# OWL Reasoners still useable in 2023

Konrad Abicht
<EMAIL_ADDRESS>
(13.09.2023)

###### Abstract

In a systematic literature and software review over 100 OWL reasoners/systems
were analyzed to see if they would still be usable in 2023. This has never
been done in this capacity. OWL reasoners still play an important role in
knowledge organisation and management, but the last comprehensive
surveys/studies are more than 8 years old. The result of this work is a
comprehensive list of 95 standalone OWL reasoners and systems using an OWL
reasoner. For each item, information on project pages, source code
repositories and related documentation was gathered. The raw research data is
provided in a Github repository for anyone to use.

##  1 Introduction

There are many surveys and studies concerning OWL reasoners. Some examine the
underlying methods and functionality, others compare performance metrics. One
might think that the field of OWL reasoners is well established and that there
is software for each relevant application. But this is not the case. Instead I
have noticed that well known reasoners have hardly been updated in the last 10
years (e.g. HermiT). Some are still usable, mostly as Protégé plugins, but it
raises the question whether new (research or commercial) projects should rely
on them. How are they maintained? Are bugs detected and dealt with? Do
projects maintain their software dependencies? People interested in OWL
reasoners today face many obstacles. To get a neutral view on the software
landscape, I conducted a survey between May and July 2023. You hold the
results of this work in your hands.

This paper is structured as follows: Section 2 contains short summary of
required background knowledge. Section 3 then summarises related work. Section
4 describes my methodology and the section 5 presents results of my research.
Finally, in section 6, I draw my conclusions and in section 7, I provide
further starting points for future work.

###  1.1 Publicly available research data

All research data is publicly available via a Github repository. It contains a
CSV file with a list of analyzed OWL reasoners as well a CSV file with systems
using a foreign OWL reasoner. For each entry there is metadata about
installation, usability and references such as source code repository. All
this data is available at the following URL:

https://github.com/k00ni/owl-reasoner-list

I invite everyone to contribute. The repository is designed in a way to
support further research and additions, so that others can continue the work
in the years to come without having to start from scratch each time.

Figure 1:  Figure 2:

##  2 Reader background

You should have an extended knowledge of Semantic Web technologies and
concepts such as RDF, RDFS, OWL 1/2 and OWL reasoning. There are many
programming/software environments used to develop OWL reasoners, so basic
knowledge in compiling and executing programs is recommended. Basic knowledge
of software development using distributed version control systems, such as
Git, is helpful. Below is a brief summary of the most widely used systems.

###  2.1 Protégé

Protégé[73] is an ontology editor well known to ontologists and Semantic Web
developers. It has been developed by Stanford
University111https://protege.stanford.edu/. It provides tools for developing
and maintaining OWL ontologies. There are many plugins available, for instance
to use an OWL reasoner. Protégé is written in Java and runs on Windows 10/11
as well as Ubuntu Linux.

###  2.2 OWL API

OWL-API [24] is written in Java and provides an Application Programming
Interface for managing OWL ontologies. In addition to parsing and manipulating
OWL ontologies, it also allows the use of reasoners. It also includes
validators for different OWL profiles, for instance OWL 2
QL222https://www.w3.org/TR/owl2-profiles/#OWL_2_QL, OWL 2
EL333https://www.w3.org/TR/owl2-profiles/#OWL_2_EL or OWL 2
RL444https://www.w3.org/TR/owl2-profiles/#OWL_2_RL. Further information and
source code can be found on the project
page555https://owlcs.github.io/owlapi/.

##  3 Related work

Since the publication of OWL in 2001, there have been many benchmarks and
surveys comparing and evaluating OWL reasoners. In the following only the most
recent and relevant ones are presented.

The most recent and relevant publication [30] is from 2023. The authors
evaluated the performance of six prominent OWL 2 DL compliant reasoners (such
as Pellet, FaCT++ and Hermit) on various reasoning tasks. One of their
findings was that many projects are no longer actively maintained. This
supports my results and observations, even though their metrics differ from
the ones used in this paper (they used a wider range for activity: last 10
years).

The website http://owl.cs.manchester.ac.uk/tools/list-of-reasoners/ is often
cited in publications. It contains a list of 39 reasoners, each entry having a
summary and some metadata such as supported interfaces. Last update was in
June 19, 2018. Authors behind it are Uli Sattler and Nico Matentzoglu. They
link to https://www.w3.org/2001/sw/wiki/OWL/Implementations, an overview of
OWL implementations such as reasoners, editors and APIs. It contains fewer
entries, but still has some interesting details per entry. It was last updated
on June 9, 2020.

In [28] (2017) the authors report on a survey of many Semantic Web tools and
services, including a comparison of 23 OWL reasoners in terms of their
features. All reasoners were reported as usable, but unfortunately there was
no information about maintenance status of OWL reasoners.

