Flexible Metadata Research Articles

The Getty Research Portal: a decade of progress and developments for the future

At its inception in 2012, the Getty Research Portal shattered barriers that previously made digitized resources for art historical research challenging to locate and use without restriction. The Portal's first 10 years were marked by a period of immense growth, forging connections among collections through institutional partnerships. Flexible metadata requirements for contributing to the Portal allows large and small institutions alike to contribute a diverse range of collections but also present ongoing challenges. Work with partner institutions to identify priorities for metadata creation, cataloguing, and imaging has contributed to collection building on a global scale. Various forms of access to Portal materials have been developed alongside collection development efforts to meet new methods in art historical research. Looking to the future, the goals that were set out when the Portal was initiated continue to be the driving force behind what the Portal provides for an ever-evolving field. Ongoing work on the platform is intended to meet the shifting methodology of art historical research through the Portal's established collaborative model and open the door to new questions, new lines of inquiry, and ultimately new conclusions within art history.

Public History e Metadata Da fonti a oggetti informativi. Diffusione, didattica, co-creazione

The dematerialisation of information and the development of Information Systems combined with the use of flexible metadata standards enable a new accessibility for the sources. Matching this new accessibility with the bottom-up historiographic production promoted by Public History enables the development of new forms of history teaching and the generation of information objects through participatory metadata creation with a community of reference. Through the analysis of three different cases, this article brings out the importance of metadata for the organisation, archiving and use of historical sources in a Public History perspective.

SODAS: Smart Open Data as a Service for Improving Interconnectivity and Data Usability

In this study, we proposed Smart Open Data as a Service (SODAS) as a new open data platform based on the international standards Data Catalog Vocabulary (DCAT) and Comprehensive Knowledge Archive Network (CKAN) to facilitate the release and sharing of data. We first analyze the five problems in the legacy CKAN and then draw up corresponding solutions through three core strategies: CKAN expansion, DCATv2 support, and extendable DataMap. We then define four components and nine function blocks of SODAS for each core strategy. As a result, SODAS drives Open Data Portal, Open Data Reference Model, DataMap Publisher, and Analytics and Development Environment (ADE) Provisioning for connecting the defined function blocks. We confirm that each function works correctly through the SODAS Web portal, and then we apply SODAS to actual data distribution sites to prove its efficiency and practical use. SODAS is the first open data platform that provides secure interoperability between heterogeneous platforms based on international standards, and it enables domain-free data management with flexible metadata.

A Flexible, Extensible, Machine-Readable, Human-Intelligible, and Ontology-Agnostic Metadata Schema (OIMS)

This paper presents a lightweight, flexible, extensible, machine readable and human-intelligible metadata schema that does not depend on a specific ontology. The metadata schema for metadata of data files is based on the concept of data lakes where data is stored as they are. The purpose of the schema is to enhance data interoperability. The lack of interoperability of messy socio-economic datasets that contain a mixture of structured, semi-structured, and unstructured data means that many datasets are underutilized. Adding a minimum set of rich metadata and describing new and existing data dictionaries in a standardized way goes a long way to make these high-variety datasets interoperable and reusable and hence allows timely and actionable information to be gleaned from those datasets. The presented metadata schema OIMS can help to standardize the description of metadata. The paper introduces overall concepts of metadata, discusses design principles of metadata schemes, and presents the structure and an applied example of OIMS.

A user-centric metadata model to foster sharing and reuse of multidisciplinary datasets in environmental and life sciences

The recent technological advancements and emergence of the open data in environmental and life sciences are opening new research opportunities while creating new challenges around data management. They make available an unprecedented amount of data that can be exploited for studying complex phenomena. However, new challenges related to data management need to be addressed to ensure effective data sharing, discovery and reuse, especially when dealing with interdisciplinary research contexts. These issues are magnified in interdisciplinary context, by the fact that each discipline has its practices, e.g., specific formats and metadata standards. Moreover, the majority of current data management practices do not consider semantic heterogeneity existing among disciplines. For this reason, we introduce a flexible metadata model that describes the datasets of various disciplines using a common paradigm based on the observation concept. It provides a key vision for articulating the user point of view and underlying scientific domains. In this study, we therefore decide to mainly reuse the SOSA lightweight ontology (Sensor, Observation, Sample, and Actuator) to efficiently leverage others existing ontologies to improve datasets discovery and reuse coming from Earth and life observation. The main benefit of the proposed metadata model is that it extends the technical description, usually provided by existing metadata models, with the observation context description enabling the need of a user viewpoint. Moreover, following the FAIR principles, the metadata model specifies the semantics of its elements using ontologies and vocabularies, and reuses as much as possible ontological and terminological existing resources. We show the benefit and applicability of the model through a case study we identified as representative after interviewing researchers in environmental and life sciences.

AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata

BackgroundMetagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and prevalence of antibiotic resistance genes (ARGs) across multiple studies and environments is currently impossible without a complete re-analysis of published datasets. This challenge must be addressed for metagenomics to realize its potential for helping guide effective policy and practice measures relevant to agricultural ecosystems, for example, identifying critical control points for mitigating the spread of antibiotic resistance.ResultsHere we introduce AgroSeek, a centralized web-based system that provides computational tools for analysis and comparison of metagenomic data sets tailored specifically to researchers and other users in the agricultural sector interested in tracking and mitigating the spread of ARGs. AgroSeek draws from rich, user-provided metagenomic data and metadata to facilitate analysis, comparison, and prediction in a user-friendly fashion. Further, AgroSeek draws from publicly-contributed data sets to provide a point of comparison and context for data analysis. To incorporate metadata into our analysis and comparison procedures, we provide flexible metadata templates, including user-customized metadata attributes to facilitate data sharing, while maintaining the metadata in a comparable fashion for the broader user community and to support large-scale comparative and predictive analysis.ConclusionAgroSeek provides an easy-to-use tool for environmental metagenomic analysis and comparison, based on both gene annotations and associated metadata, with this initial demonstration focusing on control of antibiotic resistance in agricultural ecosystems. Agroseek creates a space for metagenomic data sharing and collaboration to assist policy makers, stakeholders, and the public in decision-making. AgroSeek is publicly-available at https://agroseek.cs.vt.edu/.

LabPipe: an extensible bioinformatics toolkit to manage experimental data and metadata

BackgroundData handling in clinical bioinformatics is often inadequate. No freely available tools provide straightforward approaches for consistent, flexible metadata collection and linkage of related experimental data generated locally by vendor software.ResultsTo address this problem, we created LabPipe, a flexible toolkit which is driven through a local client that runs alongside vendor software and connects to a light-weight server. The toolkit allows re-usable configurations to be defined for experiment metadata and local data collection, and handles metadata entry and linkage of data. LabPipe was piloted in a multi-site clinical breathomics study.ConclusionsLabPipe provided a consistent, controlled approach for handling metadata and experimental data collection, collation and linkage in the exemplar study and was flexible enough to deal effectively with different data handling challenges.

The SPECCHIO Spectral Information System

Spectral Information Systems provide a framework to assemble, curate, and serve spectral data and their associated metadata. This article documents the evolution of the SPECCHIO system, devised to enable long-term usability and data-sharing of field spectroradiometer data. The new capabilities include a modern, web-based client-server architecture, a flexible metadata storage scheme for generic metadata handling, and a rich application programming interface, enabling scientists to directly access spectral data and metadata from their programming environment of choice. The SPECCHIO system source code has been moved into the open source domain to stimulate contributions from the spectroscopy community while binary distributions, including the SPECCHIO virtual machine, simplify the installation and use of the system for the end-users.

Flexible Metadata based Document Management System for Research Organization

Flexible Metadata based Document Management System for Research Organization

Understanding Connections: Examining Digital Library and Institutional Repository Use Overlap

The University of North Texas Libraries’ Digital Collections are situated as a unified whole within their preservation infrastructure, with three separate user interfaces serving the content to different audiences. These separate interfaces are: The UNT Digital Library (DL), The Portal to Texas History, and The Gateway to Oklahoma History. Situated within each interface are collections, and hosted within these collections are digital objects. One collection, the UNT Scholarly Works Repository, specifically serves UNT’s research and creative contributions and functions as the Institutional repository (IR) for the University of North Texas. Because UNT Scholarly works is seated as a collection amongst other collections, users can access faculty research, not just out of an interest in research from specific faculty members, but also as it ties into the user’s broader understanding of a given topic. With flexible infrastructure and metadata schema that connect collections beneath the umbrella of the wider preservation infrastructure, the UNT DL employs full-text searching and interlinked metadata to strengthen and make visible the connections between objects in different collections. This paper examined how users navigated between other collections within the UNT IR, as well as within the UNT DL. Through this examination, we observed patterns between how users navigated between objects, understood which collections may have related to one another, examined why some unique items were used more than others, and viewed the average number of items used within a session.

