settings.yml revision e2586f58230ac2938db5ee91191108988b206e2f
#
# Project configuration
#
# Environment specific settings can be overridden in:
# /config/settings/<environment>.yml
#
# Name of the installation
name: "MyOntohub"
# Hostname of the installation
hostname: #nil - overwrite in the settings.local.yml
# Generalizing term "Ontology",ALternatives are M:Models and S:Specification
OMS: ontology
# In case of Model,this should be used.
OMS_qualifier: modeling
# Optional asset host for delivery of static files (css, images, javascripts)
# asset_host: assets.example.com
# Sender address for outgoing mail
email: noreply@example.com
# Mail delivery
# http://guides.rubyonrails.org/action_mailer_basics.html#action-mailer-configuration
action_mailer:
# possible values for delivery_method (see ActionMailer documentation):
# :smtp, :sendmail, :file, :test
delivery_method: :sendmail
perform_deliveries: true
raise_delivery_errors: true
smtp_settings:
address: 'mail'
port: 25
# Supply the fully qualified domain name in the settings.local.yml at:
domain: # nil
enable_starttls_auto: true
password: # nil
authentication: # nil
# The number of days a user can access
# the website without confirming his account.
allow_unconfirmed_access_for_days: 3
# Limits for displaying file contents and diffs
max_read_filesize: 524_288
max_combined_diff_size: 1_048_576
# Timeout for ontology parsing jobs in hours
ontology_parse_timeout: 6
# Footer links and texts
footer:
- text: Foo Institute
- text: About
href: http://about.example.com
# Delivery of exceptions, disabled by default
exception_notifier:
enabled: false
email_prefix: "[ontohub exception]"
sender_address: "exceptions@example.com"
exception_recipients:
- exception-recipient@example.com
# The following paths can be absolute paths
# or relative paths to the project root
paths:
# General data.
data: data
# git repositories (names are numbers/ids)
git_repositories: data/repositories
# named symlinks to the git repositories
symlinks: data/git_daemon
# cache for files that needed to be checked out from the git repositories
commits: data/commits
# home directory of the git user
# needed for handling of ssh keys in ~git/.ssh/authorized_keys
git_home: ~git
hets:
# This is the path to the hets executable we use in `rake hets:*` and for the
# process manager in production mode (god)
executable_path: /usr/bin/hets
# The number of hets instances to run in parallel in production mode.
# Minimum: 1, Maximum: number of processors
instances_count: 1
git:
verify_url: http://localhost/
default_branch: 'master'
push_priority:
commits: 1
changed_files_per_commit: 5
fallbacks:
committer_name: 'ontohub_system'
committer_email: 'ontohub_system@ontohub.org'
# The name of the repository in which the externally imported ontology files are
# saved.
external_repository_name: 'External'
allowed_iri_schemes:
- http
- https
- file
- gopher
- urn
display_head_commit: false
display_symbols_tab: false
format_selection: false
# Possible values for metadata, adapted from OMV
formality_levels:
- name: vocabulary
description: "list of words"
- name: terminology
description: "list of concepts with definitions"
- name: taxonomy
description: "terminology with subsumption hierarchy"
- name: axiomatization
description: "ontology with axioms beyond a pure subsumption hierarchy"
# number of axioms per concept can be displayed
license_models:
- name: Apple Public Source License (APSL)
- name: Open Software License (OSL)
- name: General Public License (GPL)
- name: IBM Public License (IBM PL)
- name: Common Public License (CPL)
- name: Lesser General Public License (LGPL)
- name: INTEL Open Source License (INTEL OSL)
- name: Modified BSD License (mBSD)
- name: Academic Free License (AFL)
ontology_types:
- name: Upper Level Ontology
description: describes general, domain-independent concepts e.g. space, time
documentation: http://www.example.com
- name: Core Ontology
description: "describes the most important concepts in a specific domain (also: mid-level ontology)"
documentation: http://www.example.com
- name: Domain Ontology
description: describes some domain of the world
documentation: http://www.example.com
- name: Application Ontology
description: describes some domain in an application-dependent manner
documentation: http://www.example.com
tasks:
- name: SearchTask
description: the task characterizes how ontologies are used to refine common keywordbased search algorithms using domain knowledge in form of subsumption relations. Ontology-driven search is usually performed automatically by means of reasoning services handling particular aspects of an ontology representation language.
- name: AnnotationTask
description: the ontology is used as a controlled vocabulary to annotate Semantic Web resources. This task includes the usage of a semantically rich ontology for representing arbitrarily complex annotation statements on these resources. The task can be performed manually or (semi-)automatically.
- name: QueryRewritingTask
description: complementary to the query formulation dimension, this task applies ontologies to semantically optimize query expressions by means of the domain knowledge (constraints, subsumption relations etc.) The task can be interpreted as a particular art of filtering information. The task is performed automatically; however, it assumes the availability of patterns describing the transformations at query level.
- name: FilteringTask
description: the task describes at a very general level how ontologies are applied to refine the solution space of a certain problem, such as information retrieval or personalization. The task is targeted at being performed semi-automatically or automatically.
- name: IntegrationTask
description: the task characterizes how ontologies provide an integrating environment, an inter-lingua, for information repositories or software tools. In this scenario the ontology is applied (semi-)automatically to merge between heterogeneous data pools in the same or in adjacent domains.
- name: QueryFormulationTask
description: the ontology is used in information retrieval settings as a controlled vocabulary for representing user queries. Usually the task is performed automatically in that the concepts of the ontology is are listed in a query formulation front-end in order to allow users to specifies their queries.
- name: MediationTask
description: the ontology is built to reduce the ambiguities between communicating human or machine agents. It can act as a normative model which formally and clearly defines the meaning of the terms employed in agent interactions. In the context of programmed agents, the task is envisioned to be performed automatically.
- name: ConfigurationTask
description: the ontology is designed to provide a controlled and unambiguous means to represent valid configuration profiles in application systems. As the aim of the ontology is to support the operationalization of particular system-related processes; this task is performed automatically in that the ontology is processed in an automatic manner by means of reasoners or APIs.
- name: PersonalizationTask
description: the ontology is used mainly for providing personalized access to information resources. Individual user preferences w.r.t. particular application settings are formally specified by means of an ontology, which, in conjunction with appropriate reasoning services, can be directly integrated to a personalization component for filtering purposes. The usage of ontologies in personalization tasks might be carried out in various forms, from a direct involvement of the user who manually specifies ontological concepts which optimally describe his preferences, to the ontological modelling of user profiles.
- name: IndexingTask
description: in this scenario, the goal of the ontology is to provide a clearly defined classification and browsing structure for the information items in a repository. Again, the task can be performed manually by domain experts or as part of an application in an automatic or semi-automatic way.
- name: MatchingTask
description: the goal of matching is to establish links between semantically similar data items in information repositories. In contrast to the previous task, matching does not include the production of a shared final schema/ontology as a result of aggregating the matched source elements to common elements. W.r.t. the automatization level the range varies from manual to fully-automatical execution.