically rich, object-oriented data/metadata model, integrating the main steps of data processing and covering all aspects of data warehousing (Pool et al, 2002). In this paper we examine data/metadata modeling according to the techniques and paradigms used for metadata schemas development. However, only the integration of a model into a SIS is not sufficient for automatic manipulation of related datasets and quality assurance, if not accompanied by certain operators/ transformations. Two types of transformations can be considered: (i) the ones used to alleviate breaks in the time series and (ii) a set of model-integrated operators for automating data/metadata management and minimizing human errors. This latter category is extensively discussed. Finally, we illustrate the applicability of our scientific framework in the area of Biomedical statistics. Request access from your librarian to read this chapter's full text.
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Jinane N. Hashem · 2005
M.S. -- Faculty of Natural and Applied Sciences, Notre Dame University, Louaize, 2005; A thesis submitted for partial fulfillment of the requirements for the degree of Masters in Computer Information Systems, Department of Computer Science, Faculty of Natural and Applied Sciences, Notre Dame University; Includes bibliographical references (leaves 88-89).
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Ainslie, M.A. · Figshare · 2018
A lack of globally applied standards for underwater acoustic measurements (soundscapes) means that different researchers make different choices for frequency ranges and time averaging windows, often referring to the resulting plethora of different quantities with identical names, making it difficult, and sometimes impossible, to compare like with like.<br>This document, the ADEON Underwater Soundscape and Modeling Metadata Standard, is the first of five standardization products. Its purpose is to specify a minimum metadata standard for measured and predicted OCS soundscapes in the US EEZ. It is intended to be used as a tool to facilitate direct comparisons between soundscapes reported by different projects. Compliance with this standard in no way precludes calculation of metrics not specified by the standard or of the same metrics in different frequency bands or averaging intervals.<br>
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Terje Brasethvik · Internet Research · 1998
States that heterogeneous project groups today may be expected to use the mechanisms of the Web for sharing information. Metadata has been proposed as a mechanism for expressing semantics of information and, hence, facilitate information retrieval, understanding and use. Presents an approach to sharing of information which aims to use a semantic modeling language as the basis for expressing semantics of information and designing metadata schemes. Functioning in the borderlines between human and computer understandability, the modeling language could be able to express semantics of published Web documents. Reporting on work in progress, the paper presents the overall framework and ideas.
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Pérez-Blanco, C. Dionisio, González-López, Héctor, Sapino, Francesco et al. · Zenodo (CERN European Organization for Nuclear Research) · 2024
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Sameer Avinash Kibey · Digital Repository at the University of Maryland (University of Maryland College Park) · 2007
In this Thesis, we focus on problems in surveillance video analysis and propose advanced metadata modeling techniques to address them. First, we explore the problem of constructing a snapshot summary of people in a video sequence. We propose an algorithm based on the eigen-analysis of faces and present an evaluation of the method. Second, we present an algorithm to learn occlusion points in a scene using long observations of moving objects, provide an implementation and evaluate its performance. Third, to address the problem of availability and storage of surveillance videos, we propose a novel methodology to simulate video metadata. The technique is completely automated and can generate metadata for any scenario with minimal user interaction. Finally, a threat detection model using activity analysis and trajectory data of moving objects is proposed and implemented. The collection of tools presented in this Thesis provides a basis for higher level video analysis algorithms.
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Yan Lu, Boonserm Kulvatunyou, Dimitrije Milenković et al. · 2024
The continuous digitalization in manufacturing directly leads to a significant increase in "data volume", while digital transformation is expanding the exchange scenarios of such data. Managing metadata, the description of data, is a foundational aspect of successful enterprise digital transformation. By providing clarity and structure of data, metadata models and standards ensure that data can be discovered, accessed, shared and used effectively across the organization, driving better decision-making, improving operational efficiency, and supporting compliance. This report examines common manufacturing enterprise metadata exchange scenarios, analyzes and compares existing metadata standards using the Findable, Accessible, Interoperable and Reusable (FAIR) principles. Based on the metadata standards reviewed and a FAIR data metadata stack model, we propose a uniform, general, and extendable metadata model which not only captures essential metadata elements for Findability, Accessibility, and Interoperability but also uses an extendable metadata model for (Re)usability. An extension of the proposed Uniform Metadata Model for Manufacturing Enterprise Integration is demonstrated for industrial measurement dataset metadata representation. Additional general metadata elements are identified for measured, sampled data, and derived stream descriptions. The report concludes with a direction for manufacturing metadata standards development.
Cited by 1Open access
Silva, David Joseph, Steele, Ekwan D., Bird, John David · Digital WPI · 2000
This project designed and implemented an interface to be housed on Fleet Bank's internal computer system. It assisted Fleet's business analysts in grasping the concepts behind its Data Warehouse. The actual interface used Adobe Acrobat as its engine and contained visual subject models designed through Sybase PowerDesigner. Its basic utility and strength lay in offering a visual aid that greatly facilitated the analysts' task in understanding the Data Warehouse structure as a whole.