The authors of [57] performed a reasoner evaluation in 2015 using 13 reasoners
(such as FaCT++, HermiT and jcel). They reported that all the reasoners were
usable, although they performed very differently in the competition (e.g.
performing DL consistency checking or DL classification). Also in 2015 a
survey was conducted using 35 OWL reasoners [37] by the same authors who also
created http://owl.cs.manchester.ac.uk/tools/list-of-reasoners/. In the survey
they asked developers about functionality, language used and for feedback for
recommended usage. They report that eight reasoners are barely maintained and
CEL and HermiT are not maintained at all.

It is important to note that there no survey or benchmark has been found that
compares more than 35 reasoners. They either focus on the most prominent
reasoners or only use reasoners for a certain OWL profile. Some surveys also
include other systems, such as editors or IDEs, which are out of the scope of
this work.

##  4 Methodology

The motivation behind this survey was to get an objective view of available
OWL reasoners. For a comprehensive overview information such as project status
and usability is important. This information needs to be researched, ordered
and assessed for each OWL reasoner.

The following list contains major research questions:

  1. 1.

Which OWL reasoners are available?

  2. 2.

Which are still usable?

  3. 3.

Which are still actively maintained?

I have chosen these research questions in order to get as neutral an overview
as possible, they provide a basis for further investigation. The second
question refers to usable tools, which is crucial because if a software can no
longer be started, it is useless. In the following I specify the terms OWL
reasoner, usable and actively maintained.

###  4.1 Important terms

####  4.1.1 OWL Reasoner

An OWL reasoner (or semantic reasoner) is basically an inference machine that,
infers logical consequences from a given set of axioms (RDFS/OWL data).
However, my analysis has shown, that OWL reasoners can have a wide range of
features. For example, checking the consistency of an ontology, or checking
whether a given set of rules applies. In this survey, the range of features
scope doesn’t matter as long as it provides OWL reasoning in some way.

An OWL reasoner was included in the analysis if it is an open source project
or is provided free of charge. Furthermore, only software released after the
public announcement of OWL 1 in 2004666According to https://www.w3.org/TR/owl-
features/ was considered.

####  4.1.2 Usable

An OWL reasoner (or system using a foreign OWL reasoner) is considered usable,
if it meets the following criteria:

  1. 1.

The OWL reasoner can be started successfully on Ubuntu 20.04 (64-bit, X11). Or
using PlayOnLinux777https://www.playonlinux.com/en/ \+
Wine888https://www.winehq.org/, if software requires a Windows environment. My
local machine hardware details are: IBM ThinkCentre with 8 GB RAM, Intel Core
i5-7400T and solid state disk.

  2. 2.

I did not test on my local machine if I did not know the development
environment of the software. Systems such as Haskell or Prolog require a
certain software stack, that can only be set up properly with prior knowledge.
This is also the case, if a project was only available as a Java API or
Protégé plugin. No custom code was written and executed to test the reasoner.
In all these cases I have instead examined project documentation and
projects/publications, that use a particular reasoner to determine, whether it
is usable or not.

In some cases it was not possible to clarify whether an OWL reasoner was
usable without any doubt. Relevant information has been added and its up to
the reader to conduct further analysis. This approach was taken to avoid
misunderstandings and false claims.

####  4.1.3 Actively maintained

Active maintenance is an important criteria for people looking for software
for a specific use case. However, it is difficult to objectively assess
whether a software is still being actively maintained or not. The following
aspects have been chosen because they are objective and rooted in software
engineering.

  1. 1.

An open source OWL reasoner is considered to be actively maintained, if the
last release/code commit is not older than 3 years or there are other
activities by the developers/maintainers, such as responses to bug reports in
the same time period.

  2. 2.

A closed source OWL reasoner is considered to be actively maintained, if the
developer has provided software at the time of the survey.

Why 3 years? In my experience open source projects can be inactive for 2-3
years, but still receive important updates from time to time. 3 years seemed
to be reasonable enough for this type of survey.

###  4.2 Literature- and Internet research

The OWL reasoner has its roots in the scientific community. Therefore
literature research was the starting point. I used Google
Schoolar999https://scholar.google.com/ to find relevant publications.
Initially, I searched for ”OWL Reasoner”, but refined my search by using
specific project names with the term reasoner to avoid ambiguous results. Only
publicly available publications were considered, which means that if a
publication was behind a paywall, it was ignored. A paywalled publication may
contain valuable information, but I found it unreasonable to pay 30 EUR or
more just to gain access.

An OWL reasoner was selected for further research, if there was a scientific
publication or technical report about it, or it had a dedicated project
repository. Small demos were ignored, because their usability in the long term
was questionable. Systems that provide reasoning services using a third-party
OWL reasoner were managed separately. They were included because they provide
a benefit to users for certain applications, such as selecting an appropriate
reasoner for a given ontology (meta reasoner).

All OWL reasoners were collected in a CSV file, supplemented by meta data such
as usability, maintenance status or project website. This list provided a
stable overview of available OWL reasoners and also helped to find relations
between some projects. At https://github.com/k00ni/owl-reasoner-list you can
get all raw data, such as the mentioned CSV file, which was created during
this analysis.

In addition to the literature search, a separate internet search was carried
out for each OWL reasoner using Google Search. Project websites, source code
repositories and other relevant information were of interest. One note: Some
projects were mentioned in an article and only have a project page, but there
was no dedicated article about them.