Analytical metadata modeling for next generation BI systems

Business Intelligence (BI) systems are extensively used as in-house solutions to support decision-making in organizations. Next generation BI 2.0 systems claim for expanding the use of BI solutions to external data sources and assisting the user in conducting data analysis. In this context, the Analytical Metadata (AM) framework defines the metadata artifacts (e.g., schema and queries) that are exploited for user assistance purposes. As such artifacts are typically handled in ad-hoc and system specific manners, BI 2.0 argues for a flexible solution supporting metadata exploration across different systems.In this paper, we focus on the AM modeling. We propose SM4AM, an RDF-based Semantic Metamodel for AM. On the one hand, we claim for ontological metamodeling as the proper solution, instead of a fixed universal model, due to (meta)data models heterogeneity in BI 2.0. On the other hand, RDF provides means for facilitating defining and sharing flexible metadata representations. Furthermore, we provide a method to instantiate our metamodel. Finally, we present a real-world case study and discuss how SM4AM, specially the schema and query artifacts, can help traversing different models instantiating our metamodel and enabling innovative means to explore external repositories in what we call metamodel-driven (meta)data exploration.

Setting out on an unknown sea – an extremely flexible metadata model for the "Engelandvaarders" collection (a case study)

Setting out on an unknown sea – an extremely flexible metadata model for the "Engelandvaarders" collection (a case study)

SaaS Level based Middleware Database Integrator Platform

In purpose of data searching acceleration, the fastest data response is the major concern for latest cloud environment. Regarding this, the intellectual decision is to enrich the SaaS level applications. Amongst the SaaS based applications, service level database integration is the recent trend to provide the integrated view of the heterogeneous cloud databases through shared services using DBaaS. But the generic limitations interacted during the database integration are dynamic adaptability of multiple databases structure, dynamic data location identification in the concern databases, data response using the data commonality. Data migration technique and single query approach are the two individual solutions for the proposed limitations. But the side effects during data migration technique are extra space utilisation and excess time consumption. Again, the single query approach suffers from worst case time complexity for data connectivity, data aggregation and query evaluation. So, to find a suitable data response solution by eliminating these combined major issues, a graph based Middleware Database Integrator Platform or MDIP model has been proposed. This integrator platform is actually the flexible metadata representation technique for the concerned heterogeneous cloud databases. The associativity and commonality among components of multiple databases would be further helpful for efficient data searching in an integrated way. For the incorporation within the service level but not in the services, MDIP is considered as the different platform. It is applicable over any service based database integration in purpose of data response efficiency. Finally, the quality assessment using evaluated query time compared with already proposed SLDI shows better data access quality. Thus, its expertise dedication in data response can overcome summarised challenges like data adaptation flexibility, dynamic identification of data location, wastage of data storage, data accessing within minimal time span and optimised cost in presence of data consistency, data partitioning and user side scalability.

Reusing Components from Cultural Heritage Games – the RAGE Project Approach

Video games proved to be an attractive media for presenting cultural heritage issues. They can use virtual worlds to present cultural and historic information in amazing and highly appealing way. Each video game is implemented using set of valuable artifacts (components) reflecting technological, socioeconomic and historical issues. These software components are known as software assets, which are key output of the RAGE project. They can be used by game developers to enhance the pedagogical and educational value of their games. These software assets cover a broad spectrum of functionalities, including emotion detection, intelligent adaptation and social gamification. In order to facilitate integration and interoperability, all of these assets adhere to a common model, which describes their properties through a set of metadata. In this paper, we present the RAGE asset model and asset metadata model, highlighting key issues and challenges in constructing RAGE assets and using asset metadata model with flexible metadata editor, facilitating both adaptation and improvement of the asset metadata model.

A comparison of research data management platforms: architecture, flexible metadata and interoperability

Research data management is rapidly becoming a regular concern for researchers, and institutions need to provide them with platforms to support data organization and preparation for publication. Some institutions have adopted institutional repositories as the basis for data deposit, whereas others are experimenting with richer environments for data description, in spite of the diversity of existing workflows. This paper is a synthetic overview of current platforms that can be used for data management purposes. Adopting a pragmatic view on data management, the paper focuses on solutions that can be adopted in the long tail of science, where investments in tools and manpower are modest. First, a broad set of data management platforms is presented—some designed for institutional repositories and digital libraries—to select a short list of the more promising ones for data management. These platforms are compared considering their architecture, support for metadata, existing programming interfaces, as well as their search mechanisms and community acceptance. In this process, the stakeholders’ requirements are also taken into account. The results show that there is still plenty of room for improvement, mainly regarding the specificity of data description in different domains, as well as the potential for integration of the data management platforms with existing research management tools. Nevertheless, depending on the context, some platforms can meet all or part of the stakeholders’ requirements.