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Ainslie, M.A., Miksis-Olds, J.L., Martin, B. et al. · Figshare · 2018
A lack of globally applied standards for underwater acoustic measurements (soundscapes) means that different researchers make different choices for frequency ranges and time averaging windows, often referring to the resulting plethora of different quantities with identical names, making it difficult, and sometimes impossible, to compare like with like.<br>This document, the ADEON Underwater Soundscape and Modeling Metadata Standard, is the first of five standardization products. Its purpose is to specify a minimum metadata standard for measured and predicted OCS soundscapes in the US EEZ. It is intended to be used as a tool to facilitate direct comparisons between soundscapes reported by different projects. Compliance with this standard in no way precludes calculation of metrics not specified by the standard or of the same metrics in different frequency bands or averaging intervals.<br>
Cited by 1Open access
O. David A, I. W. Schneider B, G. H. Leavesley C · 2008
Abstract: The main motivation for the usage of modeling frameworks for environmental simulation software is to manage and simplify the interoperability of (loosely) coupled simulation components. Conventional approaches in collaboration are using an Application Programming Interface (API). Recent developments in simulation frameworks focus on introspecting architectures for simulation components, where components become passively explored and integrated in to the framework. Such solutions seem to be more flexible to support the framework evolution because components are less tight to a specific framework API. The Object Modeling System (OMS) is an introspecting simulation framework, which uses metadata in annotated components such as (i) spatial and temporal constraint specification, (ii) data annotation for variables and parameters to specify simulation related data like runtime constraints for range validation, unit conversion, or automated testing. The OMS utilizes metadata annotation (i) at model construction time to support proper spatial and temporal model assembly (ii) and at model runtime to support proper data linkage. This paper will emphasize on metadata access to support model linkage to simplify the development of simulation components for environmental scientists and will give application examples based on the Object Modeling System
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The Web Ayse, S. Ayse Özel, I. Sengör Altingövde et al. · 2004
This paper deals with the problem of modeling Web information resources using expert knowledge and personalized user information for improved Web searching capabilities. We propose a &quot;Web information space&quot; model, which is composed of Web-based information resources (HTML/XML [Hypertext Markup Language/Extensible Markup Language] documents on the Web), expert advice repositories (domain-expert-specified metadata for information resources), and personalized information about users (captured as user profiles that indicate users&apos; preferences about experts as well as users&apos; knowledge about topics)
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Francisco B. Valero, Marion Baranes, Elena V. Epure · arXiv (Cornell University) · 2022
Podcasts have emerged as a massively consumed online content, notably due to wider accessibility of production means and scaled distribution through large streaming platforms. Categorization systems and information access technologies typically use topics as the primary way to organize or navigate podcast collections. However, annotating podcasts with topics is still quite problematic because the assigned editorial genres are broad, heterogeneous or misleading, or because of data challenges (e.g. short metadata text, noisy transcripts). Here, we assess the feasibility to discover relevant topics from podcast metadata, titles and descriptions, using topic modeling techniques for short text. We also propose a new strategy to leverage named entities (NEs), often present in podcast metadata, in a Non-negative Matrix Factorization (NMF) topic modeling framework. Our experiments on two existing datasets from Spotify and iTunes and Deezer, a new dataset from an online service providing a catalog of podcasts, show that our proposed document representation, NEiCE, leads to improved topic coherence over the baselines. We release the code for experimental reproducibility of the results.
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Filipe A. Santana, André F. R. Cordeiro, Edson OliveiraJr · 2023
Metadata consists of elements that describe specific content of data. When structured according to standards, they contribute to data interoperability. This study presents a secondary study, a Systematic Mapping (SM), to search for metadata patterns that can be used in the field of Computer Science (CS), especially in the subjects of Software Engineering (SE) and Information Systems (IS). At the end of the search string execution, 43 studies were analyzed. Of these, 23 studies were selected. Based on the observed results, a promising research area is identified, focusing on the adoption of metadata standards in various activities within the context of CS, SE, and IS.
Cited by 2Open access
Cheung, Kei-Hoi · OpenCommons - UConn (University of Connecticut) · 1998
With evolution of scientific knowledge, knowledge within a scientific domain is accumulated within multiple databases maintained by separate groups of researchers. While information across all these databases is semantically related, the individual databases are characterized by different data models, query languages, and user interfaces. There is a growing need for exchanging such semantically related data for detection of redundancies and inconsistencies in both the primary (experimental) data as well as the secondary (inferred) data contained in the databases. However, due to the heterogeneities involved, it is difficult for users of these structurally different databases to query each other's data. To address such a problem, this dissertation proposes a system that allows users to query a set of semantically similar databases based on their existing schema knowledge. ^ The proposed system consists of a query mapping module that automatically maps a (source) query issued against one database schema to an equivalent (target) query against another database schema. The source query may be composed directly by the user using a query language such as SQL. Alternatively, the user can specify the query via a graphical front end (e.g., a query form). Such a graphical query interface is generated dynamically and is tailored to the schema knowledge of the user. The user input, which is accepted by the graphical interface, is converted into the corresponding database query by a “query generator”. ^ Underlying our system is a metadata, model that extends the entity-relationship (ER) model to describe and establish mappings between components among individual databases. The metadata model also includes constructs such as inheritance and aggregation. To facilitate database comparisons, additional information, which is not modeled explicitly in the original database schemas, is described in the metamodel. Such additional information is modeled in the form of hidden entities/attributes/relationships, meta-attributes, and domain constraints. ^ In addition to describing database objects, the model captures metadata that are used to dynamically generate schema-specific graphical query interfaces. As a demonstration, we apply our system to perform query mappings between two genome databases, namely, DB/12 and GDB. ^
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Abdoulmajid Hakki · 2007
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