Github101010https://www.github.com is one of the main platforms for finding
open source projects111111https://www.linuxfoundation.org/blog/hosting-open-
source-projects-on-github-nine-things-you-need-to-know. Therefore a search
using reasoner name (and sometimes the term ”reasoner” too) was conducted. The
same applies for projects on other platforms such as Bitbucket or Sourceforge.

###  4.3 Software review and analysis

Each OWL reasoner was examined. First, executable binaries, if available, were
downloaded and tested on my local machine running Ubuntu 20.04. After
downloading a binary, I tried to find information about installation/setup.
Based on the available information and my personal knowledge the binary was
installed/setup and executed.

If the software started and showed a CLI or user interface the test was
complete. If a library (e.g. as Jar-
file121212https://en.wikipedia.org/wiki/Jar_(file_format)) was provided by the
project, I tried to determine usability by searching the project files and the
web. For example, if a library was provided and the project used a continuous
integration pipeline that did not report any errors during the last run, it
can be assumed that the library still works.

If no usable files could be found, no further investigation was conducted. No
custom code was developed to test a reasoner.

##  5 Results

The structure of this section is as follows. First, a short overview about the
most important statistical figures related to OWL reasoners (Table 1) and
systems using a foreign OWL reasoner (Table 2) is given.

This is followed by a list of available OWL reasoners. Each block consists of
a summary, download and repository part as well as an installation and usage
part. This is followed by a list of systems which use a foreign OWL reasoner.
Finally, a list of (probably) unusable OWL reasoners is given. Table 3 in the
appendix shows a list of all usable and maintained reasoners. Table 4 contains
a list of all analyzed OWL reasoners. A more detailed overview can be found in
the mentioned Github repository (look for the files: ”reasoner.csv” and
”system-using-foreign-reasoner.csv”).

The amount of … |
---|---
… usable and maintained OWL reasoners is | 25
… usable OWL reasoners (maintenance ignored) is | 32
… maintained OWL reasoners (usability ignored) is | 28
… OWL reasoners that weren’t tried is | 9
… OWL reasoners with no available files is | 20
Table 1: Overview of figures for a total of 73 analyzed OWL reasoners  The amount of systems using a foreign OWL reasoner that … |
---|---
… are usable and maintained is | 4
… are usable (maintenance ignored) is | 8
… are maintained (usability ignored) is | 5
… weren’t tried is | 4
… are have no available files is | 9
Table 2: Overview of figures for a total of 22 analyzed systems using a
foreign OWL reasoner

###  5.1 Usable OWL Reasoners

Below is a list of all usable OWL reasoners.

####  5.1.1 AllegroGraph

Summary: AllegroGraph131313https://allegrograph.com/products/allegrograph/ is
an RDF graph database which provides data storage and other services. One of
these is an RDFS++ reasoner, which supports all RDFS predicates and also some
OWL
predicates.141414https://franz.com/agraph/support/documentation/current/agraph-
introduction.html#reasoning-intro. Source code is not available. The most
relevant publication is from Diogo Fernandes and Jorge Bernardino [18]. The
company behind AllegroGraph has published many white papers about this
reasoner, but no information was found about their RDFS++
Reasoner151515https://allegrograph.com/white-papers/.

Download and Repository: AllegroGraph can be in version 7.3.1 downloaded for
different Linux systems (Ubuntu,
RHEL,…)161616https://franz.com/agraph/downloads/. You can also use a Docker
container to run it. There was no binary available for Windows. The
AllegroGraph client source code is available on Github in several
languages171717https://github.com/franzinc?tab=repositories.

Installation and Usage: Installation introductions are available on the
download page. Usage information can be found at the following
link181818https://franz.com/agraph/support/documentation/current/reasoner-
tutorial.html.

####  5.1.2 Arachne

Summary: Arachne [4] is an RDF rule engine written in Scala with support for
efficient reasoning over large OWL RL terminologies. It implements the Rete/UL
algorithm of Robert B. Doorenbos [15].

Download and Repository: The source code is available on
Github191919https://github.com/balhoff/arachne. Latest release 1.2.1 and is
from January 14, 2020. The release file contains a couple of Jar files as well
as a bat-file for Windows and a binary for Linux systems.

Installation and Usage: Initially there was little information available about
installation and usage. I created an issue to ask for help and get more
information202020https://github.com/balhoff/arachne/issues/146. The author
responded very quickly and added sufficient information in the usage section
of the README file. There is also a Protégé plugin
available212121https://github.com/balhoff/arachne-protege, but it seems to be
still unstable222222https://github.com/balhoff/arachne/issues/5.

####  5.1.3 BaseVISor

Summary: BaseVISor [38] is a forward-chaining inference machine written in
Java and optimized for ontological and rule-based reasoning.

Download and Repository: BaseVISor can be downloaded from the following
project page232323https://vistology.com/products/basevisor/. The current
license allows use free-of-charge for academic purposes only. For all other
purposes a commercial license is to be acquired. To start the download you
need to enter your name and email. You will receive a license key later on,
which is required to use the software.

