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The publication of research activities and results as well as the various participants pose major challenges for data exchange, exploration and visualization. The German Centre for Higher Education Research and Science Studies (DZHW) has developed an open data portal for the National Academics Panel Study (Nacaps), funded by the Federal Ministry of Education and Research (BMBF). With interactive graphics on topics such as doctoral conditions, career intentions, mobility and financing, the portal offers an overview of the life and work reality of doctoral students in Germany. Survey data is prepared in the data portal so that it can be used at a low threshold. Since the data is made available free of charge in open and reusable formats without restrictions, it can be used by researchers and the public alike. At the same time, the portal offers cooperating partner universities university-specific reporting on the data of doctoral students at their institution in a protected space. The possible further development and effective use of the Nacaps data portal for the management of open survey data will be discussed. In particular, the quality of open survey data as well as the potential and special features of the Nacaps data portal when visualizing survey data are discussed. [ABSTRACT FROM AUTHOR]

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The overall objective of the ARIADNE initiative is to help archaeological research and data management communities in Europe and beyond to more effectively share and use data that are dispersed across many institutions and projects. The initiative developed Research Infrastructure services that enable aggregation, integration, search and visualisation of data records that describe and link to data collections and items available in the providers' repositories and databases. Funded under the Research Infrastructures strand of the European Union's Framework Programme for Research and Innovation, the ARIADNE projects implemented and enhanced the ARIADNE Research Infrastructure and mobilised a growing community of institutions and collaborative projects interested in sharing data through the e-Infrastructure. In the ARIADNEplus project almost 4 million data records were integrated in the ARIADNE Portal. Following a brief introduction to the ARIADNE initiative, this article presents selected achievements of the initiative with the ARIADNEplus project. It addresses the extension and support of the ARIADNE community, the activities promoting FAIR data in archaeology, and the standardisation of datasets based on the CIDOC CRM and the domain vocabularies Getty AAT and PeriodO. It considers the ARIADNE Portal as an effective data access and research tool, and the development of Virtual Research Environments as a new innovative approach. The final remarks highlight the ability of the ARIADNE initiative to provide incentives for institutions and projects to share their data and make it useful through the ARIADNE Portal, which leverages the value of the providers' repositories and databases. Furthermore, ways in which ARIADNE fosters cross-disciplinary fertilisation are noted, for example, between scholars and technological developers of research services.

Mutations in MeCP2 result in a crippling neurological disease, but we lack a lucid picture of MeCP2′s molecular role. Individual transcriptomic studies yield inconsistent differentially expressed genes. To overcome these issues, we demonstrate a methodology to analyze all modern public data. We obtained relevant raw public transcriptomic data from GEO and ENA, then homogeneously processed it (QC, alignment to reference, differential expression analysis). We present a web portal to interactively access the mouse data, and we discovered a commonly perturbed core set of genes that transcends the limitations of any individual study. We then found functionally distinct, consistently up- and downregulated subsets within these genes and some bias to their location. We present this common core of genes as well as focused cores for up, down, cell fraction models, and some tissues. We observed enrichment for this mouse core in other species MeCP2 models and observed overlap with ASD models. By integrating and examining transcriptomic data at scale, we have uncovered the true picture of this dysregulation. The vast scale of these data enables us to analyze signal-to-noise, evaluate a molecular signature in an unbiased manner, and demonstrate a framework for future disease focused informatics work. [ABSTRACT FROM AUTHOR]

Globally, democratic principles revolve around transparency, accountability and greater involvement of the citizens in government programmes and activities for sustainable development. This can only be achieved if the people have access to government information and this is why agitations for freedom of information continue to heighten. Open government data (OGD) play major roles in democratization of information and a propeller of transparency and open governance. This paper adopted descriptive informatics and literature review approach to examine the websites of major government ministries and agencies in Nigeria including Nigeria Data Portal to determine the availability and status of open government data. Findings reveal that while some websites have presence of OGD, over 60% are yet to provide such data in the website. Also the data portal has several government data but they are hardly updated. The paper also identified several challenges of OGD in Nigeria and proposed recommendations to mitigate the challenges. [ABSTRACT FROM AUTHOR]

