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The concept of Essential Biodiversity Variables (EBVs) was conceived to study, report, and manage biodiversity change. The EBV netCDF structure was developed in order to support publication and interoperability of biodiversity data. This standard is based on the Network Common Data Format (netCDF). Additionally, it follows the Climate and Forecast Conventions (CF, version 1.8) and the Attribute Convention for Data Discovery (ACDD, version 1.3). The standard allows several datacubes per netCDF file (see Fig. 1). These cubes have four dimensions: longitude, latitude, time and entity, whereby the last dimension can, for example, encompass different species or groups of species, ecosystem types or other aspects. The usage of hierarchical groups enables the coexistence of multiple EBV cubes (see Fig. 2). The first level (netCDF group) are scenarios, e.g., the modelling for different Shared Socioeconomic Pathways (SSP) scenarios. The second level (netCDF group) are metrics, e.g., the percentage of protected area per pixel and its proportional loss over a certain time span per pixel. All metrics are repeated per scenario, if any are present. The result is a rather complex raster dataset (see example dataset in Fig. 3). This is where the ebvcube R package comes into play. This R package enables scientists to create their own netCDFs in the EBV cube standard. Its functionality covers the creation, opening/reading and visualizing the EBV netCDFs. The ebvcube package is part of the overall EBV infrastructure and works together with the EBV Data Portal. Users can work with the downloaded EBV netCDFs or upload their own EBV netCDFs to the portal. Generally, the package aims to condense the output for the users and assist in the understanding of the file structure to overcome the complexity. The output is reduced to the necessary information, e.g., not displaying coordinate variables or any technical attributes. Moreover, functionality for a quick data exploration is implemented.

Natural history specimens constitute physical evidence for past observations of nature. They hold further value as the backbone of taxonomy and as historical samples that can be subjected to further analysis. Yet, as physical objects scattered across collections around the world, their scientific use cases are limited by an overall lack of FAIRness, i.e. not easily Findable, Accessible, Interoperable or Reusable. Digitization of these specimens through imaging and categorical metadata capture can improve this FAIRness and has been done to some extent for decades already, but only recently have technical developments in the field of imaging and information technology made it possible for the fruits of these digitization efforts to be widely distributed and utilized. Digitization can be done in many different ways and while protocols may be well formulated during a project or within the responsible digitization team, they are often not communicated beyond to users, get lost with time and are not available for analysts to assess the state of digitization or make requests concerning material for which further information may be available. Hence, as digitization is ongoing, it is a difficult exercise to estimate how much has been digitized, and to what extent, at the collection level or on a larger scale. The Minimum Information about a Digital Specimen (MIDS) standard that is currently under development by a Working Group of Biodiversity Information Standards (TDWG) aims to address this problem by defining hierarchical levels of digitization, each associated with a set of criteria for a level to be achieved by an individual specimen. MIDS has been in development since work in the ICEDIG project in 2019 and its earlier drafts have been used in surveys to try and determine digitization status, often through coarse estimates based on the experience of curators. As a result, these scores cannot be considered reproducible or particularly reliable. Ideally, MIDS scores can be calculated automatically based on a mapping made between the data model of the source and the MIDS criteria. These mappings should also take into account any data value that is known not to be reflective of digitization status. While in an ideal world there would be only one accepted mapping for any data model, different practices causing interoperability conflicts and different kinds of specimens will likely continue to require slight modifications. To make this concrete, we constructed a few JSON schemas that specify such mappings, based on the current specification of the MIDS standard and the state of biodiversity data in a few sources, including Darwin Core archives for occurrence data as produced by the Global Biodiversity Information Facility (GBIF). These schemas could be incorporated into existing data publication workflows to automatically calculate MIDS levels. We have also developed an R Shiny app with a user interface to make calculations and simple adjustments of the schemas. We welcome anyone interested to further develop the syntax and philosophy behind the schemas and their integration into other systems.

