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11 results for “Archival Sources”
Source Code Archiving to the Rescue of Reproducible Deployment — Replication Package
<p>Replication package for the paper:</p> <p>Ludovic Courtès, Timothy Sample, Simon Tournier, Stefano Zacchiroli.<br><em>Source Code Archiving to the Rescue of Reproducible Deployment</em><br><a href="https://acm-rep.github.io/2024/">ACM REP'24</a>, June 18-20, 2024, Rennes, France<br><a href="https://doi.org/10.1145/3641525.3663622">https://doi.org/10.1145/3641525.3663622</a></p> <h2>Generating the paper</h2> <p>The paper can be generated using the following command:</p> <pre><code>guix time-machine -C channels.scm \ -- shell -C -m manifest.scm \ -- make </code></pre> <p>This uses GNU Guix to run <code>make</code> in the exact same computational environment used when preparing the paper. The computational environment is described by two files. The <code>channels.scm</code> file specifies the exact version of the Guix package collection to use. The <code>manifest.scm</code> file selects a subset of those packages to include in the environment.</p> <p>It may be possible to generate the paper without Guix. To do so, you will need the following software (on top of a Unix-like environment):</p> <ul> <li>GNU Make</li> <li>SQLite 3</li> <li>GNU AWK</li> <li>Rubber</li> <li>Graphviz</li> <li>TeXLive</li> </ul> <h2>Structure</h2> <ul> <li><code>data/</code> contains the data examined in the paper</li> <li><code>scripts/</code> contains dedicated code for the paper</li> <li><code>logs/</code> contains logs generated during certain computations</li> </ul> <h2>Preservation of Guix</h2> <p>Some of the claims in the paper come from analyzing the Preservation of Guix (PoG) database as published on January 26, 2024. This database is the result of years of monitoring the extent to which the source code referenced by Guix packages is archived. This monitoring has been carried out by Timothy Sample who occasionally publishes reports on his personal website: <a href="https://ngyro.com/pog-reports/latest/">https://ngyro.com/pog-reports/latest/</a>. The database included in this package (<code>data/pog.sql</code>) was downloaded from <a href="https://ngyro.com/pog-reports/2024-01-26/pog.db">https://ngyro.com/pog-reports/2024-01-26/pog.db</a> and then exported to SQL format. In addition to the SQL file, the database schema is also included in this package as <code>data/schema.sql</code>.</p> <p>The database itself is largely the result of scripts, but also of manual adjustments (where necessary or convenient). The scripts are available at <a href="https://git.ngyro.com/preservation-of-guix/">https://git.ngyro.com/preservation-of-guix/</a>, which is preserved in the Software Heritage archive as well: <a href="https://archive.softwareheritage.org/swh:1:snp:efba3456a4aff0bc25b271e128aa8340ae2bc816;origin=https://git.ngyro.com/preservation-of-guix">https://archive.softwareheritage.org/swh:1:snp:efba3456a4aff0bc25b271e128aa8340ae2bc816;origin=https://git.ngyro.com/preservation-of-guix</a>. These scripts rely on the availability of source code in certain locations on the Internet, and therefore will not yield exactly the same result when run again.</p> <h3>Analysis</h3> <p>Here is an overview of how we use the PoG database in the paper. The exact way it is queried to produce graphs and tables for the paper is laid out in the Makefile.</p> <p>The <code>pog-types.sql</code> query gives the counts of each source type (e.g. “git” or “tar-gz”) for each commit covered by the database.</p> <p>The <code>pog-status.sql</code> query gives the archival status of the sources by commit. For each commit, it produces a count of how many sources are <em>stored</em> in the Software Heritage archive, <em>missing</em> from it, or <em>unknown</em> if stored or missing. The <code>pog-status-total.sql</code> query does the same thing but over all sources without sorting them into individual commits.</p> <p>The <code>disarchive-ratio.sql</code> query estimates the success rate of Disarchive disassembly.</p> <p>Finally, the <code>swhid-ratio.sql</code> query gives the proportion of sources for which the PoG database has an SWHID.</p> <h3>Estimating missing sources</h3> <p>The Preservation of Guix database only covers sources from a sample of commits to the Guix repository. This greatly simplifies the process of collecting the sources at the risk of missing a few. We estimate how many are missed by searching Guix’s Git history for Nix-style base-32 hashes. The result of this search is compared to the hashes in the PoG database.</p> <p>A naïve search of Git history results in an over estimate due to Guix’s branch development model. We find hashes that were never exposed to users of ‘guix pull’. To work around this, we also approximate the history of commits available to ‘guix pull’. We do this by scraping push events from the guix-commits mailing list archives (<code>data/guix-commits.mbox</code>). Unfortunately, those archives are not quite complete. Missing history is reconstructed in the <code>data/missing-links.txt</code> file.