Metadata Representation Research Articles

TSDSystem: a framework to collect, archive and share time series data at volcanological observatories

This paper presents a framework designed to collect, archive, and share time series data coming from sensor networks at Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (Italy), which we have developed and called Time Series Database management System (TSDSystem). The framework proposes a flexible database model for the standardization of sensor networks data and implements an optimized technology for storage and retrieval of acquired time series data. It is designed for the implementation of multiparametric databases and then suitable for development in volcanological observatories worldwide. The proposed framework provides a web service to perform writing and reading data via a standard web communication protocol, which easily enables interaction with other instruments or automatic systems. All results provided by the TSDSystem web service are represented using common data formats in the context of online services. In particular, the station networks metadata representation follows a schema inspired by the International Federation of Digital Seismograph Networks, widely known in seismology. A web GUI (graphical user interface) is provided to test and document the web service. Additionally, basic built-in web applications are supplied with the web GUI to perform joint and synchronized time series data visualization as well as representation of stations on a geographical map. The web GUI also offers administration tools for data access policy management, creation of monitoring dashboards and data publication through web pages. The framework implements an authorization system that can be used to restrict both writing or reading operations. The TSDSystem can also be a useful tool for engineering surveillance systems. The implementing code of the framework is available with an open source license on a public repository together with a user manual.

Cover Feature: Hierarchical Representation of Measurement Data, Metrological Uncertainty and Metadata for Calibrated Battery Tests (Batteries & Supercaps 3/2024)

Cover Feature: Hierarchical Representation of Measurement Data, Metrological Uncertainty and Metadata for Calibrated Battery Tests (Batteries & Supercaps 3/2024)

Promoting Learning Health System Cycles by Optimizing EHR Data Clinical Concept Encoding Processes.

Electronic health records (EHRs) and other real-world data (RWD) are critical to accelerating and scaling care improvement and transformation. To efficiently leverage it for secondary uses, EHR/RWD should be optimally managed and mapped to industry standard concepts (ISCs). Inherent challenges in concept encoding usually result in inefficient and costly workflows and resultant metadata representation structures outside the EHR. Using three related projects to map data to ISCs, we describe the development of standard, repeatable processes for precisely and unambiguously representing EHR data using appropriate ISCs within the EHR platform lifecycle and mappings specific to SNOMED-CT for Demographics, Specialty and Services. Mappings in these 3 areas resulted in ISC mappings of 779 data elements requiring 90 new concept requests to SNOMED-CT and 738 new ISCs mapped into the workflow within an accessible, enterprise-wide EHR resource with supporting processes.

Hierarchical Representation of Measurement Data, Metrological Uncertainty and Metadata for Calibrated Battery Tests

AbstractWe present an interoperable hierarchical data representation for battery tests, leading to improved scalability of data transmission and enhanced data accessibility and comprehensibility for both human interpretation and machine processing. The hierarchical data format includes the raw trace electrical measurement data, the metrological calibration and uncertainty data, the metadata such as experimental settings, instruments and software versions, as well as post‐processed data such as electrochemical model fit parameters. This data representation allows repetition of the battery test under the exact same conditions such that identical results are achieved within defined error bounds. This is in line with the general F. A. I. R. data approach and provides repeatability and traceability in the battery value chain. As an application of the hierarchical data representation, we show the classification of cells as pass/fail being performed with quantitative confidence levels. We demonstrate the complete workflow of establishing the hierarchical data structure for electrochemical impedance spectroscopy (EIS), starting from metrological traceability of the calibration and uncertainty analysis towards the storage of the structured data as a single integrated file that preserves the hierarchical data format. The structured data file is provided in JSON format in the Zenodo repository, as well as the program scripts to generate and read the JSON EIS files.

Entity Embeddings in Remote Sensing: Application to Deformation Monitoring for Infrastructure

There is a critical need for a global monitoring capability for Tailings Storage Facilities (TSFs), to help protect the surrounding communities and the environment. Satellite Synthetic Aperture Radar Interferometry (InSAR) shows much promise towards this ambition. However, extracting meaningful information and interpreting the deformation patterns from InSAR data can be a challenging task. One approach to address this challenge is through the use of data science techniques. In this study, the representation of InSAR metadata as Entity Embeddings within a Deep Learning framework (EE-DL) is investigated for modelling the spatio-temporal deformation response. Entity embeddings are commonly used in natural-language-processing tasks. They represent discrete objects, such as words, as continuous, low-dimensional vectors that can be manipulated mathematically. We demonstrate that EE-DL can be used to predict anomalous patterns in the InSAR time series. To evaluate the performance of the EE-DL approach in SAR interferometry, we conducted experiments over a mining test site (Cadia, Australia), which has been subject to a TSF failure. This study demonstrated that EE-DL can detect and predict the fine spatial movement patterns that eventually resulted in the failure. We also compared the results with deformation predictions from common baseline models, the Random Forest model and Gaussian Process Regression (GPR). Both EE-DL and GPR greatly outperform Random Forest. While GPR is also able to predict displacement patterns with millimetric accuracy, it detects a significantly lower number of anomalies compared to EE-DL. Overall, our study showed that EE-DL is a promising approach for building early-warning systems for critical infrastructures that use InSAR to predict ground deformations.

