NIFSTD - A Comprehensive Ontology for Neuroscience
Fahim T. Imam, Sarah M. Maynard, Stephen D. Larson, Maryann E. Martone, Amarnath Gupta, Jeffery S. Grethe
Neuroscience Information Framework, University of California, San Diego
As a core component of Neuroscience Information Framework (NIF) project (http://neuinfo.org), NIF Standard (NIFSTD) was Class Definitions. OBO Foundry practice requires all concepts receive clear and specific human readable definitions structured in
envisioned as a set of modular ontologies that provide a comprehensive collection of terminologies to describe neuroscience relevant Aristotelian form: ―A is a B which has C‖, e.g., ―the globus pallidus is a brain region which is found within the basilar region of the
data and resources. We present here on the structure, design principles and current state of NIFSTD. The NIFSTD is a critical vertebrate telencephalon.‖ Without definitions, there is no way to guide the annotation choices made by curators which leads to terms
constituent in the NIF project to enable an effective concept-based search mechanism against a diverse collection of neuroscience being used in unanticipated ways that confound concept-based data federation. As is quite common even with well-utilized
resources. The overall ontology has been assembled in a form that promotes reuse of standard ontologies in biomedical domain, terminologies, not all terms in NIFSTD have definitions at this time. The curation_status annotation property tracks entities that are
easy extension and modification over the course of its evolution. still lacking final definitions; this property is updated as definitions are added (uncurated) and finalized (curated).
Lexical Variants. NIFSTD includes a variety of accepted synonymous terms to identify a distinct concept. These terms serve as an
STRUCTURE AND DESIGN PRINCIPLES aid to annotators and help when using the ontology to index a large text corpus that often employ a variety of synonyms to identify a
specific concept. Lexical variants also include alternative spellings and antiquated terms no longer in common use.
The NIFSTD is constructed according to best practices closely followed by the Open Biological Ontology (OBO) community. It was
built in a modular fashion, each covering a distinct orthogonal neuroscience relevant domain. A list of this module is listed in Table 1. Mapping Existing Equivalent Concepts. In addition to synonymous terms, external identifiers are included from one or more
NIFSTD avoids duplication of efforts by conforming to standards that promote reuse. The modules are standardized to the same external sources where equivalent concepts exist, e.g., UMLS CUIs, NCBI Taxonomy IDs, or NeuroNames IDs. This inter-terminology
upper level ontologies, the Basic Formal Ontology (BFO), OBO Relations Ontology (OBO-RO), and the Ontology of Phenotypic mapping helps to enable automatic data federation and querying against existing data sets already annotated with such IDs.
Qualities (PATO). Through the use of these foundational and generic ontologies, each of these modules was represented in a
standardized manner. This approach not only follows the powerful modularization ontology design pattern Representation of Concept Relations. NIFSTD utilizes the OBO-RO for specifying relationships between entities that are
(http://odps.sourceforge.net/), but can also be more easily extended to provide highly nuanced representations to meet the need of unambiguous, distinct, and constrained. Concepts across domains are related to one another through a set of specific object
emerging neuroscientific research domains. properties specified in the OBO-RO such as located in, contains, inheres in, participates in, etc. These relational properties mostly
exist as inverse pairs—e.g., part of and has part (see below for more detail on relations). Use of the OBO-RO serves both to separate
Domain External sources Import or NIFSTD Module Unique Comment
classes (As of
the representation of different types of relations (e.g., ―is a‖ vs. ―part of‖) and to limit to proliferation of relation types. The former
OWL July 2009) requirement is critical to enabling maximal algorithmic parseability of relations. For instance, it has been documented that the
Organism NCBI Taxonomy, GBIF, ITIS, IMSR, adapt http://purl.org/nif/ontology/ 781 Specifically the taxonomy of model computational power of the Gene Ontology is limited by the fact that it mixes the depiction of ―is a‖ and ―part of‖ relations in a single
taxonomy Jackson Labs mouse catalog BiomaterialEntities/NIF- organisms in common use by neuroscientists
hierarchical graph (Smith et al. 2003). At the same time, it is equally vital that the number of relations not be overly expansive, as
each relation brings with it a computational burden – the computer code required to interpret the meaning of that relation.
