Posted:July 10, 2014

50 Ontology Mapping and Alignment Tools

Open Semantic FrameworkMore Than 20 Are Currently Active and Often in Open Source

I have been periodically tracking ontology tools for some time now (also as contained on the Open Semantic Framework wiki). Recent work caused me to update the listing in the ontology matching/mapping/alignment area. Ontology alignment is important once one attempts to integrate across multiple knowledge bases. Steady progress in better performance (precision and recall) has been occurring, though efforts may have plateaued somewhat. Shvaiko and Euzenat have a good report on the state of the art in ontology alignment.

There has been a formalized activity on ontology alignment going back to 2003. This OAEI (Ontology Alignment Evaluation Initiative) has evolved to include formal tests and datasets, and annual evaluations and bake-offs. Over the years, various tools have come and gone, and some have evolved through multiple versions. Some are provided in source or with online demos; others are research efforts with no testable code.

As far as I know, no one has kept a current and comprehensive listing of these tools and their active status (though the Ontology Matching site does have an outdated list). Please accept the listing below as one attempt to redress this gap.

I welcome submissions of new (unlisted) tools, particularly those that are still active and available for download. There are surely gaps in what is listed below. Also, expect some new tools and updated results to be forthcoming from OAEI 2014 as reported at the Ontology Mapping workshop at ISWC effort in October.

Besides the tapering improvement in performance, other notable trends in ontology matching include ways to optimize multiple scoring methods and using background knowledge to help guide alignments.

Active, Often with Code

  • The Alignment API is an API and implementation for expressing and sharing ontology alignments. The correspondences between entities (e.g., classes, objects, properties) in ontologies is called an alignment. The API provides a format for expressing alignments in a uniform way. The goal of this format is to be able to share on the web the available alignments. The format is expressed in RDF, so it is freely extensible. The Alignment API itself is a Java description of tools for accessing the common format. It defines four main interfaces (Alignment, Cell, Relation and Evaluator)
  • AgreementMakerLight is an automated and efficient ontology matching system derived from AgreementMaker
  • Blooms is a tool for ontology matching. It utilizes information from Wikipedia category hierarchy and from the web to identify subclass relationship between entities. See also its Wiki page
  • CODI (Combinatorial Optimization for Data Integration) leverages terminological structure for ontology matching. The current implementation produces mappings between concepts, properties, and individuals. CODI is based on the syntax and semantics of Markov logic and transforms the alignment problem to a maximum-a-posteriori optimization problem
  • COMA++ is a schema and ontology matching tool with a comprehensive infrastructure. Its graphical interface supports a variety of interaction
  • Falcon-AO (Finding, aligning and learning ontologies) is an automatic ontology matching tool that includes the three elementary matchers of String, V-Doc and GMO. In addition, it integrates a partitioner PBM to cope with large-scale ontologies* hMAFRA (Harmonize Mapping Framework) is a set of tools supporting semantic mapping definition and data reconciliation between ontologies. The targeted formats are XSD, RDFS and KAON
  • GOMMA is a generic infrastructure for managing and analyzing life science ontologies and their evolution. The component-based infrastructure utilizes a generic repository to uniformly and efficiently manage many versions of ontologies and different kinds of mappings. Different functional components focus on matching life science ontologies, detecting and analyzing evolutionary changes and patterns in these ontologies
  • HerTUDA is a simple, fast ontology matching tool, based on syntactic string comparison and filtering of irrelevant mappings. Despite its simplicity, it outperforms many state-of-the-art ontology matching tools
  • Karma is an information integration tool to integrate data from databases, spreadsheets, delimited text files, XML, JSON, KML and Web APIs. Users integrate information according to an ontology of their choice using a graphical user interface that automates much of the process. Karma learns to recognize the mapping of data to ontology classes and then uses the ontology to propose a model that ties together these classes
  • KitAMO is a tool for evaluating ontology alignment strategies and their combinations. It supports the study, evaluation and comparison of alignment strategies and their combinations based on their performance and the quality of their alignments on test cases. Based on the SAMBO project
  • The linked open data enhancer (LODE) framework is a set of integrated tools that allow digital humanists, librarians, and information scientists to connect their data collections to the linked open data cloud. It can be applied to any domain with RDF datasets
  • LogMap is highly scalable ontology matching system with ‘built-in’ reasoning and diagnosis capabilities. LogMap can deal with semantically rich ontologies containing tens (and even hundreds) of thousands of classes
  • MapOnto is a research project aiming at discovering semantic mappings between different data models, e.g, database schemas, conceptual schemas, and ontologies. So far, it has developed tools for discovering semantic mappings between database schemas and ontologies as well as between different database schemas. The Protege plug-in is still available, but appears to be for older versions
  • MatchIT automates and facilitates schema matching and semantic mapping between different Web vocabularies. MatchIT runs as a stand-alone or plug-in Eclipse application and can be integrated with popular third party applications. MatchIT’s uses Adaptive Lexicon™ as an ontology-driven dictionary and thesaurus of English language terminology to quantify and ank the semantic similarity of concepts. It apparently is not available in open source
  • OntoM is one component of the OntoBuilder, which is a comprehensive ontology building and managing framework. OntoM provides a choice of mapping and scoring methods for matching schema
  • The Ontology Mapping Tool (OMT) is an Eclipse plug-in part of the Web Service Modeling Toolkit (WSMT), designed to offer support for the semi-automatic creation of ontology mappings. OMT offers a set of features such as multiple ontology perspectives, mapping contexts, suggestions, bottom-up and top-down mapping strategies
  • Optima is a state of the art general purpose tool for performing ontology alignment. It automatically identifies and matches relevant concepts between ontologies. The tool is supported by an intuitive user interface that facilitates the visualization and analysis of ontologies in N3, RDF and OWL and the alignment results. This is an open source ontology alignment frame work. Optima is also available as a plugin to Protégé ontology editor
  • PARIS is a system for the automatic alignment of RDF ontologies. PARIS aligns not only instances, but also relations and classes. Alignments at the instance level cross-fertilize with alignments at the schema level
  • S-Match takes any two tree like structures (such as database schemas, classifications, lightweight ontologies) and returns a set of correspondences between those tree nodes which semantically correspond to one another
  • ServOMap is an ontology matching tool based on Information Retrieval technique relying on the ServO system. To run it, please follow the directions described at
  • The Silk framework is a tool for discovering relationships between data items within different Linked Data sources. Data publishers can use Silk to set RDF links from their data sources to other data sources on the Web. While designed for mapping instance data, it can also be used for schema
  • Yam++ (not) Yet Another Matcher is a flexible and self-configuring ontology matching system for discovering semantic correspondences between entities (i.e., classes, object properties and data properties) of ontologies. This new version YAM++ 2013 has a significant improvement from the previous versions. See also the 2013 results. Code not apparently available.

