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Found 10 result(s)

MUSE-Wide

MUSE-Wide archive

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We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth of 1 hour and hence targets more extreme and more luminous objects over 10 times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of MUSE-Wide lies in providing "spectroscopy of everything" without photometric pre-selection. We describe the data reduction, post-processing and PSF characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released with this publication. Using a 3D matched filtering approach we detected 1,602 emission line sources, including 479 Lyman-α (Lya) emitting galaxies with redshifts 2.9≲z≲6.3. We cross-match the emission line sources to existing photometric catalogs, finding almost complete agreement in redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high redshift, we only find ~55% matches to photometric catalogs. We encounter a higher outlier rate and a systematic offset of Δz≃0.2 when comparing our MUSE redshifts with photometric redshifts. Cross-matching the emission line sources with X-ray catalogs from the Chandra Deep Field South, we find 127 matches, including 10 objects with no prior spectroscopic identification. Stacking X-ray images centered on our Lya emitters yielded no signal; the Lya population is not dominated by even low luminosity AGN. A total of 9,205 photometrically selected objects from the CANDELS survey lie in the MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are able to determine the spectroscopic redshift of 98% of 772 photometrically selected galaxies brighter than 24th F775W magnitude. All the data in the first data release - datacubes, catalogs, extracted spectra, maps - are available at the website.

Kikapu

University of the Western Cape Institutional Research Data Respository

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The University of the Western Cape (UWC) uses Figshare for Institutions for their institutional research data repository. It is called Kikapu, and serves as a repository for storing and disseminating research data.

DIGITAL.CSIC

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DIGITAL.CSIC is the institutional repository of the Spanish National Research Council (CSIC). Designed for organising, archiving, preserving and disseminating via open access the scientific output generated as a product of the CSIC research activities by CSIC researchers

melbourne.figshare.com

University of Melbourne data repository

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melbourne.figshare.com is a specialised service that has been tailored according to specific needs and requirements of the University and our community of researchers. The service offered at the University is free to use, provides 100GB of data, and stores all data on the University's storage system.

ZivaHub

Open Data UCT

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The University of Cape Town (UCT) uses Figshare for institutions for their data repository, which was launched in 2017 and is called ZivaHub: Open Data UCT. ZivaHub serves principal investigators at the University of Cape Town who are in need of a repository to store and openly disseminate the data that support their published research findings. The repository service is provided in terms of the UCT Research Data Management Policy. It provides open access to supplementary research data files and links to their respective scholarly publications (e.g. theses, dissertations, papers et al) hosted on other platforms, such as OpenUCT.

Open-source Scientific Software and Service Repository

OSSR

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The ESCAPE Open-source Scientific Software and Service Repository (OSSR) is a sustainable open-access repository to share scientific software, services and datasets to the astro-particle-physics-related communities and enable open science. It is built as a curated Zenodo community (https://zenodo.org/communities/escape2020) integrated with several tools to enable a complete software life-cycle. The ESCAPE Zenodo community welcomes entries that support the software and service projects in the OSSR such as user-support documentation, tutorials, presentations and training activities. It also encourages the archival of documents and material that disseminate and support the goals of ESCAPE.

datacommons@psu

Penn State Data Commons

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The datacommons@psu was developed in 2005 to provide a resource for data sharing, discovery, and archiving for the Penn State research and teaching community. Access to information is vital to the research, teaching, and outreach conducted at Penn State. The datacommons@psu serves as a data discovery tool, a data archive for research data created by PSU for projects funded by agencies like the National Science Foundation, as well as a portal to data, applications, and resources throughout the university. The datacommons@psu facilitates interdisciplinary cooperation and collaboration by connecting people and resources and by: Acquiring, storing, documenting, and providing discovery tools for Penn State based research data, final reports, instruments, models and applications. Highlighting existing resources developed or housed by Penn State. Supporting access to project/program partners via collaborative map or web services. Providing metadata development citation information, Digital Object Identifiers (DOIs) and links to related publications and project websites. Members of the Penn State research community and their affiliates can easily share and house their data through the datacommons@psu. The datacommons@psu will also develop metadata for your data and provide information to support your NSF, NIH, or other agency data management plan.

Portal de Datos Abiertos de la Pontificia Universidad Católica del Perú

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This Open Data Portal gives access to research data from the Public Opinion Institute of the Pontifical Catholic University of Peru, and plans to incorporate open data from other institutes in the mid and large term.

Astromaterials Data System

AstroMat

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The Astromaterials Data System (AstroMat) is a data infrastructure to store, curate, and provide access to laboratory data acquired on samples curated in the Astromaterials Collection of the Johnson Space Center. AstroMat is developed and operated at the Lamont-Doherty Earth Observatory of Columbia University and funded by NASA.

SAO/NASA Astrophysics Data System Dataverse

ADS Dataverse

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This Dataverse will contain data generated by ADS team members using ADS data.