CitSci.org is a global citizen science software platform and support organization housed at Colorado State University. The mission of CitSci is to help people do high quality citizen science by amplifying impacts and outcomes. This platform hosts over one thousand projects and a diverse volunteer base that has amassed over one million observations of the natural world, focused on biodiversity and ecosystem sustainability. It is a custom platform built using open source components including: PostgreSQL, Symfony, Vue.js, with React Native for the mobile apps. CitSci sets itself apart from other Citizen Science platforms through the flexibility in the types of projects it supports rather than having a singular focus. This flexibility allows projects to define their own datasheets and methodologies. The diversity of programs we host motivated us to take a founding role in the design of the PPSR Core, a set of global, transdisciplinary data and metadata standards for use in Public Participation in Scientific Research (Citizen Science) projects. Through an international partnership between the Citizen Science Association, European Citizen Science Association, and Australian Citizen Science Association, the PPSR team and associated standards enable interoperability of citizen science projects, datasets, and observations. Here we share our experience over the past 10+ years of supporting biodiversity research both as developers of the CitSci.org platform and as stewards of, and contributors to, the PPSR Core standard. Specifically, we share details about: the origin, development, and informatics infrastructure for CitSci our support for biodiversity projects such as population and community surveys our experiences in platform interoperability through PPSR Core working with the Zooniverse, SciStarter, and CyberTracker data quality data sharing goals and use cases. the origin, development, and informatics infrastructure for CitSci our support for biodiversity projects such as population and community surveys our experiences in platform interoperability through PPSR Core working with the Zooniverse, SciStarter, and CyberTracker data quality data sharing goals and use cases. We conclude by sharing overall successes, limitations, and recommendations as they pertain to trust and rigor in citizen science data sharing and interoperability. As the scientific community moves forward, we show that Citizen Science is a key tool to enabling a systems-based approach to ecosystem problems.

The utopian vision is of a future where a digital representation of each object in our collections is accessible through the internet and sustainably linked to other digital resources. This is a long term goal however, and in the meantime there is an urgent need to share data about our collections at a higher level with a range of stakeholders (Woodburn et al. 2020). To sustainably achieve this, and to aggregate this information across all natural science collections, the data need to be standardised (Johnston and Robinson 2002). To this end, the Biodiversity Information Standards (TDWG) Collection Descriptions (CD) Interest Group has developed a data standard for describing collections, which is approaching formal review for ratification as a new TDWG standard. It proposes 20 classes (Suppl. material 1) and over 100 properties that can be used to describe, categorise, quantify, link and track digital representations of natural science collections, from high-level approximations to detailed breakdowns depending on the purpose of a particular implementation. The wide range of use cases identified for representing collection description data means that a flexible approach to the standard and the underlying modelling concepts is essential. These are centered around the ‘ObjectGroup’ (Fig. 1), a class that may represent any group (of any size) of physical collection objects, which have one or more common characteristics. This generic definition of the ‘collection’ in ‘collection descriptions’ is an important factor in making the standard flexible enough to support the breadth of use cases. For any use case or implementation, only a subset of classes and properties within the standard are likely to be relevant. In some cases, this subset may have little overlap with those selected for other use cases. This additional need for flexibility means that very few classes and properties, representing the core concepts, are proposed to be mandatory. Metrics, facts and narratives are represented in a normalised structure using an extended MeasurementOrFact class, so that these can be user-defined rather than constrained to a set identified by the standard. Finally, rather than a rigid underlying data model as part of the normative standard, documentation will be developed to provide guidance on how the classes in the standard may be related and quantified according to relational, dimensional and graph-like models. So, in summary, the standard has, by design, been made flexible enough to be used in a number of different ways. The corresponding risk is that it could be used in ways that may not deliver what is needed in terms of outputs, manageability and interoperability with other resources of collection-level or object-level data. To mitigate this, it is key for any new implementer of the standard to establish how it should be used in that particular instance, and define any necessary constraints within the wider scope of the standard and model. This is the concept of the ‘collection description scheme,’ a profile that defines elements such as: which classes and properties should be included, which should be mandatory, and which should be repeatable; which controlled vocabularies and hierarchies should be used to make the data interoperable; how the collections should be broken down into individual ObjectGroups and interlinked, and how the various classes should be related to each other. which classes and properties should be included, which should be mandatory, and which should be repeatable; which controlled vocabularies and hierarchies should be used to make the data interoperable; how the collections should be broken down into individual ObjectGroups and interlinked, and how the various classes should be related to each other. Various factors might influence these decisions, including the types of information that are relevant to the use case, whether quantitative metrics need to be captured and aggregated across collection descriptions, and how many resources can be dedicated to amassing and maintaining the data. This process has particular relevance to the Distributed System of Scientific Collections (DiSSCo) consortium, the design of which incorporates use cases for storing, interlinking and reporting on the collections of its member institutions. These include helping users of the European Loans and Visits System (ELViS) (Islam 2020) to discover specimens for physical and digital loans by providing descriptions and breakdowns of the collections of holding institutions, and monitoring digitisation progress across European collections through a dynamic Collections Digitisation Dashboard. In addition, DiSSCo will be part of a global collections data ecosystem requiring interoperation with other infrastructures such as the GBIF (Global Biodiversity Information Facility) Registry of Scientific Collections, the CETAF (Consortium of European Taxonomic Facilities) Registry of Collections and Index Herbariorum. In this presentation, we will introduce the draft standard and discuss the process of defining new collection description schemes using the standard and data model, and focus on DiSSCo requirements as examples of real-world collection descriptions use cases.

