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5 results for “Metadata aggregation”

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zenodo44/100

Raw and aggregated data for the study introduced in the paper "The way we cite: common metadata used across disciplines for defining bibliographic references"

<p>These data have been gathered in the context of a study aiming to investigate citation practices for referencing different types of entities and, in particular, for understanding the most used metadata in bibliographic references. The data are stored in two documents in XLSX format:</p> <ul> <li>file &quot;links-intext-pointers-and-cited-entity-types.xlsx&quot; - it contains information about whether the in-text reference pointers of the various PDF articles of the corpus have specified hypertextual links from the in-text reference pointers to the denoted bibliographic reference, plus information about the types of all the entities cited by each article in the corpus;</li> <li>file &quot;metadata-bibliographic-references.xlsm&quot; - it contains information about the metadata used to identify the various descriptive elements of all the bibliographic references defined in the article of the corpus.</li> </ul> <p>The methodology used to gather all these data is described in:</p> <blockquote> <p>Santos, E. A. d., Peroni, S., Mucheroni, M. L.: Workflow for retrieving all the data of the analysis introduced in the article &quot;Citing and referencing habits in Medicine and Social Sciences journals in 2019&quot;. (2020), <a href="https://doi.org/10.17504/protocols.io.bbifikbn">https://doi.org/10.17504/protocols.io.bbifikbn</a></p> </blockquote>

opencc-by-4.0May 2022View details →
zenodo44/100

Raw and aggregated data for the study introduced in the article "An analysis of citing and referencing habits across all scholarly disciplines: approaches and trends in bibliographic metadata errors"

<p>This dataset contains all the raw data and aggregated data subject of the study introduced in the article &quot;An analysis of citing and referencing habits across all scholarly disciplines: approaches and trends in bibliographic metadata errors&quot;. The study is based on the bibliographic and citation data contained in 729 articles published in 147 journals in 27 subject areas. The articles contained a total amount of 34,140 bibliographic references and 55,100 mentions and quotations overall.</p> <p>The dataset is composed of a series of files:</p> <ul> <li>the files &quot;subject_area_&lt;discipline-name&gt;.csv&quot; contain the raw data of the articles published in the journals of all the disciplines considered in the study;</li> <li>the file &quot;article_data_summary.csv&quot; contains the aggregated data created considering the raw data in the previous files, which have been used to creating all the tables and figures in the article;</li> <li>the file &quot;starred_metadata_set.csv&quot; contains information about the most used subset of bibliographic metadata;</li> <li>the file &quot;journals_selection.csv&quot; contains information about all the journals selected for the study.</li> </ul>

opencc-zeroAug 2021View details →
zenodo40/100

ARIADNEplus questionnaire responses for metadata aggregation

<p>Anonymized responses to the ARIADNEplus questionnaire to gather information for the aggregation of metadata about archaelogical resources to be included in the ARIADNEplus Knowledge Base and portal (https://portal.ariadne-infrastructure.eu/).</p> <p>The csv includes only the plain responses as provided by 31 archaelogical content providers until 18 October 2021.&nbsp;</p> <p>The excel file includes also two additional sheets where the responses about the formats and the aggregation update schedule have been normalised.</p> <p>The responses are discussed in deliverable <a href="../doi/10.5281/zenodo.7506765">D12.4 "Final report on data integration"</a>.</p>

opencc-by-4.0Dec 2021View details →
zenodo36/100

Searchable Index of Metadata Aggregators

<p>Searchable Index of Metadata Aggregators is a database that stores general information of metadata aggregators. This database is accompanied&nbsp;with the &ldquo;A WDS guide to Metadata Aggregators for Repository Managers&rdquo;. The Searchable Index of Metadata Aggregators is an up-to-date catalogue of Dataset Metadata Aggregators (DMAs), implemented as an access database. It was designed to fill in a gap&nbsp;found by the Harvestable Metadata Services Working Group (HMetS-WG) members of the World Data System&rsquo;s International Technology Office (WDS-ITO).&nbsp;These include&nbsp;up-to-date resources giving an overview of current infrastructures used to syndicate dataset metadata. The database contains information on DMA&#39;s supported metadata standards and software interfaces, as well as documentation on how to be aggregated by each.</p> <p>The WDS Guide to Metadata Aggregators is a guidance document for the associated Searchable Index of Metadata Aggregators. We have defined DMAs&nbsp;as federated service infrastructures&nbsp;that foster the findability and accessibility of data products by enabling access to multiple, distributed metadata records via a single search interface. This guide gives a description of this catalogue and general guidance on how to use it. In the sections that follow, we give a short background to the Harvestable Metadata Services-Working Group project. Then, we outline the project&#39;s research methodology and the properties of the searchable index. Finally, we discuss this project&#39;s limitations, as well as its future development.&nbsp;Providing metadata to aggregators can significantly improve the findability of research data products.</p> <p>Together, this guidance document and dataset package are designed to provide research data repository managers with options for participation in federated research data systems, and support institutional repositories&#39; harvestable metadata service implementation strategies. In addition, as developers in the global research data management community seek to create pathways and workflows across data, software and compute resources, we anticipate that they&#39;re likely to prioritize connecting sites, organizations and services that have already done a lot of work harmonizing content from disparate providers. In this context, this resource will be helpful for creating roadmaps and implementation plans for integration across science clouds.</p>

opencc-by-4.0Mar 2021View details →
zenodo20/100

Metadata - Perylene-Based Coordination Polymers: Synthesis, Fluorescent J-Aggregates, and Electrochemical Properties

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2023View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

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abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record