Installation and Usage: The tested version was 2.0.2 and was downloaded as ZIP
archive. The archive contains some script and jar files as well as API
documentation and usage information. To see if it is usable, execute
test_drive.bat (Windows) or test_drive.sh (Linux) in the terminal (requires
Java 1.5). A local test showed that BaseVISor is usable on Ubuntu 20.04, using
OpenJDK 11.0.8.

####  5.1.4 BORN

Summary: BORN [11] is a Bayesian ontology reasoner and written in Java.
Bayesian ontology language is a family of probabilistic ontology languages
that allow modelling of probabilistic information about axioms in an ontology.
BORN is able to work with the Bayesian ontology language BEL.

Download and Repository: The source code of BORN is available on
Github242424https://github.com/julianmendez/born. It is provided as stand-
alone software and Protégé plugin. Version 0.3.0 has been reviewed and was
released in April
2017252525https://sourceforge.net/projects/latitude/files/born/0.3.0/born-0.3.0.zip/download.
There are development activities from time to time. Latest commit was January
2022262626https://github.com/julianmendez/born/commit/028bdf00f25594d9f1edb22ce91119d3093386b3.

Installation and Usage: The Protégé plugin must be installed
manually272727https://github.com/julianmendez/born#usage. To use the
standalone version, execute born.jar in the terminal. The file is located in
born-standalone/target directory (see zip archive). Further usage information
can be found in the Github repository as well as on a separate project
page282828https://julianmendez.github.io/born/.

####  5.1.5 CEL

Summary: CEL [42] is a lightweight Description Logic reasoner for large-scale
biomedical ontologies in OWL 2 EL. It is written in Java and its source code
is released as open source.

Download and Repository: The latest version 0.6.0 can be downloaded from
Sourceforge292929https://sourceforge.net/projects/latitude/files/cel/ and
Github303030https://github.com/julianmendez/cel. There is also a Protégé
plugin available, which can be downloaded from
Sourceforge313131https://sourceforge.net/projects/latitude/files/cel/0.6.0/de.tu-
dresden.inf.lat.cel.Jar-0.6.0.zip/download. There are sporadic development
activities in the Github repository, latest commit was in January
2022323232https://github.com/julianmendez/cel/commit/36b3e62bd26278d79874d0fe7ee49a6f70ff2bcc.

Installation and Usage: CEL has been developed to run only on 32-bit Linux
systems according to the
documentation333333https://github.com/julianmendez/cel#downloading-cel, but
the source code can be compiled for other systems if needed. There is a short
usage section in the README
file343434https://github.com/julianmendez/cel#using-cel. A manual with further
information is available on
Sourceforge353535https://sourceforge.net/projects/latitude/files/cel/cel/cel-
manual.pdf. There is also a Protégé plugin available.

####  5.1.6 Clipper

Summary: Clipper is a conjunctive query rewriting/answering engine for Horn-
SHIQ ontologies. There was no primary publication available, but it is
mentioned in a few publications, such as [9] and [67].

Download and Repository: It is written in Java and the source code can be
found on Github363636https://github.com/ghxiao/clipper. Further information
can be found in the repository, but most of it is
outdated373737http://www.kr.tuwien.ac.at/research/systems/clipper/download.html.

Installation and Usage: The Maven build was tested successfully and Clipper
CLI was shown on the terminal. No further test has been conducted. Some usage
information can be found in the README
file383838https://github.com/ghxiao/clipper#usage-from-cli. Be aware that a
program called DLV seems to be required, but its project page is not longer
accessible393939http://www.dlvsystem.com/dlvsystem/index.php/DLV.

####  5.1.7 ElepHant

Summary: ElepHant [65] is a consequence-based reasoner prototype for EL+
fragment of Description Logics. It is the successor of the previously
developed reasoner called CHEETAH [66]. The motivation behind the development
of ElepHant was to improve performance and to allow usage on embedded systems
with limited memory and CPUs.

Download and Repository: It is written in C and the source code can be found
on Github404040https://github.com/sertkaya/elephant-reasoner. A binary for
64-bit Linux systems is available for download there and needs to be executed
on the terminal to show a CLI. Latest commit was in 2021, but since the latest
release (0.5.9) not much has
changed414141https://github.com/sertkaya/elephant-
reasoner/compare/v.0.5.9…master. It seems project receives a few updates from
time to time, but is not developed any further.

Installation and Usage: The binary424242https://github.com/sertkaya/elephant-
reasoner/releases/tag/v.0.5.9 has been tested successfully on Ubuntu Linux
20.04. Some usage information are available in the README
file434343https://github.com/sertkaya/elephant-reasoner/blob/master/README.

####  5.1.8 ELK

Summary: ELK [27] is an OWL 2 EL reasoner and written in Java. OWL 2 EL is a
subset of OWL 2 that recommended when defining a large amount of
classes/properties. According to the developers, ELK provides better
performance compared to other reasoners, because it utilizes parallelization.

