Making Common Fund data more Findable: Catalyzing a Data Ecosystem

The Common Fund Data Ecosystem has created a flexible system of data federation that enables users to discover datasets from across the Common Fund without requiring the data owners to move, reformat, or rehost those data. The CFDEs federation system is centered on a metadata catalog that ingests metadata from individual Common Fund Program Data Coordination Centers into a uniform metadata model that can then be indexed and searched from a centralized portal. This uniform Crosscut Metadata Model (C2M2), supports the wide variety of data set types and metadata terms used by the individual and is designed to enable easy expansion to accommodate new datatypes.

Efficient IoT Data Management for Geological Disasters Based on Big Data-Turbocharged Data Lake Architecture

Multi-source Internet of Things (IoT) data, archived in institutions’ repositories, are becoming more and more widely open-sourced to make them publicly accessed by scientists, developers, and decision makers via web services to promote researches on geohazards prevention. In this paper, we design and implement a big data-turbocharged system for effective IoT data management following the data lake architecture. We first propose a multi-threading parallel data ingestion method to ingest IoT data from institutions’ data repositories in parallel. Next, we design storage strategies for both ingested IoT data and processed IoT data to store them in a scalable, reliable storage environment. We also build a distributed cache layer to enable fast access to IoT data. Then, we provide users with a unified, SQL-based interactive environment to enable IoT data exploration by leveraging the processing ability of Apache Spark. In addition, we design a standard-based metadata model to describe ingested IoT data and thus support IoT dataset discovery. Finally, we implement a prototype system and conduct experiments on real IoT data repositories to evaluate the efficiency of the proposed system.

Analysis of Data Model for News Media

The article deals with communicative aspect of using metadata in news media. The relevance of the study is due to the objective need for theoretical justification and the specification of new communication models that have arisen with new channels of communication emergence, media digitalization and convergence. Some modern scientific works raise issue of “the communication of metadata model” in connection with the development of metadata journalism. In particular, the purpose of this article is to analyze the components of the metadata model in news media by the standard of the International Press Telecommunications Council. The rNews standard defines the terminology and a data model for embedding metadata in web documents. It was found that the rNews data model is nonlinear, because the communication in new media is positioned as a two-way process of interaction of actors. The model captures the feedback elements: one of its components is the User Comments Class with the relevant attributes, which, on the one hand, helps to make communication more effective, as the active role of the audience is provided, supported and stimulated, and on the other – makes it possible to create the original metatext. In the communicative aspect, the model is based on a two-way asymmetric model that fixes the feedback, but retains the leading role of the communicator. Asymmetry is reflected in the quantitative (disproportion between the number of “professional” and “naïve” communicators), communicative (disproportion of the “voices” of communicators and recipients, interfering with the building a dialogue) and intentional (unequal intentions of communicators and recipients) forms. The model reflects the general trends in the development of modern mass communication: the target setting for the formation not knowledge, but opinion, the removal of barriers to the involvement of audience in communication, the shift of information from the objective, factual, not related to the situation and participants of communication to a pragmatic, subjective one, synergetic effect of interactive polycode content. Issues of modeling communication processes in new digital media, the transformation of the roles of communicators and recipients, the formation and dissemination of polycode content, its impact on the audience are promising areas of further research and can be explored in various aspects.

Smart Parking Systems: A Data-Oriented Taxonomy and a Metadata Model

Smart parking systems (SPS) represent an evolving and heterogeneous field of approaches and applications in parking management. One commonality is that all present systems deal with digital data related to the parking domain, such as data about parking infrastructure, parking demand, transactions, and similar. Data offerings of SPS seem to provide essential benefits for actors in parking space management, as long as they can be discovered and assessed efficiently. This paper presents mechanisms for the discovery and assessment of SPS data offerings. First, a taxonomy is developed via an inductive approach, based on a review of existing approaches to categorizing such data offerings. The taxonomy represents a hierarchical classification system, looking at functional, technical, and content perspectives of SPS data. This taxonomy is further integrated and formalized into a metadata model, allowing structured and harmonized descriptions about data offerings of individual SPS. The metadata model is built on established metadata frameworks, namely the Resource Description Framework (RDF). For reasons of reusability and interoperability, it also adopts existing metadata vocabularies from the domain of internet data catalogs. This work intends to make the data offerings of SPS assessable and comparable for potential SPS users, namely actors in parking space management. It also provides a foundation for integrating the various forms and technologies of current SPS deployments. Such integration is missing so far, according to some other authors, and is addressed in this work by an interoperable metadata approach.