The French Critical Zone research infrastructure, OZCAR-RI, gathers 20 observatories sampling various compartments of the critical zone, each having developed their own data management and distribution systems. A common information system (Theia/OZCAR IS) was built to make their in situ observation FAIR (findable, accessible, interoperable, reusable). The IS architecture was designed after consultation of the users, data producers and IT teams involved in data management. A common data model based on various metadata standards was defined to create information fluxes between observatories' ISs and the Theia/OZCAR IS. Controlled vocabularies were defined to develop a data discovery web portal offering a faceted search with various criteria, including variables names and categories that were harmonized in a thesaurus published on the web. This paper describes the IS architecture, the pivot data model and open-source solutions used to implement data discovery, and future steps to implement data downloading and interoperability services. [ABSTRACT FROM AUTHOR]

Mutations in MeCP2 result in a crippling neurological disease, but we lack a lucid picture of MeCP2′s molecular role. Individual transcriptomic studies yield inconsistent differentially expressed genes. To overcome these issues, we demonstrate a methodology to analyze all modern public data. We obtained relevant raw public transcriptomic data from GEO and ENA, then homogeneously processed it (QC, alignment to reference, differential expression analysis). We present a web portal to interactively access the mouse data, and we discovered a commonly perturbed core set of genes that transcends the limitations of any individual study. We then found functionally distinct, consistently up- and downregulated subsets within these genes and some bias to their location. We present this common core of genes as well as focused cores for up, down, cell fraction models, and some tissues. We observed enrichment for this mouse core in other species MeCP2 models and observed overlap with ASD models. By integrating and examining transcriptomic data at scale, we have uncovered the true picture of this dysregulation. The vast scale of these data enables us to analyze signal-to-noise, evaluate a molecular signature in an unbiased manner, and demonstrate a framework for future disease focused informatics work.

We present a new service of Arachnologische Gesellschaft -- data publication in Arachnologische Mitteilungen / Arachnology Letters. A first exemplary dataset is published in this volume. Here we inform about the goals, criteria for acceptance of manuscripts and data, the foreseen editorial procedures, formats, the websites of the digital publication and the data repository ARAMOB used to archive, manage and mobilize the data. [ABSTRACT FROM AUTHOR]

The Functional Annotation of ANimal Genomes (FAANG) project is a worldwide coordinated action creating high-quality functional annotation of farmed and companion animal genomes. The generation of a rich genome-to-phenome resource and supporting informatic infrastructure advances the scope of comparative genomics and furthers the understanding of functional elements. The project also provides terrestrial and aquatic animal agriculture community powerful resources for supporting improvements to farmed animal production, disease resistance, and genetic diversity. The FAANG Data Portal (https://data.faang.org) ensures Findable, Accessible, Interoperable and Reusable (FAIR) open access to the wealth of sample, sequencing, and analysis data produced by an ever-growing number of FAANG consortia. It is developed and maintained by the FAANG Data Coordination Centre (DCC) at the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI). FAANG projects produce a standardised set of multi-omic assays with resulting data placed into a range of specialised open data archives. To ensure this data is easily findable and accessible by the community, the portal automatically identifies and collates all submitted FAANG data into a single easily searchable resource. The Data Portal supports direct download from the multiple underlying archives to enable seamless access to all FAANG data from within the portal itself. The portal provides a range of predefined filters, powerful predictive search, and a catalogue of sampling and analysis protocols and automatically identifies publications associated with any dataset. To ensure all FAANG data submissions are high-quality, the portal includes powerful contextual metadata validation and data submissions brokering to the underlying EMBL-EBI archives. The portal will incorporate extensive new technical infrastructure to effectively deliver and standardise FAANG's shift to single-cellomics, cell atlases, pangenomes, and novel phenotypic prediction models. The Data Portal plays a key role for FAANG by supporting high-quality functional annotation of animal genomes, through open FAIR sharing of data, complete with standardised rich metadata. Future Data Portal features developed by the DCC will support new technological developments for continued improvement for FAANG projects.