Not Apparently in Active Use

  • ASMOV (Automated Semantic Mapping of Ontologies with Validation) is an automatic ontology matching tool which has been designed in order to facilitate the integration of heterogeneous systems, using their data source ontologies
  • The AMW (ATLAS Model Weaver) is a tool for establishing relationships (i.e., links) between models. The links are stored in a model, called weaving model
  • Chimaera is a software system that supports users in creating and maintaining distributed ontologies on the web. Two major functions it supports are merging multiple ontologies together and diagnosing individual or multiple ontologies
  • ConcepTool is a system to model, analyse, verify, validate, share, combine, and reuse domain knowledge bases and ontologies, reasoning about their implication
  • CMS (CROSI Mapping System) is a structure matching system that capitalizes on the rich semantics of the OWL constructs found in source ontologies and on its modular architecture that allows the system to consult external linguistic resources
  • ConRef is a service discovery system which uses ontology mapping techniques to support different user vocabularies
  • DRAGO reasons across multiple distributed ontologies interrelated by pairwise semantic mappings, with a vision of peer-to-peer mapping of many distributed ontologies on the Web. It is implemented as an extension to an open source Pellet OWL Reasoner
  • DSSim is an agent-based ontology matching framework; neither application nor source code appears to be available
  • FOAM is the Framework for ontology alignment and mapping. It is based on heuristics (similarity) of the individual entities (concepts, relations, and instances)
  • HMatch is a tool for dynamically matching distributed ontologies at different levels of depth. In particular, four different matching models are defined to span from surface to intensive matching, with the goal of providing a wide spectrum of metrics suited for dealing with many different matching scenarios that can be encountered in comparing concept descriptions of real ontologies
  • IF-Map is an Information Flow based ontology mapping method. It is based on the theoretical grounds of logic of distributed systems and provides an automated streamlined process for generating mappings between ontologies of the same domain
  • LILY is a system matching heterogeneous ontologies. LILY extracts a semantic subgraph for each entity, then it uses both linguistic and structural information in semantic subgraphs to generate initial alignments. The system is presently in a demo version only
  • MAFRA Toolkit – the Ontology MApping FRAmework Toolkit allows users to create semantic relations between two (source and target) ontologies, and apply such relations in translating source ontology instances into target ontology instances
  • Malasco is an ontology matching system for matching large-scale OWL ontologies. It can use different partitioning algorithms and existing matching tools
  • myOntology is used to produce the theoretical foundations, and deployable technology for the Wiki-based, collaborative and community-driven development and maintenance of ontologies instance data and mappings
  • OLA stands for OWL Lite Alignment. This is the name of a method for computing alignments between two OWL (non necessary Lite) ontologies
  • OntoEngine is a step toward allowing agents to communicate even though they use different formal languages (i.e., different ontologies). It translates data from a “source” ontology to a “target”
  • OntoMerge serves as a semi-automated nexus for agents and humans to find ways of coping with notational differences between ontologies with overlapping subject areas
  • The OWL-CTXMATCH application is a Java 5-compliant implementation of the OWL-CTXMATCH algorithm. Beside the Java platform it requires additional libraries and external data source that is WordNet 2.0
  • OLA/OLA2 (OWL-Lite Alignment) matches ontologies written in OWL. It relies on a similarity combining all the knowledge used in entity descriptions. It also deal with one-to-many relationships and circularity in entity descriptions through a fixpoint algorithm
  • OWLS-MX is a hybrid semantic Web service matchmaker. OWLS-MX 1.0 utilizes both description logic reasoning, and token based IR similarity measures. It applies different filters to retrieve OWL-S services that are most relevant to a given query
