Metadata repository

About: Metadata repository is a research topic. Over the lifetime, 5841 publications have been published within this topic receiving 121778 citations.

System and method for managing content including addressability features

Abstract: A system and method for electronic file management includes an object-oriented file management database, a volume manager, and a coherency manager. The volume manager manages electronic files and metadata relating to the files of one or more volumes. Each volume may include folders, files, and/or other digital content. The file management system organizes files based on the metadata related to each file. The metadata may include automatically generated metadata or user-defined metadata. A user interface facilitates user interaction with the file management system.

Multi-modal face recognition

Abstract: A method for identifying an individual includes the steps of collecting data from an individual's face using visible and infrared cameras, processing the acquired data, fitting a geometric model template of the face to the data according to a mathematical method, processing the fitted model to extract relevant first metadata, storing the first metadata in a machine readable format, and comparing second metadata to the first metadata, to determine their degree of similarity in order to identify the individual.

Optimizations for an unbounded transactional memory (utm) system

Abstract: A method and apparatus for optimizing an Unbounded Transactional Memory (UTM) system is herein described. Hardware support for monitors, buffering, and metadata is provided, where orthogonal metaphysical address spaces for metadata may be separate associated with threads and/or software subsystems within threads. In addition, the metadata may be held with hardware in a compressed manner with regard to data transparently to software. Furthermore, in response to metadata access instruction/operations the hardware is capable of supporting a forced metadata value to enable multiple modes of transactional execution. However, if monitors, buffered data, metadata, or other information is lost or conflicts are detected hardware provides for variations of a loss instruction that is able to poll a transaction status register for such loss or conflict and jump execution to a label in response to detecting the loss or conflict. Similarly, multiple variations of a commit instruction are provided for to allow software to define commit conditions and information to clear upon commit. Furthermore, hardware provides support to enable suspension and resume of transactions upon ring level transitions.

Sensor Metadata Management and Its Application in Collaborative Environmental Research

Abstract: This paper considers metadata generation and tracking in a collaborative environment where users publish raw sensor data in the form of virtual sensors and post-process data by means of filtering, modeling, or query processing techniques. In the metadata system described, data from different sources with different provenance will be enriched with further metadata at each processing step to describe the processing implemented and/or observations which may explain anomalies in the data. The management of this data is the subject of this paper. In the context of sensor data processing, in particular in the environmental sciences, there is still a large gap between data acquisition and metadata gathering, further complicated by the problem of combining both. In this paper, an attempt is made to bridge the gap between data management and semantic annotation. This paper describes a user friendly, easily deployable system for gathering sensor metadata and capturing semantics behind higher level data processing steps. These semantics are particularly useful in understanding data processing workflows. Furthermore, different methods of querying, exporting and importing gathered data from and to higher level applications are examined.

Deriving semantic sensor metadata from raw measurements

Abstract: Sensor network deployments have become a primary source of big data about the real world that surrounds us, measuring a wide range of physical properties in real time. With such large amounts of heterogeneous data, a key challenge is to describe and annotate sensor data with high-level metadata, using and extending models, for instance with ontologies. However, to automate this task there is a need for enriching the sensor metadata using the actual observed measurements and extracting useful meta-information from them. This paper proposes a novel approach of characterization and extraction of semantic metadata through the analysis of sensor data raw observations. This approach consists in using approximations to represent the raw sensor measurements, based on distributions of the observation slopes, building a classification scheme to automatically infer sensor metadata like the type of observed property, integrating the semantic analysis results with existing sensor networks metadata.