The Functional Annotation of ANimal Genomes (FAANG) project is a worldwide coordinated action creating high-quality functional annotation of farmed and companion animal genomes. The generation of a rich genome-to-phenome resource and supporting informatic infrastructure advances the scope of comparative genomics and furthers the understanding of functional elements. The project also provides terrestrial and aquatic animal agriculture community powerful resources for supporting improvements to farmed animal production, disease resistance, and genetic diversity. The FAANG Data Portal (https://data.faang.org) ensures Findable, Accessible, Interoperable and Reusable (FAIR) open access to the wealth of sample, sequencing, and analysis data produced by an ever-growing number of FAANG consortia. It is developed and maintained by the FAANG Data Coordination Centre (DCC) at the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI). FAANG projects produce a standardised set of multi-omic assays with resulting data placed into a range of specialised open data archives. To ensure this data is easily findable and accessible by the community, the portal automatically identifies and collates all submitted FAANG data into a single easily searchable resource. The Data Portal supports direct download from the multiple underlying archives to enable seamless access to all FAANG data from within the portal itself. The portal provides a range of predefined filters, powerful predictive search, and a catalogue of sampling and analysis protocols and automatically identifies publications associated with any dataset. To ensure all FAANG data submissions are high-quality, the portal includes powerful contextual metadata validation and data submissions brokering to the underlying EMBL-EBI archives. The portal will incorporate extensive new technical infrastructure to effectively deliver and standardise FAANG's shift to single-cellomics, cell atlases, pangenomes, and novel phenotypic prediction models. The Data Portal plays a key role for FAANG by supporting high-quality functional annotation of animal genomes, through open FAIR sharing of data, complete with standardised rich metadata. Future Data Portal features developed by the DCC will support new technological developments for continued improvement for FAANG projects. [ABSTRACT FROM AUTHOR]

The understanding of the biodiversity and biogeographical distribution of fungi is still limited. The small number of online databases and the large effort required to access existing data have prevented their use in research articles. The Mycology Collections Portal was established in 2012 to help alleviate these issues and currently serves data online for over 4.3 million fungal records. However, the current process for accessing the data through the web interface is manual, therefore slow, and precludes the extensive use of the existing datasets. Here we introduce the software package rMyCoPortal, which allows users rapid, automated access to the data. rMyCoPortal makes data readily available for further computations and analyses in the open source statistical programming environment R. We will demonstrate the core functions of the package, and how rMyCoPortal can be employed to obtain fungal data that can be used to address basic research questions. rMyCoPortal is a free and open-source R package, available via GitHub.

Natural history collections are invaluable tools for various questions regarding biodiversity, environmental, and cultural studies. All object metadata thus need to be findable, reachable and interoperable for the scientific community and beyond. This requires a good structuration of data, appropriate exchange formats, and web sites or portals making all necessary information accessible. Collection managers, curators, and scientist from various institutions and nationalities were surveyed in order to understand the importance of open geoscientific collections for the respective holding institution and their daily work. In addition, particular requirements for the publication of geoscientific collection object metadata were gathered in a two-day workshop with international experts working with paleontological, mineralogical, petrological and meteorite collections. The survey and workshop revealed that common data standards are of crucial importance though insufficiently used by most institutions. The extent and type of information necessary for the publication and discussed during the workshop will be considered for domain specific application schema facilitating the publication and exchange of geoscientific object metadata. There is a high demand for comprehensive data portals covering all geoscientific disciplines. Gathered portal requirements will be taken into account when improving the already running GeoCASe aggregator platform.