Most users will foresee the use of genetic sequences in the context of molecular ecology or phylogenetic research, however, a sequence with coordinates and a timestamp is a valuable biodiversity occurrence that is useful in a much broader context than its original purpose. To uncover this potential, sequence-derived data need to become findable, accessible, interoperable, and reusable through generalist biodiversity data platforms. Stimulated by the Biodiversity_Next discussions in 2019, we have worked for about 10 months to put together practical data mapping and data publishing experiences in Norway, Australia, Sweden, and Denmark, as well as in the UNITE and the GBIF (Global Biodiversity Information Facility) networks. The resulting guide was put together to provide practical instruction for mapping sequence-derived data. Biodiversity data communities remain dominated by the macroscopic, easily detectable, morphologically identifiable species. This is not only true for citizen science and other forms of biodiversity popularization, but is also visible in the university and museum department structures, financial resource allocations, biodiversity legislation, and policy design. Recent decades of molecular advances have increased the power of genetic methods for detecting, describing, and documenting global biodiversity. We have yet to see the wide shift of data generating efforts from the traditional taxonomic foci of biodiversity assesments to the more balanced and inclusive systems focusing on all functionally important taxa and environments. These include soil, limnic and marine environments, decomposing plants and deadwood, and all life therein. Environmental DNA data enable recording of present and past presence of micro- and macroscopic organisms with minimal effort and by non-invasive methods. The apparent ease of these methods requires a cautious approach to the resulting data and their interpretation. It remains important to define and agree on the organism recording and reporting routines for genetic data. DNA data represent a major addition to the many ways in which GBIF and other biodiversity data platforms index the living world. Our guide is resting on the shoulders of those who have been developing and improving MIxS (Minimum Information about any (x) Sequence), GGBN (Global Genome Biodiversity Network) and other data standards. The added value of publishing sequence-derived data through non-genetic biodiversity discovery platforms relates to spatio-temporal occurrences and sequence-based names. Reporting sequence-derived occurrences in an open and reproducible way has a wide range of benefits: notably, it increases citability, highlights the taxa concerned in the context of biological conservation, and contributes to taxonomic and ecological knowledge.

Museums and their collections have specially customized databases in order to optimally gather and record their contents and associated metadata associated with their specimens. To share, exchange, and publish data, an appropriate data standard is essential. ABCD (Access to Biological Collection Data) is a standard for biological collection units, including living and preserved specimen, together with field observation data. Its extension, EFG (Extension for Geoscience), enables sharing and publishing data related to paleontological, mineralogical, and petrological objects. The standard is very granular and allows detailed descriptions, including information about the collection event itself, the holding institution, stratigraphy, chemical analysis, and host rock. The standard extension was developed in 2006 and has been used since then by different initiatives and applied for the publication of collection-related data in domain-specific and interdisciplinary portals.