FAIR Assessment Practices

The poster presents FAIR assessment experiences in the context of the two NFDI consortia KonsortSWD and BERD@NFDI, employing the established Research Data Alliance's FAIR Data Maturity Model (RDA-FDMM) and the F-UJI Tool, an automated solution. RDA-FDMM, a manual technique, is more comprehensive, while the automated F-UJI tool effectively detects areas of improvement in metadata presentation that automated means can address. Our experiences highlight the need to examine both machine-readable as well as non-machine-readable elements and acknowledge automated tools' limitations, while valuing their insights. As the research ecosystem advances, metadata representation should be made increasingly machine-readable. We recommend a "FAIR by design" approach from the beginning to ensure alignment with FAIR principles in project outcomes. Continuous assessments during a project’s lifetime promote ongoing research data infrastructure improvements within the NFDI consortia context, contributing to NFDI infrastructure innovation and optimization.

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simulating the whole rodent brain in the Swiss EPFL Blue Brain Project (BBP) required a solution to managing large-scale highly heterogeneous data, and tracking their provenance to ensure quality, reproducibility and attribution throughout these iterative cycles. Here, we describe Blue Brain Nexus (BBN), an ecosystem of open source, domain agnostic, scalable, extensible data and knowledge graph management systems built by BBP to address these challenges. BBN builds on open standards and interoperable semantic web technologies to enable the creation and management of secure RDF-based knowledge graphs validated by W3C SHACL. BBN supports a spectrum of (meta)data modeling and representation formats including JSON and JSON-LD as well as more formally specified SHACL-based schemas enabling domain model-driven runtime API. With its streaming event-based architecture, BBN supports asynchronous building and maintenance of multiple extensible indices to ensure high performance search capabilities and enable analytics. We present four use cases and applications of BBN to large-scale data integration and dissemination challenges in computational modeling, neuroscience, psychiatry and open linked data.

A strategy for archives metadata representation on CIDOC-CRM and knowledge discovery

This paper presents a strategy for the semantic migration of Portuguese National Archives records into CIDOC-CRM standard, an ontology developed for museums, within the context of the EPISA project. The approach to automatically populate the CIDOC-CRM is based on Mapping Description Rules to semantically translate the archives descriptive information into CIDOC-CRM representation. The compliance of the CIDOC-CRM model recommendations guarantees that the populated CIDOC-CRM ontology of archives descriptive information verifies interoperability, and could be linked and integrated with other populated CIDOC-CRM ontologies. In the information modelling, requirements on the mapping representation, due to the intent of interpreting natural language text to automatically extract information of metadata text fields and to interpret natural language queries, are taken into account. To automatically interpret the Mapping Description Rules, OWL API was used to obtain the set of assertions that represents the information in the target ontology and two datasets are available with some migration examples. The exploration of the knowledge representation is done through some Description Logic queries to highlight the advantages of having this new representation of the National Archives. The evaluation of the resulting representation can be done automatically proving its correctness for the metadata that has a direct representation in CIDOC-CRM.

Metadata Representations for Queryable Repositories of Machine Learning Models

Metadata Representations for Queryable Repositories of Machine Learning Models

AUTOMATION OF A NETWORK OF PROBLEMS USING PROGRAMMING TOOLS

One of the directions of development of metadata of electronic libraries is their selective visualization with the provision of object search in the visual network representation of metadata. One of such systems is also developed by the author of EaAIS “PoiskUM”. In the “PoiskUM” system, an attempt has been made to programmatically implement an electronic library designed for personal use and providing object search functions. In contrast to the classical dictionary search, the object search system provides the reader with the opportunity to fully or partially search through the elements of the library collection and “identify” the desired objects among them on the basis of search features located in cognitive memory. In this system, the user can see a complex network consisting of a network of scientific and technical problems on the computer screen, a network of innovative cycles of technical products related to the problems shown, and a network of library documents. This network is visualized by a representative of a special class of applied software systems – a graph editor. The graph editor builds network elements in its memory in the form of objects and shows them in its windows in the form of a table displaying the attributes of objects. Maintaining and developing the functions of replenishing the network of problems require significant manual labor from the owner of the electronic library. This article discusses proposals for automating the replenishment of structural elements of the network of problems in relation to the metadata of an electronic library that supports object search.