Download and Repository: The documentation of ELK is very extensive compared
to other reasoner projects. See the project wiki on Github for installation
and usage information444444https://github.com/liveontologies/elk-
reasoner/wiki. ELK version 0.4.3454545https://github.com/liveontologies/elk-
reasoner/releases can be downloaded as binary or pure source code. Version
0.5.0 is available as a Protégé
plugin464646https://oss.sonatype.org/service/local/artifact/maven/content?r=snapshots&g=org.semanticweb.elk&a=elk-
distribution-protege&e=zip&v=LATEST.

Installation and Usage: The Protégé plugin is one of the reasoners provided
with Protégé per default. In Protégé 5.6.1 you can test ELK in version 0.4.3
and 0.5.0. ELK can also be used via the OWL API and through a command line
client474747https://github.com/liveontologies/elk-
reasoner/wiki/GettingElk#obtaining-elk. Each package appears to provide
different functionality.

####  5.1.9 Expressive Reasoning Graph Store

Summary: ERGS stands for ”Expressive Reasoning Graph Store”[50] and is a graph
store, based on JanusGraph484848https://janusgraph.org/. The project is only 3
years old and the system supports RDFS reasoning and some OWL constructs. It
is written in Java.

Download and Repository: Source code is available on
Github494949https://github.com/IBM/expressive-reasoning-graph-store, but there
are no binaries available for download. However, the repository contains a
file called ”Docker-compose.yml”, which can be used to create a Docker setup
to run ERGS.

Installation and Usage: Information about Maven builds or how to create an
ERGS repository can be found in the repository. The ”docker-compose.yml”
mentioned above can also be used to build a web application that provides
access to ERGS505050https://github.com/IBM/expressive-reasoning-graph-
store#Docker-build.

####  5.1.10 EYE and EYE JS

Summary: EYE [91, 13] is a reasoner that allows forward and backward chaining
along Euler paths. It is written in Prolog, therefore it needs a Prolog
Virtual machine to run, using an Euler Abstract Machine as a core. This core
is compatible with two of the most widely used Prolog engines called YAP and
SWI-Prolog. The advantages of this approach is high portability. EYE has a
sister project with the name ”EYE JS”, which aims to provide the EYE reasoner
in the browser by using Webassembly515151https://github.com/eyereasoner/eye-
js.

Download and Repository: There is an outdated website for EYE
available525252https://eulersharp.sourceforge.net/, but it is superseded by
another website hosted on Github535353https://eyereasoner.github.io/eye/. The
source code is available on the Github
repository545454https://github.com/eyereasoner/eye. The latest version
downloadable version is 3.24.1. The developers are very active. At the time of
checking the repository, the latest commit was a few minutes old.

Installation and Usage: See https://n3.restdesc.org/ for information about
Semantic Web Reasoning with N3. It uses an EYE variant that is accessible via
a browser. EYE also runs on your local machine. Some information about setup
and usage can be found in the README
file555555https://github.com/eyereasoner/eye#installation. There are usage
examples available, have a look at the ”documentation” folder565656Eye command
line arguments and flags:
https://github.com/eyereasoner/eye/blob/master/documentation/command_line.md.

####  5.1.11 FaCT++

Summary: FaCT++[85] is the successor to the FaCT (Fast Classification of
Terminologies) reasoner. It implements a tableaux decision procedure for the
well known SHOIQ Description Logic, with additional support for data types,
including strings and integers according to the developers [85].

Download and Repository: The latest version 1.6.5 is available for download
from the Bitbucket
repository575757https://bitbucket.org/dtsarkov/factplusplus/downloads/. The
last commit was in December
2017585858https://bitbucket.org/dtsarkov/factplusplus/commits/650a50ce78a2f9c7fd609a2ee82b72b6e25f34ee.

Installation and Usage: FaCT++ is part of the standard Protégé 5.6.1
installation, but is also available for
download595959https://bitbucket.org/dtsarkov/factplusplus/downloads/uk.ac.manchester.cs.owl.factplusplus-P5.x-v1.6.5.Jar.
In some cases the plugin installation fails on Windows, but there is a
workaround available606060https://github.com/emmo-
repo/EMMO/blob/7a4b825e310c5362f4c407b5c38192eb3013e37f/doc/installing_factplusplus.md.
It is considered usable, because of its availability in latest Protégé 5.6.1
and it is used successfully in [30].

####  5.1.12 fuzzyDL

Summary: fuzzyDL [8] is a Description Logic reasoner with support for fuzzy
logic and fuzzy rough set reasoning. A quote from the project page: ”It
provides a reasoner for fuzzy SHIF with concrete fuzzy concepts (ALC extended
with transitive roles, a role hierarchy, inverse, reflexive, symmetric roles,
functional roles, and explicit definition of fuzzy sets)”616161Source:
https://www.umbertostraccia.it/cs/software/fuzzyDL/fuzzyDL.html. Although, it
uses a reasoner, it seems that the system itself is a reasoner.

Download and Repository: There was no source code repository available, but
there are two websites with further information. The main page contains
information about the software itself, but also links to downloads, latest
changes
etc626262https://www.umbertostraccia.it/cs/software/fuzzyDL/fuzzyDL.html. The
other website provides information about the Protégé
plugin636363https://www.umbertostraccia.it/cs/software/FuzzyOWL/index.html.
Currently version 2.3 is available for download (January 9, 2019).