Micro-Meta App: an interactive software tool to facilitate the collection of microscopy metadata based on community-driven specifications

For the information content of microscopy images to be appropriately interpreted, reproduced, and meet FAIR (Findable Accessible Interoperable and Reusable) principles, they should be accompanied by detailed descriptions of microscope hardware, image acquisition settings, image pixel, and dimensional structure, and instrument performance. Nonetheless, the thorough documentation of imaging experiments is significantly impaired by the lack of community-sanctioned easy-to-use software tools to facilitate the extraction and collection of relevant microscopy metadata. Here we present Micro-Meta App, an intuitive open-source software designed to tackle these issues that was developed in the context of nascent global bioimaging community organizations, including BioImaging North America (BINA) and QUAlity Assessment and REProducibility in Light Microscopy (QUAREP-LiMi), whose goal is to improve reproducibility, data quality, and sharing value for imaging experiments. The App provides a user-friendly interface for building comprehensive descriptions of the conditions utilized to produce individual microscopy datasets as specified by the recently proposed 4DN-BINA-OME tiered-system of Microscopy Metadata model. To achieve this goal the App provides a visual guide for a microscope-user to: 1) interactively build diagrammatic representations of hardware configurations of given microscopes that can be easily reused and shared with colleagues needing to document similar instruments. 2) Automatically extracts relevant metadata from image files and facilitates the collection of missing image acquisition settings and calibration metrics associated with a given experiment. 3) Output all collected Microscopy Metadata to interoperable files that can be used for documenting imaging experiments and shared with the community. In addition to significantly lowering the burden of quality assurance, the visual nature of the Micro-Meta App makes it particularly suited for training users that have limited knowledge of the intricacies of light microscopy experiments. To ensure wide adoption by microscope-users with different needs Micro-Meta App closely interoperates with MethodsJ2 and OMERO.mde, two complementary tools described in parallel manuscripts.

Facilitating Study and Item Level Browsing for Clinical and Epidemiological COVID-19 Studies

COVID-19 poses a major challenge to individuals and societies around the world. Yet, it is difficult to obtain a good overview of studies across different medical fields of research such as clinical trials, epidemiology, and public health. Here, we describe a consensus metadata model to facilitate structured searches of COVID-19 studies and resources along with its implementation in three linked complementary web-based platforms. A relational database serves as central study metadata hub that secures compatibilities with common trials registries (e.g. ICTRP and standards like HL7 FHIR, CDISC ODM, and DataCite). The Central Search Hub was developed as a single-page application, the other two components with additional frontends are based on the SEEK platform and MICA, respectively. These platforms have different features concerning cohort browsing, item browsing, and access to documents and other study resources to meet divergent user needs. By this we want to promote transparent and harmonized COVID-19 research.

EU-Citizen.Science: A Platform for Mainstreaming Citizen Science and Open Science in Europe

Citizen Science (CS) is a prominent field of application for Open Science (OS), and the two have strong synergies, such as: advocating for the data and metadata generated through science to be made publicly available [ 1 ]; supporting more equitable collaboration between different types of scientists and citizens; and facilitating knowledge transfer to a wider range of audiences [ 2 ]. While primarily targeted at CS, the EU-Citizen. Science platform can also support OS. One of its key functions is to act as a knowledge hub to aggregate, disseminate and promote experience and know-how; for example, by profiling CS projects and collecting tools, resources and training materials relevant to both fields. To do this, the platform has developed an information architecture that incorporates the public participation in scientific research (PPSR)—Common Conceptual Model ① . This model consists of the Project Metadata Model, the Dataset Metadata Model and the Observation Data Model, which were specifically developed for CS initiatives. By implementing these, the platform will strengthen the interoperating arrangements that exist between other, similar platforms (e.g., BioCollect and SciStarter) to ensure that CS and OS continue to grow globally in terms of participants, impact and fields of application.

Research Data Infrastructures and Engineering Metadata

This chapter introduces metadata models as a semantic technology for knowledge representation to describe selected aspects of a research asset. The process of building a hierarchical metadata model is reenacted in this chapter and highlighted by the example of EngMeta. Moreover, an overview on data infrastructures is given, the general architecture and functions are disscussed, and multiple examples of data infrastructures in materials modelling are given.