Metadata-Version: 1.1
Name: ckanext-dataontosearch
Version: 0.0.4
Summary: Integration of an externally running DataOntoSearch instance, providing dataset tagging and search
Home-page: https://github.com/tobinus/ckanext-dataontosearch
Author: Thorben Werner Sjøstrøm Dahl
Author-email: thorben@sjostrom.no
License: AGPL
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        ======================
        ckanext-dataontosearch
        ======================
        
        Extension for integrating CKAN with DataOntoSearch.
        
        DataOntoSearch is a project which aims to make it easier to find datasets, by using a domain-specific ontology to find similar datasets. The software is run as a separate server, which other projects like CKAN can connect to.
        
        There are two separate plugins provided with this extension. ``dataontosearch_tagging`` provides a way of associating datasets with concepts in the ontology. (Each such association is internally called a "tag", which should not be confused with the traditional tags CKAN provide.) ``dataontosearch_searching`` provides an integrated way of searching using DataOntoSearch.
        
        The extension adds a link you can follow when editing datasets. From there, you can change what concepts are connected to what datasets.
        
        The extension also adds a link to the alternative search method. Following it lets you search using DataOntoSearch.
        
        
        ------------
        Requirements
        ------------
        
        This plugin was developed for CKAN version 2.8. We have not checked what other versions it works with.
        
        
        ------------
        Installation
        ------------
        
        .. Add any additional install steps to the list below.
           For example installing any non-Python dependencies or adding any required
           config settings.
        
        To install ckanext-dataontosearch:
        
        1. Ensure that the ckanext-dcat_ extension is installed.
        
        .. _ckanext-dcat: https://github.com/ckan/ckanext-dcat
        
        2. Ensure that CKAN can accept multiple requests in parallel. For example, if
           you use ``gunicorn`` to run your application, you could use the ``-w`` flag
           to specify more than 1 worker: ``gunicorn -w 4 …`` (This is necessary
           because this extension's request to DataOntoSearch might cause
           DataOntoSearch to make a request back to CKAN, so the applications would end
           up waiting for each other in a deadlock.) Note that the ``debug`` setting
           must be set to ``false`` for CKAN to work in parallel.
        
        3. Activate your CKAN virtual environment, for example::
        
             . /usr/lib/ckan/default/bin/activate
        
        4. Install the ckanext-dataontosearch Python package into your virtual environment::
        
             pip install ckanext-dataontosearch
        
        5. Add ``dataontosearch_tagging`` and ``dataontosearch_searching`` to the ``ckan.plugins`` setting in your CKAN
           config file (by default the config file is located at
           ``/etc/ckan/default/production.ini``). Both are not required, any one of them can be used alone, but that is rather uncommon. They need to be listed after the ``dcat`` plugins.
        
        6. Add required settings::
        
             # Base URL where dataset_tagger is running
             ckan.dataontosearch.tagger_url = https://example.com/tagger
        
             # Base URL where the search for DataOntoSearch is running
             ckan.dataontosearch.search_url = https://example.com/search
        
             # The DataOntoSearch Configuration to use
             ckan.dataontosearch.configuration = 5c7ea259c556bb42803fa17e
        
        7. Restart CKAN. For example if you've deployed CKAN with Apache on Ubuntu::
        
             sudo service apache2 reload
        
        
        ---------------
        Config Settings
        ---------------
        
        The required settings are described in the installation guide. In addition to those, you may specify the login used when connecting to DataOntoSearch::
        
            # Username and password to use when querying and tagging datasets in
            # DataOntoSearch (HTTP Basic Authentication)
            # (optional, default: no credentials).
            ckanext.dataontosearch.username = aladdin
            ckanext.dataontosearch.password = opensesame
        
        
        In addition, you can also tell the extension to use the autotagged similarity graph when searching, instead of the manual tags::
        
            # Whether to use the autotagged graph instead of the manual one when
            # searching (optional, default: no).
            ckan.dataontosearch.use_autotag = yes
        
        
        ------------------------
        Development Installation
        ------------------------
        
        To install ckanext-dataontosearch for development, activate your CKAN virtualenv and
        do::
        
            git clone https://github.com/tobinus/ckanext-dataontosearch.git
            cd ckanext-dataontosearch
            python setup.py develop
            pip install -r dev-requirements.txt
        
        
        -----------------
        Running the Tests
        -----------------
        
        To run the tests, do::
        
            nosetests --nologcapture --with-pylons=test.ini
        
        To run the tests and produce a coverage report, first make sure you have
        coverage installed in your virtualenv (``pip install coverage``) then run::
        
            nosetests --nologcapture --with-pylons=test.ini --with-coverage --cover-package=ckanext.dataontosearch --cover-inclusive --cover-erase --cover-tests
        
        
        -------------------------------------------------
        Releasing a New Version of ckanext-dataontosearch
        -------------------------------------------------
        
        ckanext-dataontosearch is availabe on PyPI as https://pypi.python.org/pypi/ckanext-dataontosearch.
        To publish a new version to PyPI follow these steps:
        
        1. Update the version number in the ``setup.py`` file.
           See `PEP 440 <http://legacy.python.org/dev/peps/pep-0440/#public-version-identifiers>`_
           for how to choose version numbers, using the principles of `semantic versioning <https://semver.org/>`_.
        
        2. Create a source distribution of the new version::
        
             python setup.py sdist
        
        3. Upload the source distribution to PyPI (assuming you have run ``pip install twine`` before)::
        
             twine upload dist/*
        
        4. Tag the new release of the project on GitHub with the version number from
           the ``setup.py`` file. For example if the version number in ``setup.py`` is
           0.0.2 then do::
        
               git tag 0.0.2
               git push --tags
        
Keywords: CKAN search ontology
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)
Classifier: Programming Language :: Python :: 2.7