</p> <p>This estimate requires a copy of the Guix Git repository (not included in this package). The repository can be obtained from GNU at <a href="https://git.savannah.gnu.org/git/guix.git">https://git.savannah.gnu.org/git/guix.git</a> or from the Software Heritage archive: <a href="https://archive.softwareheritage.org/swh:1:snp:9d7b8dcf5625c17e42d51357848baa226b70e4bb;origin=https://git.savannah.gnu.org/git/guix.git">https://archive.softwareheritage.org/swh:1:snp:9d7b8dcf5625c17e42d51357848baa226b70e4bb;origin=https://git.savannah.gnu.org/git/guix.git</a>. Once obtained, its location must be specified in the Makefile.</p> <p>To generate the estimate, use:</p> <pre><code>guix time-machine -C channels.scm \ -- shell -C -m manifest.scm \ -- make data/missing-sources.txt </code></pre> <p>If not using Guix, you will need additional software beyond what is used to generate the paper:</p> <ul> <li>GNU Guile</li> <li>GNU Bash</li> <li>GNU Mailutils</li> <li>GNU Parallel</li> </ul> <h2>Measuring link rot</h2> <p>In order to measure link rot, we ran Guix Scheme scripts, i.e., scripts that exploit Guix as a Scheme library. The scripts depend on the state of world at the very specific moment when they ran. Hence, it is not possible to reproduce the exact same outputs. However, their tendency over the passing of time should be very similar. For running them, you need an installation of <a href="https://guix.gnu.org/manual/deve/en/html_node/Installation.html">Guix</a>. For instance,</p> <pre><code>guix repl -q scripts/table-per-origin.scm </code></pre> <p>When running these scripts for the paper, we tracked their output and saved it inside the <code>logs</code> directory.</p>
Data archive: Niche overlap between a cold-water coral and an associated sponge for isotopically-enriched particulate food sources
<p>Data belonging to the paper: </p> <p>Dick van Oevelen, Christina E. Mueller, Tomas Lundälv, Fleur C. van Duyl, Jasper M. de Goeij, Jack J. Middelburg<span> </span>(In press) <strong>Niche overlap between a cold-water coral and an associated sponge for isotopically-enriched particulate food sources</strong>. PLOS ONE</p>
Data archive for the peer-reviewed journal article "Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements"
<p>This data archive accompanying the article "Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements", which was accepted in April 2024 in the peer-reviewed journal <strong><em>Science of the Total Environment</em></strong>. This data archive contains the processed OPvDTT measurements, chemical speciation of PM2.5, and source contribution used in the manuscript.</p>
Proteomic source data archive
<p>Source data from proteomic analysis performed in manuscript "<strong>Mitochondrially targeted tamoxifen alleviates markers of obesity and type 2 diabetes mellitus" </strong>by<strong> </strong>Vacurova et al.</p>
ROSAT Results Archive Sources for the PSPC
The ROSPSPC database table contains a list of sources detected by the Standard Analysis Software System (SASS) in public, unfiltered, pointed PSPC datasets. In addition to the parameters returned by SASS (like position, count rate, likelihood, etc.) each source in the table has associated with it a set of source and sequence "flags." These flags are provided by the ROSAT data centers in the US, Germany and the UK to help the user of the ROSPSPC database table quickly judge the reliability of a given source. The ROSPSPC table excludes sources that meet the following parameter criteria: false_det = 'T' or deferred = 'T' or not_checked = 'T'. See the documentation below for descriptions of these parameters. The catalog consists of all primary source parameters from the automated detection algorithm employed by the SASS. In addition each observation has been quality checked, both by automatic algorithms and by detailed visual inspection. The results of this quality checking are contained as a set of logical-value flags for a set of principal source parameters. If a source parameter is suspect, the associated flag is set to "TRUE"; parameters with no obvious problems maintain the default, "FALSE", value. This database table was last updated in August 2001. More information about the ROSAT Results Archive for PSPC sources can be obtained at the following web pages: <pre> <a href="http://heasarc.gsfc.nasa.gov/docs/rosat/rra/RRA.html">http://heasarc.gsfc.nasa.gov/docs/rosat/rra/RRA.html</a> <a href="http://hea-www.harvard.edu/rosat/rra.html">http://hea-www.harvard.edu/rosat/rra.html</a> <a href="http://www.aip.de/groups/xray/rosat/rra.html">http://www.aip.de/groups/xray/rosat/rra.html</a> <a href="http://ledas-www.star.le.ac.uk/rra">http://ledas-www.star.le.ac.uk/rra</a> </pre> This is a service provided by NASA HEASARC .