Installation and Usage: The plugin is only available for the outdated Protégé
4.3646464https://www.umbertostraccia.it/cs/software/fuzzyDL/download.html. Use
the standard procedure to install the plugin. No further installation or usage
information could be found. I tried to test the plugin using Protégé 4.3, but
Protégé didn’t start properly656565Running ”./run.sh” in the terminal showed
the following errors: org.protege.common.jar
(org.osgi.framework.BundleException: Unresolved constraint in bundle
org.protege.common [1]:
Unable to resolve 1.0: missing requirement [1.0] osgi.wiring.package;
(&(osgi.wiring.package=org.w3c.dom)(version¿=0.0.0)))
org.osgi.framework.BundleException:
Unresolved constraint in bundle org.protege.common [1]:
Unable to resolve 1.0: missing requirement [1.0] osgi.wiring.package;
(&(osgi.wiring.package=org.w3c.dom)(version¿=0.0.0)) […].

####  5.1.13 HermiT

Summary: HermiT [20] is an OWL 2 reasoner, written in Java. It uses
hypertableu calculus and provides support for entailment checking and also
reasoning services such as class and property classification or answering
SPARQL queries.

Download and Repository: The former project website is no longer
available666666http://www.hermit-reasoner.com/. Several repositories were
found on Github, but it seems that https://github.com/phillord/hermit-reasoner
contains the source code of the latest version (1.3.8). Latest commit is over
6 years old676767https://github.com/phillord/hermit-
reasoner/commit/37ec30aced32ac81ebecc5e33fad255ddefcb4c3. Repository has been
abandoned686868https://github.com/phillord/hermit-
reasoner/pull/3#issuecomment-1639673663. There are other forks, but they seen
to contain few, if any adaptions. There was no binary available on Github, but
https://Jar-download.com/?search_box=HermiT provides an unofficial one. HermiT
is also available as a Protégé
plugin696969https://protegewiki.stanford.edu/wiki/HermiT.

Installation and Usage: HermiT 1.4.3.456 is part of the standard Protégé 5.6.1
package. Interesting observation, the Protégé plugin website only contains
information for version 1.3.8 and
earlier707070https://protegewiki.stanford.edu/wiki/HermiT. No installation or
usage documentation was available. HermiT is considered usable, because its
available in the latest Protégé 5.6.1 and it is used successfully in [30].

####  5.1.14 jcel

Summary: jcel [41] is a Description Logic EL+ reasoner hat implements a subset
of OWL 2 EL. It is written in Java and uses a rule-based completion algorithm
internally. It can be used as a Java library or as a Protégé plugin. Julian
Mendez developed jcel, but was also part of the BORN reasoner development
team.

Download and Repository: The source code is available on
Github717171https://github.com/julianmendez/jcel. A zip archive containing the
relevant files is available for download on
Sourceforge727272https://sourceforge.net/projects/jcel/files/jcel/0.24.1/zip/jcel-0.24.1.zip/download.
The Protégé plugin can be downloaded from the Github
repository737373https://github.com/julianmendez/jcel/releases. The latest
version 0.24.1 was in 2016, but latest commit was in
2022747474https://github.com/julianmendez/jcel/commit/cdfb5f77312f84a6b81531d7be9974783756ff12.

Installation and Usage: The jcel plugin is part of the standard Protégé 5.6.1
package. There is no dedicated page for the plugin. It is also available as a
Java library, but it has to be built with Maven before it can be used. Good
documentation is available757575https://github.com/julianmendez/jcel#source-
code. The library was built locally and running ”jcel-
standalone/target/jcel.Jar” in the terminal produced a CLI.

####  5.1.15 JFact

Summary: JFact767676https://jfact.sourceforge.net/ is a Java port of FaCT++,
an OWL DL reasoner for OWL API 3.x and 4.x. There is no dedicated publication
for JFact available, but it is at least mentioned in [47].

Download and Repository: The project website contains some information and
also points to a Github repository777777https://github.com/owlcs/jfact. On
Sourceforge several versions (Jar file and Protégé plugin) until version 4.0.0
are available for download787878https://sourceforge.net/projects/jfact/files/.
On Github the source code until version 4.0.2 is available to
download797979https://github.com/owlcs/jfact/tags.

Installation and Usage: Protégé plugin 4.0.4 has been reported to work at
least partially with Protégé
5.2808080https://github.com/owlcs/jfact/issues/18. It is not clear if these
problems have been. JFact seems to work with (obsolete) Protégé 4.x just fine.
JFact can also be used in a Java project.

####  5.1.16 KAON2

Summary: KAON2[46] provides reasoning (e.g. satisfiability decision,
subsumption hierarchy computation) for SHIQ knowledge bases. It is free of
charge for academic purposes only, otherwise a commercial license is required.
Ontoprise GmbH, the company behind the software, filed for bankruptcy in
2012818181https://en.wikipedia.org/wiki/Ontoprise_GmbH.