The label transcription and imaging of specimens in key African herbaria has been ongoing since the early 2000s. Many collections in Benin, Cameroon, Côte d'Ivoire, Gabon, Guinea Conakry, and Togo are now fully transcribed and partially digitized. More than 200 000 transcribed specimens are available with the following distribution: • Benin: 45 000 • Cameroon: 70 000 • Côte d'Ivoire: 18 000 • Gabon: 70 000 • Guinea Conakry: 5 000 • Togo: 15 000 In April 2021, a BID project was started to deliver a regional data platform of West and Central African herbaria. Biodiversity Information for Development (BID) is a multi-year programme funded by the European Union and led by GBIF with the aim of enhancing capacity for effective mobilization and use of biodiversity data in research and policy in the 'ACP' nations of sub-Saharan Africa, the Caribbean and the Pacific. Our project's funding runs from April 2021 to April 2023. At this stage of the project, we are working on defining the information technology (IT) architecture (Fig. 1) and selecting the tools that we will be using to achieve our goals. In the talk, we will present our conclusions through architecture schemas and tools demonstrations. Each of the 6 countries will have its own PostgreSQL database, storing its data. They will also have access to the RIHA data management platform (Réseau Informatique des Herbiers d'Afrique / Digital Network of African Herbaria). This is a web application, developed in PHP, allowing full management of the data by herbarium administrators (Fig. 2). An Integrated Publishing Toolkit (IPT) will fetch these herbaria data from the databases, create the Darwin Core archives, and connect these data automatically to gbif.org on a periodic basis (Fig. 3). On the databases, we will use a PostgreSQL view to ease conversion from the RIHA data model to the Darwin Core model. On the IPT, we will create one dataset per country, linked to each PostgreSQL view. The SQL query will be configured to only fetch validated data, depending on the herbarium administrator's validation in the RIHA platform. The automatic and periodic data transmission to gbif.org is a feature available in the IPT, and recently improved by the GBIF France team, which contributes to the IPT development. Another part of the automatic data workflow will be to feed a Living Atlases portal for the West and Central African herbaria. This web application will allow public users to search, display and download herbaria data from West and Central Africa (Fig. 4). Internally, this Living Atlases application will reuse open source modules developed by the Atlas of Living Australia (ALA). The application is mainly written in Java, uses JQuery/Bootstrap for the interface and relies on SolR and Spark in the backend. It has been developed to be easily reusable, by only modifying configuration and doing web customization (HTML / CSS), hiding most of the backend technological complexity. The automatic data workflow will transfer datasets generated by the IPT, in Darwin Core Archive format, to the Living Atlases portal backend. A technical task orchestrator, yet to be selected, will implement this feature. Living Atlases subportals, limited to data of one participating country, could be easily set up, leveraging the existing backend resources (Fig. 5). One of the benefits of the Living Atlases portal is that we can easily deploy additional front end applications with limited data, configured by a filter (here, a filter on the data owner country). Only configuration and web customization (HTML / CSS) are required. All the backend modules, especially the ones storing data, are shared by the multiple front-ends, limiting the hardware consumption and data administration. The full automation of the workflow will allow this platform to run at a very low maintenance cost for IT administrators. Moreover, adding a new herbarium member from West and Central Africa will be quite easy thanks to the architecture of the Integrated Publishing Toolkit and Living Atlases tools (Fig. 6). [ABSTRACT FROM AUTHOR]

Current search engines in most geospatial data portals tend to induce users to focus on one single-data characteristic dimension (e.g. popularity and release date). This approach largely fails to take account of users’ multidimensional preferences for geospatial data, and hence may likely result in a less than optimal user experience in discovering the most applicable dataset. This study reports a machine learning framework to address the ranking challenge, the fundamental obstacle in geospatial data discovery, by (1) identifying a number of ranking features of geospatial data to represent users’ multidimensional preferences by considering semantics, user behavior, spatial similarity, and static dataset metadata attributes; (2) applying a machine learning method to automatically learn a ranking function; and (3) proposing a system architecture to combine existing search-oriented open source software, semantic knowledge base, ranking feature extraction, and machine learning algorithm. Results show that the machine learning approach outperforms other methods, in terms of both precision at K and normalized discounted cumulative gain. As an early attempt of utilizing machine learning to improve the search ranking in the geospatial domain, we expect this work to set an example for further research and open the door towards intelligent geospatial data discovery.

As a National Metrology Institute (NMI), the USA National Institute of Standards and Technology (NIST) scientists, engineers and technology experts conduct research across a full spectrum of physical science domains. NIST is a non-regulatory agency within the U.S. Department of Commerce with a mission to promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve our quality of life. NIST research results in the production and distribution of standard reference materials, calibration services, and datasets. These are generated from a wide range of complex laboratory instrumentation, expert analyses, and calibration processes. In response to a government open data policy, and in collaboration with the broader research community, NIST has developed a federated Open Access to Research (OAR) scientific data infrastructure aligned with FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Through the OAR initiatives, NIST’s Material Measurement Laboratory Office of Data and Informatics (ODI) recently released a new scientific data discovery portal and public data repository. These science-oriented applications provide dissemination and public access for data from across the broad spectrum of NIST research disciplines, including chemistry, biology, materials science (such as crystallography, nanomaterials, etc.), physics, disaster resilience, cyberinfrastructure, communications, forensics, and others. NIST’s public data consist of carefully curated Standard Reference Data, legacy high valued data, and new research data publications. The repository is thus evolving both in content and features as the nature of research progresses. Implementation of the OAR infrastructure is key to NIST’s role in sharing high integrity reproducible research for measurement science in a rapidly changing world.