Chandra Archive Of Galaxies Ultraluminous X-Ray Source Catalog
One hundred fifty-five (the abstract in the paper erroneously states the number to be 154) discrete, non-nuclear, ultraluminous X-ray (ULX) sources, with spectroscopically determined intrinsic X-ray luminosities greater than 10<sup>39</sup> erg/s, have been identified in 82 galaxies that were observed with Chandra's Advanced CCD Imaging Spectrometer (ACIS). Positions, X-ray luminosities, and spectral and timing characteristics of these ULXs are contained in this table. Eighty-three percent of ULX candidates have spectra that can be described as absorbed power laws with mean index Gamma = 1.74 and column density N<sub>H</sub> = 2.24 x 10<sup>21</sup> atoms cm<sup>-2</sup>, or ~5 times the average Galactic column. About 20% of the ULXs have much steeper indices indicative of a soft, and likely thermal, spectrum. The locations of ULXs in their host galaxies are strongly peaked toward their galaxy centers. The deprojected radial distribution of the ULX candidates is somewhat steeper than an exponential disk, indistinguishable from that of the weaker sources. About 5%-15% of ULX candidates are variable during the Chandra observations (which average 39.5 ks). Comparison of the cumulative X-ray luminosity functions of the ULXs to Chandra Deep Field results suggests ~25% of the sources may be background objects, including 14% of the ULX candidates in the sample of spiral galaxies and 44% of those in elliptical galaxies, implying the elliptical galaxy ULX population is severely compromised by background active galactic nuclei. Correlations with host galaxy properties confirm the number and total X-ray luminosity of the ULXs are associated with recent star formation and with galaxy merging and interactions. The preponderance of ULXs in star-forming galaxies as well as their similarities to less-luminous sources suggest they originate in a young but short-lived population such as the high-mass X-ray binaries, with a smaller contribution (based on spectral slope) from recent supernovae. The number of ULXs in elliptical galaxies scales with host galaxy mass and can be explained most simply as the high-luminosity end of the low-mass X-ray binary population. This table was created by the HEASARC in March 2007 based on <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/ApJS/154/519">CDS catalog J/ApJS/154/519</a> file table2.dat. This is a service provided by NASA HEASARC .
ROSAT Complete Results Archive Sources for the PSPC with Filter
This table is derived from the Second ROSAT Source Catalog of Pointed Observations with the ROSAT PSPC (Roentgen Satellite Position-Sensitive Proportional Counter) Observed Using the Boron Filter, or the 2RXF Catalog. 2XRF contains arcsecond positions and count rates for 2,526 detected sources from 258 ROSAT PSPC Filter observations covering 0.15% of the sky, including 704 high-confidence detections and 20 obvious sources which were not detected by SASS. This table contains the complete version of the list of detections (2,526 entries), whereas the short 'high-confidence' version (the HEASARC's <a href="/W3Browse/rosat/rospspcf.html">ROSPSPCF table</a>) contains 704 detections. The ROSPSPCFTOT table includes many questionable sources that meet the following parameter criteria: false_det = 'f' or deferred = 'D' or not_checked = 'n'. See the documentation below for descriptions of these parameters. The catalog consists of all primary source parameters from the automated detection algorithm employed by the SASS. In addition each observation has been quality checked, both by automatic algorithms and by detailed visual inspection. The results of this quality checking are contained as a set of logical-value flags for a set of principal source parameters. If a source parameter is suspect, the associated flag is set to a corresponding alphabetical value; parameters with no obvious problems maintain the default, '.', value. The Second ROSAT Pointed PSPC Filter Source Catalog includes missing sources, i.e. obvious sources which were not detected by the SASS source detection software but which could be easily detected by visual inspection. Missed sources are marked by negative values of their source identification number, i.e. the parameter 'MPLSX_ID' has a negative value for these sources. The only tabulated quantities for these visually identified missed sources are source positions; other quantities (like count rates, hardness ratios, etc.) are not available. These data have been screened by ROSAT data centers in the US, Germany, and the UK as a step in the production of the ROSAT Results Archive. The RRA contains extracted source and associated products with an indication of reliability for the primary parameters. More information about the ROSAT mission and the SASS can be obtained from the ROSAT User Handbook, available at <pre> <a href="http://heasarc.gsfc.nasa.gov/docs/rosat/rosdocs.html">http://heasarc.gsfc.nasa.gov/docs/rosat/rosdocs.html</a> </pre> This table was created by the HEASARC in May 2012 based on the file rospspcfcat.txt obtained from the MPE ROSAT Results Archive site (which is no longer available, unfortunately). This is a service provided by NASA HEASARC .