The Brazilian Plant-Pollinator Interactions Network*1 (REBIPP) aims to develop scientific and teaching activities in plant-pollinator interaction. The main goals of the network are to: generate a diagnosis of plant-pollinator interactions in Brazil; integrate knowledge in pollination of natural, agricultural, urban and restored areas; identify knowledge gaps; support public policy guidelines aimed at the conservation of biodiversity and ecosystem services for pollination and food production; and encourage collaborative studies among REBIPP participants. To achieve these goals the group has resumed and built on previous works in data standard definition done under the auspices of the IABIN-PTN (Etienne Américo et al. 2007) and FAO (Saraiva et al. 2010) projects (Saraiva et al. 2017). The ultimate goal is to standardize the ways data on plant-pollinator interactions are digitized, to facilitate data sharing and aggregation. A database will be built with standardized data from Brazilian researchers members of the network to be used by the national community, and to allow sharing data with data aggregators. To achieve those goals three task groups of specialists with similar interests and background (e.g botanists, zoologists, pollination biologists) have been created. Each group is working on the definition of the terms to describe plants, pollinators and their interactions. The glossary created explains their meaning, trying to map the suggested terms into Darwin Core (DwC) terms, and following the TDWG Standards Documentation Standard*2 in definition. Reaching a consensus on terms and their meaning among members of each group is challenging, since researchers have different views and concerns about which data are important to be included into a standard. That reflects the variety of research questions that underlie different projects and the data they collect. Thus, we ended up having a long list of terms, many of them useful only in very specialized research protocols and experiments, sometimes rarely collected or measured. Nevertheless we opted to maintain a very comprehensive set of terms, so that a large number of researchers feel that the standard meets their needs and that the databases based on it are a suitable place to store their data, thus encouraging the adoption of the data standard. An update of the work will soon be available at REBIPP website and will be open for comments and contributions. This proposal of a data standard is also being discussed within the TDWG Biological Interaction Data Interest Group*3 in order to propose an international standard for species interaction data. The importance of interaction data for guiding conservation practices and ecosystem services provision management has led to the proposal of defining Essential Biodiversity Variables (EBVs) related to biological interactions. Essential Biodiversity Variables (Pereira et al. 2013) were developed to identify key measurements that are required to monitoring biodiversity change. EBVs act as intermediate abstract layer between primary observations (raw data) and indicators (Niemeijer 2002). Five EBV classes have been defined in an initial stage: genetic composition, species populations, species traits, community composition, ecosystem function and ecosystem structure. Each EBV class defines a list of candidate EBVs for biodiversity change monitoring (Fig. 1). Consequently, digitalization of such data and making them available online are essential. Differences in sampling protocols may affect data scalability across space and time, hence imposing barriers to the full use of primary data and EBVs calculation (Henry et al. 2008). Thus, common protocols and methods should be adopted as the most straightforward approach to promote integration of collected data and to allow calculation of EBVs (Jürgens et al. 2011). Recently a Workshop was held by GLOBIS B*4 (GLOBal Infrastructures for Supporting Biodiversity research) to discuss Species Interactions EBVs (February, 26-28, Bari, Italy). Plant-pollinator interactions deserved a lot of attention and REBIPP's work was presented there. As an outcome we expect to define specific EBVs for interactions, and use plant-pollinators as an example, considering pairwise interactions as well as interaction network related variables. The terms in the plant-pollinator data standard under discussion at REBIPP will provide information not only on EBV related with interactions, but also on other four EBV classes: species populations, species traits, community composition, ecosystem function and ecosystem structure. As we said, some EBVs for specific ecosystem functions (e.g. pollination) lay beyond interactions network structures. The EBV 'Species interactions' (EBV class 'Community composition') should incorporate other aspects such as frequency (Vázquez et al. 2005), duration and empirical estimates of interaction strengths (Berlow et al. 2004). Overall, we think the proposed plant-pollinator interaction data standard which is currently being developed by REBIPP will contribute to data aggregation, filling many data gaps and can also provide indicators for long-term monitoring, being an essential source of data for EBVs.

The GGBN Data Standard (https://terms.tdwg.org/wiki/GGBN_Data_Standard) provides a platform based on a documented agreement to promote the efficient sharing and usage of genomic sample material and associated specimen information in a consistent way. It builds upon existing standards commonly used within the community extending them with the capability to exchange data on tissue, environmental and DNA samples as well as sequences. The standard has been recently extended to support environmental DNA and High Throughput Sequencing (HTS) library samples. Both, eDNA and HTS library sample use cases have been published in the GGBN Sandbox (http://sandbox.ggbn.org) and will be presented here. The use case collection is documented in the GGBN wiki (http://wiki.ggbn.org/ggbn/Use_Case_Collection). In addition a general overview of the GGBN Data Portal (http://www.ggbn.org) will be given. Based on ABCD, DwC and the GGBN Data Standard the GGBN Data Portal is the gateway to standardized access of DNA, tissue and environmental samples and their associated specimens. The third core piece of GGBN is the GGBN Document Library (https://library.ggbn.org), today containing more than 300 documents about research, management and legal aspects of biodiversity biobanks. We will provide an overview of covered topics and gaps that the community can help to fill. Finally an outlook of goals and priority tasks for the next two years will be given.

