Debian Science Project
Summary
Data Management
Debian Science Data Management packages

This metapackage will install packages to assist with data management tasks, such as obtaining data from remote resources, keeping data under version control, etc.

Description

For a better overview of the project's availability as a Debian package, each head row has a color code according to this scheme:

If you discover a project which looks like a good candidate for Debian Science to you, or if you have prepared an unofficial Debian package, please do not hesitate to send a description of that project to the Debian Science mailing list

Links to other tasks

Debian Science Data Management packages

Official Debian packages with high relevance

datalad
data files management and distribution platform
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upstream1.1.1
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Git

DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions

  • command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get)
  • extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support)
  • crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler)
datalad-container
DataLad extension for working with containerized environments
Maintainer: Yaroslav Halchenko
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This extension enhances DataLad (http://datalad.org) for working with computational containers.

git-annex
manage files with git, without checking their contents into git
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stretch6.20170101-1+deb9u2amd64,arm64,i386,mips,mips64el,mipsel,ppc64el,s390x
stretch-security6.20170101-1+deb9u1amd64,i386
jessie-security5.20141125+oops-1+deb8u2amd64,armel,armhf,i386
stretch-backports6.20180913-1~bpo9+1mipsel
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trixie10.20240430-1amd64,arm64,i386,mips64el,ppc64el,riscv64,s390x
bookworm-backports10.20240430-1~bpo12+1amd64,arm64,armhf,i386,mips64el,mipsel,ppc64el,s390x
bookworm-backports10.20240129-1~bpo12+1armel
bookworm10.20230126-3amd64,arm64,i386,mips64el,mipsel,ppc64el,s390x
bullseye8.20210223-2amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
buster-backports8.20200330-1~bpo10+1amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x
buster7.20190129-3amd64,arm64,armhf,i386
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Git

git-annex allows managing large files with git, without storing the file contents in git. It can sync, backup, and archive your data, offline and online. Checksums and encryption keep your data safe and secure. Bring the power and distributed nature of git to bear on your large files with git-annex.

It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with dozens of cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved.

git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way.

The package is enhanced by the following packages: elpa-git-annex elpa-magit-annex keysafe
Screenshots of package git-annex
hdf5-filter-plugin
external filters for HDF5: LZ4, BZip2, Bitshuffle
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The external filter mechanism introduced with HDF5 1.8.12 allows applications to utilize custom filters not shipped by the HDF5 core library without recompiling your application. This package provides external filters for HDF5 for

  • the LZ4 compression algorithm
  • BZip2 compression
hdf5-filter-plugin-blosc-serial
blocking, shuffling and lossless compression library
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This package contains a filter for HDF5 that uses the Blosc compressor. By installing this filter, you can read and write HDF5 files with Blosc-compressed datasets.

hdf5-filter-plugin-zfp-serial
Compression plugin for the HDF5 library using ZFP compression
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H5Z-ZFP is a compression filter for HDF5 using the ZFP compression library, supporting lossy and lossless compression of floating point and integer data to meet bitrate, accuracy, and/or precision targets.

nexus-tools
NeXus scientific data file format - applications
Versions of package nexus-tools
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bookworm4.4.3-5amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
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NeXus is a common data format for neutron, X-ray, and muon science. It is being developed as an international standard by scientists and programmers representing major scientific facilities in Europe, Asia, Australia, and North America in order to facilitate greater cooperation in the analysis and visualization of neutron, X-ray, and muon data.

This is the package containing some applications for reading and writing NeXus files.

plfit
fitting power-law distributions to empirical data -- interfaces
Versions of package plfit
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The plfit software fits power-law distributions to empirical (discrete or continuous) data, according to the method of Clauset, Shalizi and Newman [SIAM Review 51, 661-703 (2009)].

This package provides two command line utilities, plfit and plgen.

The package is enhanced by the following packages: plfit-doc
python3-jdata
JData encoder/decoder for python 3
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The JData Specification (https://github.com/fangq/jdata/) defines a lightweight language-independent data annotation interface targeted at storing and sharing complex data structures across different programming languages such as MATLAB, JavaScript, python etc. Using JData formats, a complex python data structure can be encoded as a dict object that is easily serialized as a JSON/binary JSON file and share such data between programs of different languages.

python3-mdp
Modular toolkit for Data Processing
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Python data processing framework for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers.