Marine data are needed for many purposes: for acquiring a better scientific understanding of the marine environment, but also, increasingly, as marine knowledge for decision making as well as developing products and services supporting economic growth. Data must be of sufficient quality to meet the specific users' needs. It must also be accessible in a timely manner. And yet, despite being critical, this timely access to known-quality data proves challenging. Europe's marine data have traditionally been collected by a myriad of entities with the result that much of our data are scattered throughout unconnected databases and repositories. Even when data are available, they are often not compatible, making the sharing of the information and data aggregation particularly challenging. In this paper, we present how the European Marine Observation and Data network (EMODnet) has developed over the last decade to tackle these issues. Today, EMODnet is comprised of more than 150 organizations which gather marine data, metadata, and data products and make them more easily accessible for a wider range of users. EMODnet currently consists of seven sub-portals: bathymetry, geology, physics, chemistry, biology, seabed habitats, and human activities. In addition, Sea-basin Checkpoints have been established to assess the observation capacity in the North Sea, Mediterranean, Atlantic, Baltic, Artic, and Black Sea. The Checkpoints identify whether the observation infrastructure in Europe meets the needs of users by undertaking a number of challenges. To complement this, a Data Ingestion Service has been set up to tackle the problem of the wealth of marine data that remain unavailable, by reaching out to data holders, explaining the benefits of sharing their data and offering a support service to assist them in releasing their data and making them available through EMODnet. The EMODnet Central Portal (www.emodnet.eu) provides a single point of access to these services, which are free to access and use. The strategic vision of EMODnet in the next decade is also presented, together with key focal areas toward a more user-oriented service, including EMODnet for business, internationalization for global users, and stakeholder engagement to connect the diverse communities across the marine knowledge value chain.

Open data is an important element in a variety of new industries, such as artificial intelligence and smart cities. While the South Korean government is continuously releasing new data on the public data portal, it is limited in the accomplishment of the goals such as job creation and the new economic leaps expected by the Korean government. From a data point of view, this limitation is due to a lack of data that users require and a lot of low-quality data to use. This paper analyses standard terms used in public data. The findings of this study reveals that standard vocabularies established by the government require updates to reflect the nature of public data, and the relevant laws and guidelines need to be revised. [ABSTRACT FROM AUTHOR]

The understanding of the biodiversity and biogeographical distribution of fungi is still limited. The small number of online databases and the large effort required to access existing data have prevented their use in research articles. The Mycology Collections Portal was established in 2012 to help alleviate these issues and currently serves data online for over 4.3 million fungal records. However, the current process for accessing the data through the web interface is manual, therefore slow, and precludes the extensive use of the existing datasets. Here we introduce the software package rMyCoPortal, which allows users rapid, automated access to the data. rMyCoPortal makes data readily available for further computations and analyses in the open source statistical programming environment R. We will demonstrate the core functions of the package, and how rMyCoPortal can be employed to obtain fungal data that can be used to address basic research questions. rMyCoPortal is a free and open-source R package, available via GitHub. [ABSTRACT FROM AUTHOR]

Natural history collections are invaluable tools for various questions regarding biodiversity, environmental, and cultural studies. All object metadata thus need to be findable, reachable and interoperable for the scientific community and beyond. This requires a good structuration of data, appropriate exchange formats, and web sites or portals making all necessary information accessible. Collection managers, curators, and scientist from various institutions and nationalities were surveyed in order to understand the importance of open geoscientific collections for the respective holding institution and their daily work. In addition, particular requirements for the publication of geoscientific collection object metadata were gathered in a two-day workshop with international experts working with paleontological, mineralogical, petrological and meteorite collections. The survey and workshop revealed that common data standards are of crucial importance though insufficiently used by most institutions. The extent and type of information necessary for the publication and discussed during the workshop will be considered for domain specific application schema facilitating the publication and exchange of geoscientific object metadata. There is a high demand for comprehensive data portals covering all geoscientific disciplines. Gathered portal requirements will be taken into account when improving the already running GeoCASe aggregator platform. [ABSTRACT FROM AUTHOR]

EnviDat is the environmental data portal developed by the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. The strategic initiative EnviDat highlights the importance WSL lays on Research Data Management (RDM) at the institutional level and demonstrates the commitment to accessible research data in order to advance environmental science. EnviDat focuses on registering and publishing environmental data sets and provides unified and efficient access to the WSL’s comprehensive reservoir of environmental monitoring and research data. Research data management is organized in a decentralized manner where the responsibility to curate research data remains with the experts and the original data providers. EnviDat supports data producers and data users in registration, documentation, storage, publication, search and retrieval of a wide range of heterogeneous data sets from the environmental domain. Innovative features include (i) a flexible, three-layer metadata schema, (ii) an additive data discovery model that considers spatial data and (iii) a DataCRediT mechanism designed for specifying data authorship. In addition, the overall user-friendly appearance in EnviDat provides an important opportunity for showcasing WSL research activities and results. The EnviDat portal builds on a conceptual system consisting of a core system, a set of guiding principles and a number of key services. Its development closely follows the conceptual framework, being guided by principles towards the ultimate goal of providing useful services for researchers.