Molecules IUPHAR ion channels and receptors, Adapt http://purl.org/nif/ontolo 4, 198 Tested OWL representation techniques on this limited number of
Sequence Ontology (SO); pending: NCBI, IUPHAR; gy/BiomaterialEntities/NI molecules (∼750). See below for more detail on how molecules in Bridge Files and Object Properties. In order to maintain the orthogonal nature of the ontology domain modules, the cross-domain
NCBI Entrez Protein, NCBI RefSeq, NCBI import SO F-Molecule.owl general are to be addressed in NIFSTD
Homologene; NIDA drug lists, PDSP Ki,
relations are specified in separate ontology bridge files rather than incorporated into the individual modules. In this way, the main
ChEBI, and Protein Ontology domain files—e.g., anatomy, cell type, disease, etc.—remain independent of one another. Using these bridge files, the dependencies
Sub-cellular Sub-cellular Anatomy Ontology (SAO) Import http://purl.org/nif/ontology/ 385 contains cell parts and subcellular structures from SAO-CORE — need only be introduced by those applications that require them, such as the NIF system, which requires a description of the
anatomy BiomaterialEntities/NIF- referencing the Gene Ontology Cellular Component taxonomy—and
Subcellular.owl more nerve cell specific structures needed to characterize ultra
anatomical location of nerve cell types. These relations currently reside in the NIF Cell module, but they are being moved to a
structural studies of the nervous system separate files, called ―bridge files‖ (see ―Results‖ section for explanation), so that other applications which seek to use the underlying
Cell CCDB, NeuronDB, NeuroMorpho.org Adapt http://purl.org/nif/ontology/ 277 nerve cell domain ontology, but do not necessarily intend to import those relations, can do so. Bridge files can also choose either to
terminologies; pending: OBO Cell BiomaterialEntities/NIF-
Ontology Cell.owl import the referenced domain ontologies in their entirety or to take a more minimal approach and simply declare the classes they
Gross Anatomy NeuroNames extended by including terms Adapt http://purl.org/nif/ontolo 1,483 Multi-scale representation of Nervous System Mac Macroscopic need to reference.
from BIRN, SumsDB, BrainMap.org, etc gy/BiomaterialEntities/NI anatomy
Nervous Sensory, Behavior, Cognition terms from Adapt http://purl.org/nif/ontolo 149
Importing a New Ontology. The process of importing a new vocabulary into the NIFSTD varies depending upon its state (Table 1) as
system NIF, BIRN, BrainMap.org, MeSH, and gy/Function/NIF- follows:
function UMLS Function.owl If a vocabulary already uses OWL, the OBO-RO and the BFO and is orthogonal to existing modules, the import simply involves
Nervous Nervous system disease from MeSH, Adapt http://purl.org/nif/ontolo 342
adding an owl:import statement to the main ontology file (nif.owl).
system NINDS gy/Dysfunction/NIF- If an existing orthogonal ontology is in OWL but does not use the same foundational ontologies as NIFSTD, then an ontology
dysfunction terminology; pending: OMIM Dysfunction.owl bridge file is constructed declaring the deep level semantic equivalencies such as foundational objects and processes. Relations
Phenotypic PATO Import http://purl.org/nif/ontolo 2112 Imported as part of the OBO foundry core
qualities gy/backend/ BIRNLex- http://ontology.neuinfo.org/NIF/Backend/quality.owl
are drawn from the OBO-RO as needed.