The GGBN Data Portal (http://www.ggbn.org, Droege et al. 2014) has established standardised data flows for genomic DNA samples, including voucher specimens, tissue samples, DNA samples as well as resulting sequences and publications. Dealing with different types of DNA (aDNA, gDNA, eDNA) is essential and closely related to user-friendly search and display functionalities. GGBN aims both at preserving voucher specimens of all kinds of DNA as well as making these important data accessible on the Internet. In addition to genomic DNA, the development and use of high-throughput-/next-generation-sequencing (HTS formerly designated NGS) has outstripped current plans of SYNTHESYS and GGBN to join natural history collection data with DNA and tissue collection data. HTS libraries can be considered as a preparation of the genetic material of a single organism or of multiple organism (e.g. from an environmental mixed sample). From that point of view, they are the actual physical molecular representation of a specimen or sample. However, these libraries come with specific adaptors that limit their transferability to other sequencing systems. The libraries are prepared at great expense, but frequently are only used for a single project, not making use of additional useful information that could potentially be generated. To increase the potential of the HTS libraries to be used for multiple projects they have to be discoverable via published metadata. Optimally, HTS library metadata will include specific standardized keywords (by e.g. organism, HTS method etc.). Here we present our ideas and a prototype for eDNA samples and HTS libraries based on the GGBN Data Standard (Droege et al. 2016). A use case collection from animals, diatoms, fungi and plants has been developed and is available in the GGBN Sandbox (see more details at http://wiki.ggbn.org/ggbn/Use_Case_Collection). These examples will be improved upon and kept on-line at least until 2020, so progress can be observed.

Pollination is considered one of the most important processes for biodiversity conservation (Kremen 2005). Recently, the global community, by means of the Intergovernmental Platform of Biodiversity and Ecosystems Services (IPBES 2016), and also, the Convention on Biological Diversity (CBD 2002) recognized the importance of plant-pollinator interactions for ecosystems functioning and sustainable agriculture. The conservation of pollination depends of information about plant-pollinator interactions covering a great diversity of functional and taxonomic groups. Studies show that successful pollination can improve the amount and the quality of plant fecundation and fruit production (Kevan and Imperatriz-Fonseca 2002). However, the success of these actions depends on the knowledge on pollinators, their conservation and interactions with plants and the environment. In order to conserve and manage it, more information needs to be captured about plant-pollinator interactions. Primary data about pollinators is becoming increasingly available online and can be accessed at a number of websites and portals. Many initiatives have also been created to facilitate and to stimulate the dissemination of pollination data, and examples are the Inter-American Biodiversity Information Network - Pollinators Thematic Network - IABIN-PTN (www.biocomp.org.br/iabinptn) and the WebBee (www.webbee.org.br) (Saraiva et al. 2003). One important aspect of this trend is the strong reliance on standardized data schemas and protocols (e.g. Darwin Core - DwC and TDWG Access Protocol for Information Retrieval - TAPIR, respectively) that allow us to share and aggregate biological data, among which pollinator data are included. Although plant-pollinator interaction data are critically important to our understanding of the role, importance and effectiveness of (potential) pollinators, they cannot be adequately represented by the current standards for occurrence data (such as DwC). The ways that interaction data are recorded and stored worldwide, as well as their intended use are very diverse. They lack of a common protocol and data schema, that will allow us to aggregate them in web portals and eventually use them to build decision support systems for conservation and sustainable use in agriculture, needs to be addressed. The IABIN-PTN adopted a simple solution to characterize and digitalize plant-pollinator interaction data based on DwC (Cartolano Júnior et al. 2007), allowing the digitalization of many Latin-american collections. Following that work, the Food and Agriculture Organization of the United Nations (FAO) produced a detailed survey of potential descriptors of plant-pollinators interactions. Although the ultimate goal of that work was to propose a data standard, that did not evolve (Cavalheiro et al. 2016). The FAO Global pollination project, adopted in Brazil the same simplified model used by IABIN to digitize plant-pollinator interaction data (Saraiva et al. 2010). Recently many Brazilian scientists gathered around the Brazilian Plant-Pollinator Interactions Network (REBIPP - www.rebipp.org.br) with the aim of developing scientific and teaching activities in the field. The main goals of the network are: generate a diagnosis of plant-pollinator interactions in Brazil; integrate knowledge in pollination of natural, agricultural, urban and restored areas; identify knowledge gaps; support public policy guidelines aimed at the conservation of biodiversity and ecosystem services for pollination and food production; and encourage collaborative studies among REBIPP participants. To achieve these goals the group has resumed those previous works done under the auspices of the IABIN and FAO projects, and a data standard is being discussed. The ultimate goal is to adopt a standard and develop a database of plant-pollinator data in Brazil to be used by the national community. This proposal of a data standard (depicted in Fig. 1) can serve as a starting point for the definition of a global data standard for plant-pollinator interactions under the TDWG umbrella.