Download and Repository: The project website provides extensive information
about KAON2828282http://kaon2.semanticweb.org/. The latest downloadable
version is from
2008838383http://kaon2.semanticweb.org/release/kaon2-bin-2008-06-29.zip.
According to the feedback from Boris Motik (via email), the project is no
longer being developed.

Installation and Usage: KAON2 was developed for Java 1.5, which was released
in 2004, but it can still be run on Ubuntu 20.04 using OpenJDK 11. Executing
the jar file in the terminal produces a user interface. No further testing has
been done.

####  5.1.17 Konclude

Summary: Konklude [77] is a SROIQV(D) Description Logic reasoner. According to
the authors it is optimized for high throughput. It is written in C++ and uses
the Qt framework848484https://contribute.qt-project.org/.

Download and Repository: The source code is publicly available and can be
downloaded from the project
website858585https://www.derivo.de/en/products/konclude/download/ and on
Github868686https://github.com/konclude/Konclude/releases. The latest version
0.7.0 is from 2021, so the project is considered actively maintained.

Installation and Usage: There are binaries for Windows, Linux and Mac OS
systems that can be used without installation. A Docker container setup is
also available. A local test has been conducted using the Linux
binary878787Konclude-v0.7.0-1138-Linux-x64-GCC-Static-Qt5.12.10.zip. To run
it, the archive was extracted and the file ”Konklude.sh” executed on the
terminal. It spawns a CLI with further usage information. Further usage
information can be found in the README
file888888https://github.com/konclude/Konclude/tree/master#usage.

####  5.1.18 LiFR

Summary: LiFR [88] stands for ”Lighweight Fuzzy semantic Reasoner” and is a
fuzzy Description Logic reasoner written in Java. It is an extension of the
Pocket KRHyper reasoner. They have extended the Description Logic interface to
support additional semantics and the transformation of fuzzy operators into
the native first-order clause implementation898989https://github.com/lifr-
reasoner/lifr#description. The software provides inference services such as
consistency checking and fuzzy entailment.

Download and Repository: The source code is available on
Github909090https://github.com/lifr-reasoner/lifr. There are currently no
binaries available. Based on the feedback from Dorothea Tsatsou (project
owner) the repository is monitored for new issues and is still maintained.
Latest commit was in 2023.

Installation and Usage: An issue was created to ask for help, because the
documentation provided was insufficient919191https://github.com/lifr-
reasoner/lifr/issues/2. Dorothea Tsatsou replied very quickly and provided
helpful answers. LiFR can only be used in a Java project, there is no binary
or Jar file available. Later on she added further information, such as in the
usage section929292https://github.com/lifr-reasoner/lifr#usage. LiFR is
considered usable based on the provided information in the Github repository.

####  5.1.19 LiRoT

Summary: LiRoT [6] is a reasoner that provides reasoning for a subset of OWL 2
RL and RDF-S entailment list. It is written in C and uses the RETE algorithm.
It has been optimized to use limited memory and CPUs more efficiently, making
it suitable for embedded systems, such as Arduino boards. The project is just
over one year old (started in 2022), which is very young in comparison to
other reasoners.

Download and Repository: Source code is available under the terms of the
CeCILL-C
license939393http://www.cecill.info/licences/Licence_CeCILL_V2.1-en.html on a
Gitlab repository949494https://gitlab.com/coswot/lirot. No binaries were
found.

Installation and Usage: To use, first check out the Git repository and then
start compiling. Afterwards, LiRot can be used inside a C project. A demo is
also provided, which was successfully run on Ubuntu 20.04. See the README file
for further usage information959595https://gitlab.com/coswot/lirot#how-to-use-
lirot-as-a-library. LiRot runs on Linux and Arduino systems, according to the
documentation.

####  5.1.20 NORA

NORA is a scalable OWL Reasoner, which is based on NoSQL databases and Apache
Spark, according to the developer969696https://github.com/benhid/nora. No
publications could be found, however the following reasons speak for a
mention: First of all, it is very young, the latest commit is from January 9,
2023979797https://github.com/benhid/nora/commit/8d591656cb38068422fd0889d6fb8d7ca4835f9f.
A cursory look at the source code leads me to believe that it provides a
relevant OWL reasoner. Also, the developer works at University
Málaga989898https://itis.uma.es/en/personal/antonio-benitez-hidalgo-2/ and
researches Knowledge Graphs, large-scale data processing and Big Data
management. No own local testing was conducted, as a working Apache Spark
cluster is required, which in turn depends on a specific use case and data.

####  5.1.21 Ontop and Quest

Summary: Quest [61] is a reasoner and part of the Ontop999999https://ontop-
vkg.org/ framework, an ontology-based data access (OBDA) system. OBDA
basically means that data is often read from a legacy data source, such as an
RDBMS and linked to a vocabulary from an ontology. This allows virtual
knowledge graphs to be created. According to the developers, Quest supports
SPARQL query answering for OWL 2 QL and RDFS entailment regimes [62]. Behind
the scenes, SPARQL queries are converted to highly optimized SQL queries and
executed in an RDBMS.