OBO-UBO.owl If the external terminology is organized but has not been represented in OWL, or does not use the same foundation as NIFSTD,
Investigation: Overlaps with molecules above, especially http://purl.org/nif/ontolo n.a. then the terminology is adapted to OWL/RDF in the context of the NIFSTD foundational layer ontologies.
reagents RefSeq for mRNA, ChEBI, Sequence gy/DigitalEntities/NIF-
ontology; pending: Protein Ontology Investigation.owl
Investigation: Import http://purl.org/nif/ontology/ 641 + 58 BIRNLex-Investigation imports a BIRNLex- OBI-Proxy file being Viewing the NIFSTD Vocabularies. The NIFSTD vocabularies are available as owl files which may be viewed using Protégé or
instruments DigitalEntities/NIF- assembled in parallel with the Ontology of Biomedical Investigation
similar ontology tools. However, these tools generally require a fair amount of expertise to use. To create more human friendly viewing
(OBI) This proxy will be replaced by OBI itself, once there is a full
production release of OBI environments, NIFSTD is also available through NCBO BioPortal. It supports searching for specific terms, browse the overall
Investigation: Biomaterial transformations, assays, data Import http://purl.org/nif/ontology/ (Included in same as above—i.e., ultimately derived from ontology concept tree, select specific concepts to display in the graph viewer, and view associated concept properties. Within the NIF,
protocols and collection, data transformation DigitalEntities/NIF- 641 above) OBI NIFSTD is served through an ontology management system called OntoQuest. OntoQuest generates an OWL-compliant relational
schema and supports operations for navigating, path finding, hierarchy exploration, and term searching in ontological graphs.
Investigation: NIF, OBI, IATR/NITRC, NCBC Mostly http://ontology.neuinfo.org/ 62 Will ultimately be a inferred hierarchy based on
resource Resourceome ontology (BRO) adapt, NIF/DigitalEntities/NIF- NITRC, Resourceome, OBI, and NIF
NIFSTD and NeuroLex Wiki. We strive to balance between the involvement of the neuroscience community for domain expertise
type except for
OBI and knowledge engineering community for ontology expertise when constructing the NIFSTD. The wiki version of NIFSTD, the
NeuroLex (http://neurolex.org) has been developed as the easy entry point for the broader community to access, annotate, edit and
Table 1: Domains covered by NIFSTD, along with the vocabularies imported from external sources and the corresponding NIFSTD OWL module. enhance the core NIFSTD lexicon. The peer reviewed contributions in the media wiki are later implanted in NIFSTD OWL modules in
a regular basis. We envision NeuroLex wiki to be the main entry point to NIFSTD contents for the general users and domain experts
Representation Language. The NIFSTD ontology (http://purl.org/nif/ontology/nif.owl) is expressed in Web Ontology Language to view, annotate and contribute to the overall lexicon.
(OWL). The current use of OWL for representing the NIFSTD semantic framework provides both the ability to employ current OWL
and RDF tools to assemble and edit the ontology, as well as a means to support a rich semantic mining capability to NIF in the future.
NIFSTD holds to the OWL Description Logic (OWL-DL) dialect to ensure computational decidability and support of automated NIFSTD Development Workflow. The current NIFSTD development/curation workflow includes the tasks mentioned in each of the
reasoning through the use of a common DL reasoners such as Pallet and Fact++. rectangular boxes followed by a number as in figure 3:
1. Add/Edit NeuroLex Terms/Categories: This step involves various NIF users/ group who are interested to add, update, enhance, or
Re-use of Available Distilled Knowledge Sources. Wherever possible, existing terminologies and ontologies were reused to cover annotate the current NIF vocabularies through NeuroLex. NeuroLex wiki serves as the main entry point/ collaborative interface for
domains that were required by the Neuroscience community (Table 1). These community vocabularies were culled from a variety of implementing changes in the NIFSTD ontology.
sources, ranging from fully structured ontologies to loosely structured controlled vocabularies. Table 2 highlights these source 2. Bulk Upload of Terms: Depending on the number and nature of terms (i.e., adding new large sub-tree of an existing NIFSTD class,
ontologies which were either imported directly or adopted into different NIFSTD modules. Also indicated in Table 1 is whether the or new classes with known parents for a specific NIF module etc.), we can have bulk upload of terms that requires creating too
source was in OWL or needed to be adapted, the number of unique classes (concepts) under each domain/subdomain and any many categories/pages in NeuroLex Wiki by hand otherwise. These requests can be made through a spreadsheet containing the
comments about the import terms with known parents and annotations.