Enhancing RDM in Galaxy by integrating RO-Crate

Enhancing RDM in Galaxy by integrating RO-Crate

Look at metatada processing beyond Libraries

Since many years libraries, archives and museums, the institutions entrusted with the dissemination and conservation of cultural heritage, contributed to metada standards definition, meta-dating methodologies and metadata representation in different syntaxes, by partecipating to national projects and international initiatives.Management systems and catalogs used in these contexts borrow from information and telecommunication technology tools, metodoligies and techniques to generate, organize, share and use various types of metadata. But the Information and Communication Technology (ICT) area is not only a supplier of technological tools and solutions as it also constitutes a rich basin in which metadata plays a fundamental role in designing architectures, modeling information systems and implementing services.Through an overview that includes national and European initiatives, especially in the digital transformation process of the public sector, this paper aims to offer a look to metadata beyond the traditional boundary of libraries and other cultural institutions and to underline some relevant aspects such as standardization, sharing, reuse and metadata quality assessment.This framework highlights the need to carry on with the path of cooperation between different functional domains and organizational contexts in order to consolidate and extend the (re)use of metadata schemes, ontologies and controlled vocabularies both in the redesign of digitized processes and in the implementation of services supporting them. By undertaking since design early stages a multidisciplinary approach based on metadata standards can ensure greater flexibility and higher interoperability. This vision requires the enhancement of intersectorial skills that meld metadata methodologies and syntaxes representation basic knowledge with the ability to model functional domains using metadata schemes and ontologies.

An Algorithmic Approach to Reducing Taxonomic Detail from Actual Datasets to their Metadata Representation to Increase Findabilty

An Algorithmic Approach to Reducing Taxonomic Detail from Actual Datasets to their Metadata Representation to Increase Findabilty

Tabular strategies for metadata in ecology, evolution, and the environmental sciences.

Data support knowledge development and theory advances in ecology and evolution. We are increasingly reusing data within our teams and projects and through the global, openly archived datasets of others. Metadata can be challenging to write and interpret, but it is always crucial for reuse. The value metadata cannot be overstated—even as a relatively independent research object because it describes the work that has been done in a structured format. We advance a new perspective and classify methods for metadata curation and development with tables. Tables with templates can be effectively used to capture all components of an experiment or project in a single, easy‐to‐read file familiar to most scientists. If coupled with the R programming language, metadata from tables can then be rapidly and reproducibly converted to publication formats including extensible markup language files suitable for data repositories. Tables can also be used to summarize existing metadata and store metadata across many datasets. A case study is provided and the added benefits of tables for metadata, a priori, are developed to ensure a more streamlined publishing process for many data repositories used in ecology, evolution, and the environmental sciences. In ecology and evolution, researchers are often highly tabular thinkers from experimental data collection in the lab and/or field, and representations of metadata as a table will provide novel research and reuse insights.

Aligning restricted access data with FAIR: a systematic review.

Understanding the complexity of restricted research data is vitally important in the current new era of Open Science. While the FAIR Guiding Principles have been introduced to help researchers to make data Findable, Accessible, Interoperable and Reusable, it is still unclear how the notions of FAIR and Openness can be applied in the context of restricted data. Many methods have been proposed in support of the implementation of the principles, but there is yet no consensus among the scientific community as to the suitable mechanisms of making restricted data FAIR. We present here a systematic literature review to identify the methods applied by scientists when researching restricted data in a FAIR-compliant manner in the context of the FAIR principles. Through the employment of a descriptive and iterative study design, we aim to answer the following three questions: (1) What methods have been proposed to apply the FAIR principles to restricted data?, (2) How can the relevant aspects of the methods proposed be categorized?, (3) What is the maturity of the methods proposed in applying the FAIR principles to restricted data?. After analysis of the 40 included publications, we noticed that the methods found, reflect the stages of the Data Life Cycle, and can be divided into the following Classes: Data Collection, Metadata Representation, Data Processing, Anonymization, Data Publication, Data Usage and Post Data Usage. We observed that a large number of publications used ‘Access Control‘ and ‘Usage and License Terms’ methods, while others such as ‘Embargo on Data Release’ and the use of ‘Synthetic Data’ were used in fewer instances. In conclusion, we are presenting the first extensive literature review on the methods applied to confidential data in the context of FAIR, providing a comprehensive conceptual framework for future research on restricted access data.

An Ontology and Data Converter from RDF to the i2b2 Data Model.