The Ocean Biogeographic Information System (OBIS) is the world's most comprehensive online, open-access database of marine species distributions. OBIS grows with millions of new species observations every year. Contributions come from a network of hundreds of institutions, projects and individuals with common goals: to build a scientific knowledge base that is open to the public for scientific discovery and exploration and to detect trends and changes that inform society as essential elements in conservation management and sustainable development. Until now, OBIS has focused solely on the collection of biogeographic data (the presence of marine species in space and time) and operated with optimized data flows, quality control procedures and data standards specifically targeted to these data. Based on requirements from the growing OBIS community to manage datasets that combine biological, physical and chemical measurements, the OBIS-ENV-DATA pilot project was launched to develop a proposed standard and guidelines to make sure these combined datasets can stay together and are not, as is often the case, split and sent to different repositories. The proposal in this paper allows for the management of sampling methodology, animal tracking and telemetry data, biological measurements (e.g., body length, percent live cover, ...) as well as environmental measurements such as nutrient concentrations, sediment characteristics or other abiotic parameters measured during sampling to characterize the environment from which biogeographic data was collected. The recommended practice builds on the Darwin Core Archive (DwC-A) standard and on practices adopted by the Global Biodiversity Information Facility (GBIF). It consists of a DwC Event Core in combination with a DwC Occurrence Extension and a proposed enhancement to the DwC MeasurementOrFact Extension. This new structure enables the linkage of measurements or facts - quantitative and qualitative properties - to both sampling events and species occurrences, and includes additional fields for property standardization. We also embrace the use of the new parentEventID DwC term, which enables the creation of a sampling event hierarchy. We believe that the adoption of this recommended practice as a new data standard for managing and sharing biological and associated environmental datasets by IODE and the wider international scientific community would be key to improving the effectiveness of the knowledge base, and will enhance integration and management of critical data needed to understand ecological and biological processes in the ocean, and on land. Fil: De Pooter, Daphnis. Flanders Marine Institute; Bélgica Fil: Appeltans, Ward. UNESCO-IOC; Bélgica Fil: Bailly, Nicolas. Hellenic Centre for Marine Research, MedOBIS; Grecia Fil: Bristol, Sky. United States Geological Survey; Estados Unidos Fil: Deneudt, Klaas. Flanders Marine Institute; Bélgica Fil: Eliezer, Menashè. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Italia Fil: Fujioka, Ei. University Of Duke. Nicholas School Of Environment. Duke Marine Lab; Estados Unidos Fil: Giorgetti, Alessandra. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Italia Fil: Goldstein, Philip. University of Colorado Museum of Natural History, OBIS; Estados Unidos Fil: Lewis, Mirtha Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina Fil: Lipizer, Marina. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Italia Fil: Mackay, Kevin. National Institute of Water and Atmospheric Research; Nueva Zelanda Fil: Marin, Maria Rosa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico; Argentina Fil: Moncoiffé, Gwenaëlle. British Oceanographic Data Center; Reino Unido Fil: Nikolopoulou, Stamatina. Hellenic Centre for Marine Research, MedOBIS; Grecia Fil: Provoost, Pieter. UNESCO-IOC; Bélgica Fil: Rauch, Shannon. Woods Hole Oceanographic Institution; Estados Unidos Fil: Roubicek, Andres. CSIRO Oceans and Atmosphere; Australia Fil: Torres, Carlos. Universidad Autonoma de Baja California Sur; México Fil: van de Putte, Anton. Royal Belgian Institute for Natural Sciences; Bélgica Fil: Vandepitte, Leen. Flanders Marine Institute; Bélgica Fil: Vanhoorne, Bart. Flanders Marine Institute; Bélgica Fil: Vinci, Mateo. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Italia Fil: Wambiji, Nina. Kenya Marine and Fisheries Research Institute; Kenia Fil: Watts, David. CSIRO Oceans and Atmosphere; Australia Fil: Klein Salas, Eduardo. Universidad Simon Bolivar; Venezuela Fil: Hernandez, Francisco. Flanders Marine Institute; Bélgica