734N/A#

734N/A# Project configuration

734N/A#

734N/A# Environment specific settings can be overridden in:

734N/A# /config/settings/<environment>.yml

734N/A#

734N/A

734N/A# Name of the installation

734N/Aname: "MyOntohub"

734N/A

734N/A# Hostname of the installation

734N/Ahostname: #nil - overwrite in the settings.local.yml

734N/A

734N/A# Generalizing term "Ontology",ALternatives are M:Models and S:Specification

734N/AOMS: ontology

734N/A# In case of Model,this should be used.

734N/AOMS_qualifier: modeling

734N/A

734N/A# Optional asset host for delivery of static files (css, images, javascripts)

734N/A# asset_host: assets.example.com

734N/A

734N/A# Sender address for outgoing mail

734N/Aemail: noreply@example.com

734N/A

734N/A# Mail delivery

734N/A# http://guides.rubyonrails.org/action_mailer_basics.html#action-mailer-configuration

734N/Aaction_mailer:

734N/A # possible values for delivery_method (see ActionMailer documentation):

734N/A # :smtp, :sendmail, :file, :test

734N/A delivery_method: :sendmail

734N/A perform_deliveries: true

734N/A raise_delivery_errors: true

734N/A smtp_settings:

734N/A address: 'mail'

734N/A port: 25

734N/A # Supply the fully qualified domain name in the settings.local.yml at:

734N/A domain: # nil

734N/A enable_starttls_auto: true

734N/A password: # nil

734N/A authentication: # nil

734N/A

734N/A# The number of days a user can access

734N/A# the website without confirming his account.

734N/Aallow_unconfirmed_access_for_days: 3

734N/A

734N/A# Limits for displaying file contents and diffs

734N/Amax_read_filesize: 524_288

734N/Amax_combined_diff_size: 1_048_576

734N/A

734N/A# Timeout for ontology parsing jobs in hours

734N/Aontology_parse_timeout: 6

734N/A

734N/Aasynchronous_execution:

734N/A # possible values for log level (in ascending order of verbosity):

734N/A # UNKNOWN, FATAL, ERROR, WARN, INFO, DEBUG

734N/A log_level: WARN

734N/A

734N/A# Footer links and texts

734N/Afooter:

734N/A - text: Foo Institute

734N/A - text: About

734N/A href: http://about.example.com

734N/A

734N/A# Delivery of exceptions, disabled by default

734N/Aexception_notifier:

734N/A enabled: false

734N/A 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)

# May be nil - then paths.data/repositories is used

git_repositories: data/repositories

# named symlinks to the git repositories

# May be nil - then paths.data/git_daemon is used

symlinks: data/git_daemon

# cache for files that needed to be checked out from the git repositories

# May be nil - then paths.data/commits is used

commits: data/commits

# home directory of the git user

# needed for handling of ssh keys in ~git/.ssh/authorized_keys

# May be nil - then paths.data/git is used

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

# The time between update-checks of registered hets-instances in minutes

time_between_updates: 360

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'

access_token:

expiration_minutes: 360

allowed_iri_schemes:

- http

- https

- file

- gopher

- urn

display_head_commit: false

display_symbols_tab: false

format_selection: false

# Your secret key for verifying the integrity of signed cookies.

# If you change this key, all old signed cookies will become invalid!

# Make sure the secret is at least 64 characters and all random,

# no regular words or you'll be exposed to dictionary attacks.

#

# This is just an example value.

# Overwrite this in your settings.local.yml or settings/production.local.yml!

secret_token: '6b198bfe3759ee41524d3a0d7547890a2d277f44f2ce472921ced9bac1833830028bbcacf58fdac0b482265042baa8df4de86a86ad63711ef5b50f70e57d5a07'

# 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)

url: http://www.opensource.apple.com/license/apsl/

- name: Open Software License (OSL)

url: http://opensource.org/licenses/OSL-3.0

- name: General Public License (GPL)

url: http://www.gnu.org/licenses/gpl.html

- name: IBM Public License (IBM PL)

url: http://opensource.org/licenses/IPL-1.0

- name: Common Public License (CPL)

url: http://www.eclipse.org/legal/cpl-v10.html

- name: Lesser General Public License (LGPL)

url: https://www.gnu.org/licenses/lgpl.html

- name: INTEL Open Source License (INTEL OSL)

url: http://opensource.org/licenses/Intel

- name: Modified BSD License (mBSD)

url: http://opensource.org/licenses/BSD-3-Clause

- name: Academic Free License (AFL)

url: http://opensource.org/licenses/AFL-3.0

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.