In a national effort aiming at cross-hospitals data interoperability, the Swiss Personalized Health Network elected RDF as preferred data and meta-data representation format. Yet, most clinical research software solutions are not designed to interact with RDF databases. We present a modular Python toolkit allowing easy conversion from RDF graphs to i2b2, adaptable to other common data models (CDM) with reasonable efforts. The tool was designed with feedback from clinicians in both oncology and laboratory research.

Video Source Characterization Using Encoding and Encapsulation Characteristics

We introduce the use of video coding settings for source identification and propose a new approach that incorporates encoding and encapsulation aspects of a video. To this end, a joint representation of the overall file metadata is developed and used in conjunction with a two-level hierarchical classification method. At the first level, our method groups videos into metaclasses considering several abstractions that represent high-level structural properties of file metadata. This is followed by a more nuanced classification of classes that comprise each metaclass. The method is evaluated on more than 20K videos obtained by combining four public video datasets. Tests show that a balanced accuracy of 91% is achieved in correctly identifying the class of a video among 119 video classes. This corresponds to an improvement of 6.5% over the conventional approach based on video file encapsulation characteristics. Analysis performed on a large, unlabeled video set also confirmed the aptness of our approach. To further demonstrate the versatility of encoding parameters, we consider attribution of partial video files where file metadata is not available. Our results show that, even in this limited setting that is intrinsic to forensic file recovery, an identification accuracy of 57% can be achieved through the use of a subset of encoding parameters estimated from coded video data.

Precision omics data integration and analysis with interoperable ontologies and their application for COVID-19 research.

Precision medicine focuses on individual-level disease treatment and prevention. Precision omics is a new strategy that applies omics for precision medicine research, which requires standardized representation and integration of individual genetics and phenotypes, experimental conditions, and data analysis settings. Ontology has emerged as an important artificial intelligence component to become critical for standard data and metadata representation, standardization and integration. To support precision omics, interoperable ontologies are required in order to standardize and incorporate heterogeneous data and knowledge in a human- and computer-interpretable manner. With the interoperable omics data and knowledge, omics tools such as OmicsViz can also be evolved to process, integrate, visualize and analyze various omics data, leading to the identification of new knowledge and hypotheses of molecular mechanisms underlying disease outcomes. The precision COVID-19 omics study is provided as the primary use case to illustrate the rationale and implementation of the precision omics strategy.

ISO 21526 Conform Metadata Editor for FAIR Unicode SKOS Thesauri.

Metadata repositories are an indispensable component of data integration infrastructures and support semantic interoperability between knowledge organization systems. Standards for metadata representation like the ISO/IEC 11179 as well as the Resource Description Framework (RDF) and the Simple Knowledge Organization System (SKOS) by the World Wide Web Consortium were published to ensure metadata interoperability, maintainability and sustainability. The FAIR guidelines were composed to explicate those aspects in four principles divided in fifteen sub-principles. The ISO/IEC 21526 standard extends the 11179 standard for the domain of health care and mandates that SKOS be used for certain scenarios. In medical informatics, the composition of health care SKOS classification schemes is often managed by documentalists and data scientists. They use editors, which support them in producing comprehensive and valid metadata. Current metadata editors either do not properly support the SKOS resource annotations, require server applications or make use of additional databases for metadata storage. These characteristics are contrary to the application independency and versatility of raw Unicode SKOS files, e.g. the custom text arrangement, extensibility or copy & paste editing. We provide an application that adds navigation, auto completion and validity check capabilities on top of a regular Unicode text editor.

Comparison and integration of techniques for the study and valorisation of the Corsini Throne in Corsini Gallery in Roma

<p>In recent years, digital technologies for enhancement and use of cultural heritage items has grown considerably. Multimedia, virtual and augmented reality and 3D reconstructions make it possible to bring the general public closer to an understanding of something that no longer exists or that is from a distant time. But digital tools can serve more than educational purposes.</p><p>To date, digitisation has become above all an essential tool in most cultural heritage projects involving conservation, restoration, documentation and research.</p><p>This article shows a process that integrates photogrammetry and structured light scans to obtain a 3D reconstruction of the Corsini Throne, preserved at the Corsini Gallery in Rome for its exhibition using a web application combined with semantic representation of metadata following FAIR principles. The process began during the development of the WeACT3 Project (Acting Together – Technology for Art, Culture, Tourism and Territory) jointly signed by the CIVITA Association, and the National Barberini and Corsini Galleries, collaborating in a partnership of several national and international enterprises. Within EcoDigit project, financed by Lazio Region, an automated web tool prototype was developed by ENEA. It is able to display 3D models with correlated scientific information to assist research activities and knowledge sharing.</p>