ROSAT Results Archive Sources for the PSPC with Filter
This table is derived from the Second ROSAT Source Catalog of Pointed Observations with the ROSAT PSPC (Roentgen Satellite Position-Sensitive Proportional Counter) Observed Using the Boron Filter, or the 2RXF Catalog. 2XRF contains arcsecond positions and count rates for 2,526 detected sources from 258 ROSAT PSPC Filter observations covering 0.15% of the sky, including 704 high-confidence detections and 20 obvious sources which were not detected by SASS. The complete version of the list of detections (the HEASARC's <a href="/W3Browse/rosat/rospspcftot.html">ROSPSPCFTOT</a>) table contains 2,526 entries, whereas the short 'high-confidence' version contained in this present table has 704 detection. The ROSPSPCF table excludes sources that meet the following parameter criteria: false_det = 'f' or deferred = 'D' or not_checked = 'n'. See the documentation below for descriptions of these parameters. The catalog consists of all primary source parameters from the automated detection algorithm employed by the SASS. In addition each observation has been quality checked, both by automatic algorithms and by detailed visual inspection. The results of this quality checking are contained as a set of logical-value flags for a set of principal source parameters. If a source parameter is suspect, the associated flag is set to a corresponding alphabetical value; parameters with no obvious problems maintain the default, '.', value. The Second ROSAT Pointed PSPC Filter Source Catalog includes missing sources, i.e. obvious sources which were not detected by the SASS source detection software but which could be easily detected by visual inspection. Missed sources are marked by negative values of their source identification number, i.e. the parameter 'MPLSX_ID' has a negative value for these sources. The only tabulated quantities for these visually identified missed sources are source positions; other quantities (like count rates, hardness ratios, etc.) are not available. These data have been screened by ROSAT data centers in the US, Germany, and the UK as a step in the production of the ROSAT Results Archive. The RRA contains extracted source and associated products with an indication of reliability for the primary parameters. More information about the ROSAT mission and the SASS can be obtained from the ROSAT User Handbook, available at <pre> <a href="http://heasarc.gsfc.nasa.gov/docs/rosat/rosdocs.html">http://heasarc.gsfc.nasa.gov/docs/rosat/rosdocs.html</a> </pre> This table was created by the HEASARC in May 2012 based on the file rospspcfcat-short.txt obtained from the MPE ROSAT Results Archive site (which is no longer available, unfortunately). This is a service provided by NASA HEASARC .
ROSAT Complete Results Archive Sources for the HRI
The ROSHRITOTAL data table contains a list of sources detected by the Standard Analysis Software System (SASS) in reprocessed, public HRI datasets. In addition to the parameters returned by SASS (like position, count rate, signal-to-noise, etc.) each source in the table has associated with it a set of source and sequence "flags." These flags are provided by the ROSAT data centers in the US, Germany and the UK to help the user of the ROSHRITOTAL database table quickly judge the reliability of a given source. The ROSHRITOTAL database table is a superset of the ROSHRI database table. The ROSHRI table excludes sources that meet the following parameter criteria: false_det = 'T' or deferred = 'T' or not_checked = 'T' or un_unique ='T'. See the documentation below for descriptions of these parameters. These data have been screened by ROSAT data centers in the US, Germany, and the UK as a step in the production of the ROSAT Results Archive. The RRA contains extracted source and associated products with an indication of reliability for the primary parameters. This database table was last updated in August 2001. More information about the ROSAT Results Archive for HRI sources can be obtained at the following web pages: <pre> <a href="http://heasarc.gsfc.nasa.gov/docs/rosat/rra/RRA.html">http://heasarc.gsfc.nasa.gov/docs/rosat/rra/RRA.html</a> <a href="http://hea-www.harvard.edu/rosat/rra.html">http://hea-www.harvard.edu/rosat/rra.html</a> <a href="http://www.aip.de/groups/xray/rosat/rra.html">http://www.aip.de/groups/xray/rosat/rra.html</a> <a href="http://ledas-www.star.le.ac.uk/rra">http://ledas-www.star.le.ac.uk/rra</a> </pre> This is a service provided by NASA HEASARC .
