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#Use Case DescriptionReferenceAgriculture Data IG (IGAD)Active Data Management Plans IGArchives and Records Professionals for Research Data IG Big Data IGBiodiversity Data Integration IGBrokering IGChemistry Research Data IGData Fabric IGData for Development IG Data Foundations and Terminology IGData in Context IGData Rescue IGDevelopment of cloud computing capacity and education in developing world research IGDigital Practices in History and Ethnography IGDomain Repositories Interest GroupEducation and Training on handling of research dataELIXIR Bridging Force IGEngagement IGEthics and Social Aspects of Data IGFederated Identity Management IGGeospatial IGGlobal Water Information IGHealth DataLibraries for Research Data IGLong tail of research data IGMarine Data Harmonization IGMetabolomics Data Interoperability IGMetadata IGNational Data ServicesPID IGPreservation e-Infrastructure IGQuality of Urban Life IGRDA/CODATA Legal Interoperability IGRDA/CODATA Materials Data, Infrastructure & Interoperability IGRDA/WDS Certification of Digital Repositories IGRDA/WDS Publishing Data Cost Recovery for Data Centres IGRDA/WDS Publishing Data IGRepository Platforms for Research Data IGReproducibility IG Research data needs of the Photon and Neutron Science community IGResearch Data ProvenanceService Management IGStructural Biology IGVocabulary Services Interest Group
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Imma Subirats, Devika Madalli, Johannes KeizerDavid Giaretta, Helen Glaves, Kevin AshleyElise Dunham, Rebecca GrantPeter Baumann, Ben Evans, Kwo-Sen Kuo, Morris RiedelNicola Nicolson, Vince Smith, Paul Kirk, Dimitris KoureasStefano Nativi, Jay PearlmanLeah McEwen, Stuart Chalk, Ian Bruno, David Martinsen, Richard KiddAlan Blatecky, Yunquiang Zhu, Peter WittenburgIngvill C. MochmannGary Berg-Cross, Raphael RitzKeith Jeffery, Rebecca KoskelaElizabeth Griffin, David Gallaher, Lesley WybornHugh Shanahan, Andrew HarrisonKim Fortun, Mike Fortun, Jason Baird JacksonGeorge Alter, Ruth E. Duerr, Robert J. Hanisch, Peter DoornYuri Demchenko, Laura MolloyBengt Persson, Carole Goble, Rob HooftInna Kouper, Andrew MaffeiKalpana Shankar, Candice LaniusDaan Broeder, Bob JonesSuchith Anand, Peter Baumann, Luciene Delazari, Andrea Perego, Chris PettitIlya Zaslavsky, Sylvain Grellet, Tony Boston, Matthew FryWolfram Horstmann, Kathleen Shearer, Michael WittKathleen Shearer and Wolfram HorstmannHelen Glaves, Cyndy Chandler, Dawn WrightChristoph Steinbeck, Shankar Subramanian, Susanna SansoneKeith Jeffery, Rebecca KoskelaKevin Ashley, Adrian BurtonweigelDavid Giaretta, Jamie Shears, Ruth DuerrChris Pettit, Massimo Craglia, Piyushimita (Vonu) ThakuriahPaul F. Uhlir, Enrique Alonso Garcia, Bob ChenJames A. Warren, Laura M. BartoloMicheal Diepenbroek, Ingrid Dillo, Mustapha MokraneAita de Waard, Ingrid Dillo, Simon HodsonTodd Carpenter, Micheal Diepenbroek, Eefke Smit, Jonathan Tedds, Mustapha MokraneDavid Wilcox, Stefan Kramer, Ralph Müller-PfefferkornBernard Schutz, Victoria StoddenAmber Boehnlein, Brian Matthews, Frank Schlünzen, Thomas ProffenDavid Dubin, Bridget AlmasOwen Appleton, Michael Brenner, Thomas SchaafLucia Banci, Chris Morris, Antonio RosatoStephan Zednik and Simon Cox
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1Cosmopolitan species physiological response and strain variability across ecological gradientshttp://cmore.soest.hawaii.edu/rcn2015/files/UseCase_Alexander.pdfaccessing large genomics/transcriptomics databases based on environmental parameters/locationanalyze sequence abundancefigure out queries against genomics databases based on location and related contextbest practices for domain repositories to expose APIs that would enable location and context-based queries
how to ensure that all stakeholders are engaged to make the query possibleExplore best practices for publishing and accessing metabolomics data to enable queries by space/time and environmental context variablescommon metadata elements across geospatial and metagenomics databasesmake sure that taxonomies of organisms of interests are compatible across databases (or formally expressed so that mappings can be done)
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2Diffuse nutrient leakage reporting to the Water Framework Directivehttp://www.eurogeographics.org/documents/RISE18UseCaseDocumentV1.5.pdf
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3Hydroshare Model Resource Use Case: understanding potential of stormwater controls in an urban watershedhttps://github.com/hydroshare/hydroshare/wiki/Hydroshare-Resources-Use-CasesModel programs and model input and output data are part of the data management.Models hosted in the system bring them one step closer to automatically transferring to a high performance compute resource to support modeling with large datasets.Focused on data and models structured for the hydrology and watershed sciences domain.Can become a library for contributed hydrologic model instances (applications of models at a specific site).Individual researchers can publish their models and model instances.Includes a metadata model for model programs and model instances (applications of models at a specific site with input and output data)Holds contributed hydrologic research data related to modeling.Reference to specific model and the input data and parameters enhances reproducibility.Reference to specific model and input data versions enhances provenance. Still somewhat rudimentary and could benefit being advanced.