A metadata model for cross-domain marine data management, the SeaDataNet/Geo-Seas experience

Data management in the marine sciences faces the complex issue of addressing contrasting cognitive models across scientific domains, meaning the various representations that different communities build for overlapping areas of interest. Each of these communities constructs an identity on a specific and personal set of inherited backgrounds, practices, and tacit knowledge, which are mirrored in how they understand the targets of their studies. From a practical point of view, this can result in mis-linking observations and usage. This paper reports on the work done within the EU FP7 SeaDataNet project to tackle such problems through an integrated discovery and data access paradigm. It is based on a flexible metadata model that allows researchers to link domain-specific metadata profiles encoded using SensorML OGC standard, the general discovery framework based on an ISO 19115/19139 profile called CDI, and the data through a common hub based on the Observations and Measurements OGC standard.

Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications

This paper presents an approach to developing robust metadata standards for specific applications that serves to ensure a high level of reliability and interoperability for a spectroscopy dataset. The challenges of designing a metadata standard that meets the unique requirements of specific user communities are examined, including in situ measurement of reflectance underwater, using coral as a case in point. Metadata schema mappings from seven existing metadata standards demonstrate that they consistently fail to meet the needs of field spectroscopy scientists for general and specific applications (μ = 22%, σ = 32% conformance with the core metadata requirements and μ = 19%, σ = 18% for the special case of a benthic (e.g., coral) reflectance metadataset). Issues such as field measurement methods, instrument calibration, and data representativeness for marine field spectroscopy campaigns are investigated within the context of submerged benthic measurements. The implication of semantics and syntax for a robust and flexible metadata standard are also considered. A hybrid standard that serves as a “best of breed” incorporating useful modules and parameters within the standards is proposed. This paper is Part 3 in a series of papers in this journal, examining the issues central to a metadata standard for field spectroscopy datasets. The results presented in this paper are an important step towards field spectroscopy metadata standards that address the specific needs of field spectroscopy data stakeholders while facilitating dataset documentation, quality assurance, discoverability and data exchange within large-scale information sharing platforms.

A Data Model to Support Context-aware Mobile Cloud Collaboration Scenarios

In mobile cloud computing systems, collaborators share the software and hardware infrastructure. Achieving a satisfactory throughput partly depends on providing a well-designed data model. It helps to achieve fewer database objects and improve data access, mobile cloud integration and service customization. This study uses a XSD (XML Schema Definition) approach to provide a flexible Meta data. Exploiting such pliable model, mobile clouds will be able to achieve important objectives such as effective cloud integration and customization.

Management of virtual machine images in heterogeneous clouds

This paper presents the image server of the VISOR cloud agnostic virtual machine images management service. An evaluation approach is also described and the results are discussed. VISOR is not intended to fit in a specific cloud framework but rather to overreach sharing and interoperability limitations among different frameworks. Such feature is achieved by relying on a flexible image metadata schema and in a storage abstraction layer, where the latter seamlessly abstracts the heterogeneity of distinct cloud storage systems into which images can be saved. VISOR is an open source highly distributed system composed of several independent web services. In its development we have focused in modularity, extensibility and performance. Conducted evaluation tests have shown encouraging results regarding performance and scalability.

MyExperimentalScience, extending the ‘workflow’

SUMMARYScience, especially experimental science, has always depended on the careful capture of plans, actions, raw and processed data and conclusions. With scientific research now so inextricably dependent on computers, the use of an electronic laboratory notebook (ELN) is almost essential. The meticulous notebooks of Michael Faraday and other scientists of his era remain as role models for the recording that is necessary, but they cannot provide the essential support for discussion, sharing, collaboration and formal verification. A blog (a contraction of Web log) can form the basis for implementing an electronic notebook but does not suffice to meet all the needs of an ELN. This paper describes the LabTrove ELN, which is blog based but provides numerous additional features, such as version control, security policies and a flexible metadata scheme, and facilities for interchanging objects with other systems. The MyExperimentalScience project links LabTrove with myExperiment, a repository for workflows in a collaborative environment, thereby making LabTrove templates available for discovery and reuse. Collaboration, sharing and reuse are essential for scientific progress, which depends on individual scientists building on the results already produced by others. Open‐source ELNs such as LabTrove are ideal vehicles to support the growth of Open Notebook Science. Copyright © 2012 John Wiley & Sons, Ltd.