3. Identify Valid Contribution: This step involves identifying the contributions in the previous steps that are valid according to the NIF
Distinct, Orthogonal Concept Domains. Each of the OWL modules in NIFSTD consists of a conceptually orthogonal or distinct domain experts. Every contribution in the NeuroLex requires this step before they get implemented in the actual NIFSTD ontology.
domain (Table 1). Orthogonality is one of the primary OBO Foundry principles critical to ensuring maximal re-usability of the ontology. Valid contributions are identified based on certain criteria such as relevance to neuroscience research, source, consistency,
The modularity helps minimize dependencies and ensure re-use by enabling users to accept only those domains they need for appropriateness of the hierarchy etc. For the newly added categories this step would make sure that the terms are actually new
and not the synonyms or duplicates of the existing NIF concepts. Conclusion
annotating. If an ontology contains one or more domains overlapping with an existing module, files must be mapped extensively to
Currently covering about 20,000+ concepts includes both classes and synonyms, the NIFSTD continues to evolve to incorporate new
specify semantic equivalencies thus creating an added dependency and curatorial burden.
4. Update NIFSTD (testing): This step involves modules and contents as well as implementing more detailed and useful cross-domain relations that follow ontology development
updating the actual NIFSTD OWL files or best practices.
Single Inheritance. Each class within the NIFSTD modules follows single inheritance principle. This promotes the classes to be
creating new OWL files in testing environment
univocal and avoids ambiguities. However, classes with multiple parents can be derived via automated classification on defined
based on the update of contents from previous
classes i.e., asserted classes with logical necessary and sufficient conditions.
5. Testing in OntoQuest: After each significant
Unique Concept Identifiers and Supported Annotations. Each entity in NIFSTD is identified by a unique identifier and is
updates in the owl files, the NIFTD OWL
accompanied by a variety of supporting annotations such as a preferred label, definition, synonymous terms, links to equivalent terms
implementation goes for OntoQuest testing in
in other terminologies, and other lexical variants (Table 3). These properties were developed largely through the import of similar
staging server for feedback.
properties from the Dublin Core Metadata and the Simple Knowledge Organization System (SKOS). Our policy on NIFSTD class
6. Testing in BioPortal: After each significant
identifiers is as follows.
updates in the owl files the NIFSTD OWL
implementation is tested in BioPortal staging
If a module was imported from an OBO Foundry ontology that uses BFO as its foundational ontology, the class names (i.e.,
environment for feedback.
identifiers) remain unchanged. As many modules were imported directly from BIRNLex and BIRNLex follows the OBO foundry
7. Keep persistent links to older versions: After
principles the prefix birnlex_XXXX is frequently used.
positive feedbacks from Step 5 and 6, we
Any extensions added by NIF to an imported ontology are identified by the nifext prefix (NIF extension). If an imported ontology
archive the links to the old owl files and post
was not OBO compliant, e.g., used a string as a class name, was not in OWL or had to be refactored according to BFO, NIF
the links to the Project wiki.
assigns its own class name, and the mapping to the source concept is maintained through the annotation properties, e.g,
NeuroNamesID: 342. Figure : NIFSTD Development/ Curation Workflow
The identifiers for the new classes in NIFSTD are prefixed by nlx (NeuroLex) followed by an extension that indicates the core
module, e.g., nlx_cell_xxxx and nlx_mol_xxxx represent two class identifiers for the Cell and Molecule modules respectively. Tasks 8-13 involves updating the NIFSTD production version, updating the NIFSTD project wiki page with release notes with version
Following the semantic web practice, NIFSTD uses complete Universal Resource Identifiers (URIs) to maintain the identity of a given specific major changes and additions of the new contents in NIFTSD, Updating OntoQuest and BioPortal production versions, and
entity. In the case of a class in NIFSTD, the complete URI is the URI for the OWL module where it resides along with the specific ID updating the textpresso repository of vocabularies with the newly added terms in NIFSTD.
(or local name in XML) for the class within that file—e.g., http:// purl.org/nif/NIF-Anatomy.owl#birnlex_1699 is the URI for middle
Neuroscience Information Framework http://neuinfo.org