ROSAT Results Archive Sources for the HRI
The ROSHRI data table contains a list of sources detected by the Standard Analysis Software System (SASS) in reprocessed, public HRI datasets. In addition to the parameters returned by SASS (like position, count rate, signal-to-noise, etc.) each source in the table has associated with it a set of source and sequence "flags." These flags are provided by the ROSAT data centers in the US, Germany and the UK to help the user of the ROSHRI database table quickly judge the reliability of a given source. The ROSHRI table excludes sources that meet the following parameter criteria: false_det = 'T' or deferred = 'T' or not_checked = 'T' or un_unique ='T'. See the documentation below for descriptions of these parameters. These data have been screened by ROSAT data centers in the US, Germany, and the UK as a step in the production of the ROSAT Results Archive. The RRA contains extracted source and associated products with an indication of reliability for the primary parameters. This database table was last updated in August 2001. More information about the ROSAT Results Archive for HRI sources can be obtained at the following web pages: <pre> <a href="http://heasarc.gsfc.nasa.gov/docs/rosat/rra/RRA.html">http://heasarc.gsfc.nasa.gov/docs/rosat/rra/RRA.html</a> <a href="http://hea-www.harvard.edu/rosat/rra.html">http://hea-www.harvard.edu/rosat/rra.html</a> <a href="http://www.aip.de/groups/xray/rosat/rra.html">http://www.aip.de/groups/xray/rosat/rra.html</a> <a href="http://ledas-www.star.le.ac.uk/rra">http://ledas-www.star.le.ac.uk/rra</a> </pre> This is a service provided by NASA HEASARC .
ROSAT Complete Results Archive Sources for the PSPC
The ROSPSPCTOTAL database table contains a list of sources detected by the Standard Analysis Software System (SASS) in public, unfiltered, pointed PSPC datasets. In addition to the parameters returned by SASS (like position, count rate, likelihood, etc.) each source in the table has associated with it a set of source and sequence "flags." These flags are provided by the ROSAT data centers in the US, Germany and the UK to help the user of the ROSPSPCTOTAL database table quickly judge the reliability of a given source. The ROSPSPCTOTAL database table is a superset of the ROSPSPC database table. The ROSPSPC table excludes sources that meet the following parameter criteria: false_det = 'T' or deferred = 'T' or not_checked = 'T'. See the documentation below for descriptions of these parameters. The catalog consists of all primary source parameters from the automated detection algorithm employed by the SASS. In addition each observation has been quality checked, both by automatic algorithms and by detailed visual inspection. The results of this quality checking are contained as a set of logical-value flags for a set of principal source parameters. If a source parameter is suspect, the associated flag is set to "TRUE"; parameters with no obvious problems maintain the default, "FALSE", value. This database table was last updated in August 2001. More information about the ROSAT Results Archive for PSPC sources can be obtained at the following web pages: <pre> <a href="http://heasarc.gsfc.nasa.gov/docs/rosat/rra/RRA.html">http://heasarc.gsfc.nasa.gov/docs/rosat/rra/RRA.html</a> <a href="http://hea-www.harvard.edu/rosat/rra.html">http://hea-www.harvard.edu/rosat/rra.html</a> <a href="http://www.aip.de/groups/xray/rosat/rra.html">http://www.aip.de/groups/xray/rosat/rra.html</a> <a href="http://ledas-www.star.le.ac.uk/rra">http://ledas-www.star.le.ac.uk/rra</a> </pre> This is a service provided by NASA HEASARC .
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.
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.
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.