The package is enhanced by the following packages: python3-sklearn
python3-nxs
NeXus scientific data file format - Python 3 binding
Versions of package python3-nxs
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NeXus is a common data format for neutron, X-ray, and muon science. It is being developed as an international standard by scientists and programmers representing major scientific facilities in Europe, Asia, Australia, and North America in order to facilitate greater cooperation in the analysis and visualization of neutron, X-ray, and muon data.

This is the package containing the Python 3 bindings.

python3-pyzoltan
Wrapper for the Zoltan data management library
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PyZoltan is as the name suggests, is a Python wrapper for the Zoltan data management library.

In PyZoltan, only specific routines and objects are wrapped. The following features of Zoltan are currently supported:

  • Dynamic load balancing using geometric algorithms
  • Unstructured point-to-point communication
  • Distributed data directories
virtuoso-opensource
high-performance database
Versions of package virtuoso-opensource
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bookworm7.2.5.1+dfsg1-0.3all
trixie7.2.12+dfsg-0.2all
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upstream7.2.13
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OpenLink Virtuoso is a high-performance object-relational SQL database. It provides transactions, a smart SQL compiler, hot backup, SQL:1999 support, a powerful stored-procedure language supporting server-side Java or .NET, and more. It supports all major data-access interfaces, including ODBC, JDBC, ADO.NET, and OLE/DB.

Virtuoso supports SPARQL embedded into SQL for querying RDF data stored in its database. SPARQL benefits from low-level support in the engine itself, such as SPARQL-aware type-casting rules and a dedicated IRI data type.

Install this metapackage for the full suite of packages that make up Virtuoso OSE ("Open-Source Edition").

visidata
rapidly explore columnar data in the terminal
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VisiData is a multipurpose terminal utility for exploring, cleaning, restructuring and analysing tabular data. Current supported sources are TSV, CSV, fixed-width text, JSON, SQLite, HTTP, HTML, .xls, and .xlsx (Microsoft Excel).

Official Debian packages with lower relevance

libnexus-dev
NeXus scientific data file format - development libraries
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NeXus is a common data format for neutron, X-ray, and muon science. It is being developed as an international standard by scientists and programmers representing major scientific facilities in Europe, Asia, Australia, and North America in order to facilitate greater cooperation in the analysis and visualization of neutron, X-ray, and muon data.

This is the package containing the development libraries.

libnexus-java
NeXus scientific data file format - java libraries
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NeXus is a common data format for neutron, X-ray, and muon science. It is being developed as an international standard by scientists and programmers representing major scientific facilities in Europe, Asia, Australia, and North America in order to facilitate greater cooperation in the analysis and visualization of neutron, X-ray, and muon data.

This is the package containing the java libraries.

libplfit-dev
fitting power-law distributions to empirical data -- development
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The plfit software fits power-law distributions to empirical (discrete or continuous) data, according to the method of Clauset, Shalizi and Newman [SIAM Review 51, 661-703 (2009)].

This package contains the header files, static libraries and symbolic links that developers using the plfit library will need.

The package is enhanced by the following packages: plfit-doc
python3-openpyxl
Python 3 module to read/write OpenXML xlsx/xlsm files
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Openpyxl is a pure Python 3 module to read/write Excel 2007 (OpenXML) xlsx/xlsm files.

This package contains the module itself.

python3-opentsne
t-Distributed Stochastic Neighbor Embedding algorithm
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Modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE), a popular dimensionality-reduction algorithm for visualizing high-dimensional data sets. openTSNE incorporates the latest improvements to the t-SNE algorithm, including the ability to add new data points to existing embeddings, massive speed improvements, enabling t-SNE to scale to millions of data points and various tricks to improve global alignment of the resulting visualizations.

python3-plfit
fitting power-law distributions to empirical data -- Python
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The plfit software fits power-law distributions to empirical (discrete or continuous) data, according to the method of Clauset, Shalizi and Newman [SIAM Review 51, 661-703 (2009)].

This package provides a Python module.

The package is enhanced by the following packages: plfit-doc
*Popularitycontest results: number of people who use this package regularly (number of people who upgraded this package recently) out of 235799