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4Hydroshare resource Publication Use Casehttps://github.com/researchsoftwareinstitute/software-data-citation-ws/issues/11Engage users early in the research cycle so that metadata grows through evolution of the data resources, and through social media comment and rating additions. This is also the time researchers are interested in the data, and know it best for annotating it with correct metadata, rather than at the end of the project when it is a chore.Use iRODS to work with datasets larger than could efficiently be handled on desktop computers.Focused on data structured for the hydrology and watershed sciences domain.Includes geographic raster, geographic feature and multidimensional space-time resource types. Supports automatic extraction and annotation of coverage metadata for these resource types. Supports map server visualization and applications acting on these resource types.Focused on water data for the hydrologic and watershed sciences domains.Can become a library for contributed hydrologic research data.Individual researchers can publish their data.Strives to balance metadata required for proper interpretation with chasing users away. Could benefit from advances in this area.Can become a platform for contributed hydrologic research data.Enables publication of data and models along with research products to enhance reproducibility.Facilitates versioning and referencing among resources to enhance provenance. Still somewhat rudimentary and could benefit being advanced.
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5CINERGI discovery use case 1: Global rivers: major dissolved anion and cation concentrationshttps://github.com/CINERGI/UseCases/issues/5interactions of dissolved cations and anions in water, and agriculture: accumulation of ions in crops; appropriate water quality for irrigation; concentrations as influenced by agricultural runoff how would this use case be captured in DMPs given the many dependenciespotential re-use of chemical ontologies to find "major dissolved ions" (in Chebi?)how such queries can be cast in foundational terms so that we can use generic query templatescontext and spatial joins?measurements like this may be done in multiple smaller projects and are at riskwhich domain repository data need to be integrated to respond to this query, and how access and other policies, and lifecycles, coordinatedefficient parsing spatial join parameters from such a query, and executing it in a distributed system of servicesthis appears a typical long tail use case: small projects, poorly connected, with questionable sustainability, data retention, lifecycle management, with compatible data in publications and not in managed datasets. Transition guidelines?Sufficient metadata to make this query possible across repositories?given the "long tail" and dynamic nature of data in this query, what are reproducibility criteria and guidelinesanswering the query implies a workflow with provenance recordeda common issue with long tail data is staging them as services for such queries. How we then manage this service lifecycleSeveral ontologies needed: chemical parameters, water quality, coastal features, hydrologic features, samples.
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6CINERGI discovery use case 2: CZO: bedload tracer experiments in the field and ralated studieshttps://github.com/CINERGI/UseCases/issues/1
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7W3C Spatial: Time Series of a Water Coursehttps://www.w3.org/2015/spatial/wiki/Working_Use_Cases#Images.2C_e.g._a_Time_series_of_a_Water_Course_.28Best_Practice.2C_Time.2C_SSN.2C_Coverage.29Depending on the geographical scope and community time series and watercourse can be exposed using different formats. Cross border issuesNeed reference datasets for watercoursesMetadata on timeseries ? Watercourse datasetsHow to steer national water data services into using the same IT approach / standardsPID of watercourse, timeserieTimeseries of something need controlled, shared vocab
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8W3C Spatial: droughts in geologically complex environments where groundwater is importanthttps://www.w3.org/2015/spatial/wiki/Working_Use_Cases#Droughts_in_geological_complex_environments_where_groundwater_is_important_.28Best_Practice.2C_Time.2C_SSN.2C_Coverage.29Hydrogeology data models could be highly complex from an IT point of view. Some are gridded. need for guidance, harmonisation on their storage and the way to querry themDepending on the geographical scope and community the information can be exposed using different formats. Cross border issuesHydrogeology models are fine tuned, often maybe by scientist using various tools. Challenge is how to create, update them based on new information coming in ? (remember it is underground so we often can only infer behaviour of the system)Need reference datasets for surface, ground water (and theiur geospatial connexion!) + monitoring facilitiesSimply having a metadata catalogue describing which hydrogeological model is avaible, where, its resolution, why it was created, using which tool is a plus.
Additionnal information is also crucial to be sure the models are re-used the right way, and the associated uncertainty/biases they vehiculate		Hydrogeology models are often tied to software used to generate them. How can 2 National Water Data Services can share their respective model on the same ressourcePID of hydrogeological modelSharing models and their in/outputs needs controlled, shared vocab
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9NFIE: concept of reach-catchment pairs, uniquely identified at high resolution, to enable real-time vector-based streamflow routingNFIE: https://www.cuahsi.org/NFIE, RAPID: http://rapid-hub.org/This concept directly supports flood forecasting and mapping. The Iowa Flood Center has mapped 3 million reaches and catchments in their state alone. Models and workflow for estimating wide-area streamflow and flooding based on weather forecasts can be taught / learned in a 2-3 day workshop. Reach-catchment networks are not normally captured in most countries, but can be determined from 1:100k flowline network and 30m (or better) elevation models.
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10Data sharing to support transboundary integrated water resources managementhttp://www.tandfonline.com/doi/full/10.1080/02508060.2015.981783
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11Relevant data and parameters for understanding and validating models and comparing
observations about water reservoirs and lakes, with specific emphasis on addressing algae bloom.
https://grid.ifca.es/wiki/ModellingWaterReservoirsWe are also in contact with this IG for the integration of ontologiesWe are in collaboration with EGI.eu and INDIGO DataCloud to enable the prostprocessing of large output files from Delft3D simulations, including how to find the optimal way to explore parameters and find best matchingIn contact for the algae bloom characteristics (in particular expression, as different species and also different harmful impact, like toxins, etc)This is it.Similar reflection regarding Active Management IGWe work with the National Research Council in Spain as a relevant examplePreservation Portal Preservation portal includes launching VM for exact analysis reproduction
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