  • Potluck is a Web-based user interface that lets casual users—those without programming skills and data modeling expertise—mash up data themselves. Potluck is novel in its use of drag and drop for merging fields, its integration and extension of the faceted browsing paradigm for focusing on subsets of data to align, and its application of simultaneous editing for cleaning up data syntactically. Potluck also lets the user construct rich visualizations of data in-place as the user aligns and cleans up the data
  • PRIOR+ is a generic and automatic ontology mapping tool, based on propagation theory, information retrieval technique and artificial intelligence model. The approach utilizes both linguistic and structural information of ontologies, and measures the profile similarity and structure similarity of different elements of ontologies in a vector space model (VSM)
  • RiMOM (Risk Minimization based Ontology Mapping) integrates different alignment strategies: edit-distance based strategy, vector-similarity based strategy, path-similarity based strategy, background-knowledge based strategy, and three similarity-propagation based strategies
  • SAMBO is a system that assists a user in aligning and merging two ontologies in OWL format. The user performs an alignment process with the help of alignment suggestions proposed by the system. The system carries out the actual merging and derives the logical consequences of the merge operations
  • semMF is a flexible framework for calculating semantic similarity between objects that are represented as arbitrary RDF graphs. The framework allows taxonomic and non-taxonomic concept matching techniques to be applied to selected object properties
  • Snoggle is a graphical, SWRL-based ontology mapper. Snoggle attempts to solve the ontology mapping problem by providing a graphical user interface (similar to which of the Microsoft Visio) to guide the process of ontology vocabulary alignment. In Snoggle, user-defined mappings can be serialized into rules, which is expressed using SWRL
  • Terminator is a tool for creating term to ontology resource mappings (documentation in Finnish)
  • Vine is a tool that allows users to perform fast mappings of terms across ontologies. It performs smart searches, can search using regular expressions, requires a minimum number of clicks to perform mappings, can be plugged into arbitrary mapping framework, is non-intrusive with mappings stored in an external file, has export to text files, and adds metadata to any mapping. See also Markup

50 Ontology Mapping and Alignment Tools

More Than 20 Are Currently Active and Often in Open Source



Ontology alignment is important once one attempts to integrate across multiple knowledge bases. Steady progress in better performance (precision and recall) has been occurring, though efforts may have plateaued somewhat.

see above


5 thoughts on “50 Ontology Mapping and Alignment Tools

  1. Dear Mike,

    Great page! I just would like to mention that AgreementMaker is not in it. AgreementMaker is in use by more than one hundred users for several years. It has also been consistently one of the best (and first in conference, anatomy track). Ontology Matching tool in OAEI (please see reports by the organizers). AgreementMaker has a full user interface, is automatically configurable, supports user feedback, has a visual analytics tool, and several other unique features. AgreementMaker papers have now dozens of citations in several top conferences.

    Thanks for mentioning AgreementMakerLight, which is geared to very large ontologies and has recently obtained top places in OAEI (but does not support the features above mentioned as the efforts have been on making the matching algorithms scalable).


    Isabel Cruz

  2. Dear Isabel Cruz,
    i have been working in the area of Ontology Matching for the past three years and i found AgreementMaker as one of the best flexible ontology matching tool. I would like to use it for my research work, but i am not able to get the “AgreementMaker tool” from the website dedicated for downloading it (“”). I would be really thankful , if you can let me know from where i can download the configurable “AgreementMaker tool” . Thank you once again.

    Sathiya Balasubramanian

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