Current search engines in most geospatial data portals tend to induce users to focus on one single-data characteristic dimension (e.g. popularity and release date). This approach largely fails to take account of users’ multidimensional preferences for geospatial data, and hence may likely result in a less than optimal user experience in discovering the most applicable dataset. This study reports a machine learning framework to address the ranking challenge, the fundamental obstacle in geospatial data discovery, by (1) identifying a number of ranking features of geospatial data to represent users’ multidimensional preferences by considering semantics, user behavior, spatial similarity, and static dataset metadata attributes; (2) applying a machine learning method to automatically learn a ranking function; and (3) proposing a system architecture to combine existing search-oriented open source software, semantic knowledge base, ranking feature extraction, and machine learning algorithm. Results show that the machine learning approach outperforms other methods, in terms of both precision at K and normalized discounted cumulative gain. As an early attempt of utilizing machine learning to improve the search ranking in the geospatial domain, we expect this work to set an example for further research and open the door towards intelligent geospatial data discovery. [ABSTRACT FROM AUTHOR]

EnviDat is the environmental data portal developed by the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. The strategic initiative EnviDat highlights the importance WSL lays on Research Data Management (RDM) at the institutional level and demonstrates the commitment to accessible research data in order to advance environmental science. EnviDat focuses on registering and publishing environmental data sets and provides unified and efficient access to the WSL's comprehensive reservoir of environmental monitoring and research data. Research data management is organized in a decentralized manner where the responsibility to curate research data remains with the experts and the original data providers. EnviDat supports data producers and data users in registration, documentation, storage, publication, search and retrieval of a wide range of heterogeneous data sets from the environmental domain. Innovative features include (i) a flexible, three-layer metadata schema, (ii) an additive data discovery model that considers spatial data and (iii) a DataCRediT mechanism designed for specifying data authorship. In addition, the overall user-friendly appearance in EnviDat provides an important opportunity for showcasing WSL research activities and results. The EnviDat portal builds on a conceptual system consisting of a core system, a set of guiding principles and a number of key services. Its development closely follows the conceptual framework, being guided by principles towards the ultimate goal of providing useful services for researchers. [ABSTRACT FROM AUTHOR]

Many fish species use active sound production for communication in numerous behaviors. Additionally, likely all fish can make passive or incidental sounds that may also serve some signal functions. Despite the ecological importance of fish sounds, their evident passive acoustic monitoring applications, and extensive endeavors to document soniferous fish diversity, the fields of bioacoustics and ichthyology have historically lacked an easily accessible, global inventory of known fish sound production. To alleviate this limitation, we developed http://FishSounds.net , a website that compiles and disseminates fish sound production information and recordings. FishSounds Version 1.0 launched in 2021, cataloging documented examinations for active and passive sound production for 1185 fish species from 837 references as well as 239 exemplary audio recordings. FishSounds allows users to search by taxa (e.g., family or common name), geographical distribution (e.g., region or water body), sound type, or reference. We have also made available the code used to create the website, so that it may be used in other data-sharing efforts—acoustic or otherwise. Subsequent versions of the website will update the data and improve the website functionality. FishSounds will advance research into fish behavior, passive acoustic monitoring, and human impacts on underwater soundscapes; serve as a resource for public outreach; and provide the foundation needed to investigate more of the 96% of fish species that lack published examinations of sound production. We further hope the FishSounds design, implementation, and engagement strategies will serve as a model for future data management and sharing efforts. • The FishSounds website, launched in 2021, can be found at http://FishSounds.net. • We present sound information on 1185 fish species and 239 recordings. • Subsequent versions will update the data and improve website functionality. • The website code is available on GitLab for others to adapt and use. • FishSounds will aid research, outreach, management, and data sharing efforts. [ABSTRACT FROM AUTHOR]