Download and Repository: Ontop is written in Java and the source code is
available on Github100100100https://github.com/ontop/ontop. The latest version
of Ontop is 5.0.2 and can be downloaded from the Github repository and other
sources101101101https://ontop-vkg.org/guide/getting-started.html. The project
is actively as the latest commit was 17 hours ago, last time I checked (June
2023).

Installation and Usage: Ontop has extensive documentation at https://ontop-
vkg.org/guide. There is a Protégé plugin available, but it has to be installed
manually. Also, Ontop can be used via a CLI102102102https://ontop-
vkg.org/guide/cli.html and SPARQL endpoint103103103https://ontop-
vkg.org/tutorial/endpoint/. The file ”ontop-cli-5.1.0-SNAPSHOT.zip” has been
downloaded and extracted to test Ontop. Running the file ”./ontop” in the
terminal produced a CLI with further information.

####  5.1.22 Openllet

Summary: Openllet is an OWL 2 reasoner and built on top of Pellet. It is
written in Java and provides functionality to check the consistency of
ontologies, compute the classification hierarchy, explain inferences, and
answer SPARQL queries104104104https://github.com/Galigator/openllet#openllet-
is-an-owl-2-dl-reasoner. No specific publications about Openlett could be
found, but it is mentioned in [69].

Download and Repository: Openllet is open source and its source code as well
as pre-generated Jar files can be downloaded from
Github105105105https://github.com/Galigator/openllet. The latest version 2.6.5
is from September 27,
2019106106106https://github.com/Galigator/openllet/releases. The project is
considered maintained as it receives updates from time to time (latest commit
was in May
2023107107107https://github.com/Galigator/openllet/commit/3abccbfc0eec54233590cd4149055b78351e374d).

Installation and Usage: Openllet can be used via a Jar file in your own Java
project. Examples are available in the
repository108108108https://github.com/Galigator/openllet/tree/integration/examples/src/main/java/openllet/examples.
There seems to be a Protégé plugin based on various
sources109109109https://mvnrepository.com/artifact/com.github.galigator.openllet/openllet-
protege and https://Jar-
download.com/artifacts/com.github.galigator.openllet/openllet-protege/2.6.5,
but a usable plugin could not be found.

####  5.1.23 OWL-RL

Summary: OWL-RL is a reasoner, written in Python, for the OWL 2 RL
profile110110110https://www.w3.org/TR/owl2-profiles/#Reasoning_in_OWL_2_RL_and_RDF_Graphs_using_Rules.
It is based on RDFLib111111111https://github.com/RDFLib/rdflib, an RDF library
that provides tools and services for working with RDF data (Parser, SPARQL and
store implementations).

Download and Repository: The project repository is on
Github112112112https://github.com/RDFLib/OWL-RL. The latest version 5.2.3
(from September 13, 2021) can be downloaded there.

Installation and Usage: No local testing has been done, as you need to include
the library in your own Python project. The README file contains some usage
information113113113https://github.com/RDFLib/OWL-RL/blob/master/README.rst,
but overall documentation is very scarce114114114https://owl-
rl.readthedocs.io/en/latest/installation.html. However, the project is
considered usable and maintained as the latest commit is only 2 years old and
its developers are very active in other RDF projects. Therefore future
refinements and developments are very likely.

####  5.1.24 Pellet

Summary: Pellet [56] is an OWL 2 DL reasoner and, according to the authors,
was the first sound and complete OWL 2 DL reasoner with extensive support for
reasoning with individuals, user-defined data types, and debugging support for
ontologies [72]. It is written in Java and its source code is publicly
available.

Download and Repository: It official website was difficult to find. In
publications [56] and [72] the website http://www.mindswap.org/2003/pellet/ is
mentioned, but it is not available anymore. There are a few repositories on
Github which claim to provide the source code of Pellet. The repository
https://github.com/severin-lemaignan/pellet seems to contain the original
source code. Another repository is maintained by Stardog
Union115115115https://github.com/stardog-union and it contains a more recent
version (v2). In the projects README file there is a note about a version 3 of
Pellet116116116https://github.com/stardog-union/pellet/blob/master/README.md
which is no longer open source. Both repositories are considered not
maintained anymore. In ”severin-lemaignan/pellet” the latest commit was
2011117117117https://github.com/severin-
lemaignan/pellet/commit/7710fb0f258c081d5dfe8f8af0f829e1a73d2250 while in
”stardog-union/pellet” the latest commit was
2017118118118https://github.com/stardog-
union/pellet/commit/4c7d16bd1811ec04117fa4cd96ed592c6cfa956b. There are 5 open
pull requests119119119A pull request is a contribution by the community, e.g.
a patch with no comments120120120https://github.com/stardog-
union/pellet/pulls.

Installation and Usage: The Pellet plugin is part of the standard Protégé
5.6.1 package and is still usable. It can be used via a Jar file within a
custom Java project. A local test of the CLI failed, because running
”pellet.sh” on Ubuntu 20.04 aborted due to compilation errors121121121In the
following a snippet of the long error message: WARNING: An illegal reflective
access operation has occurred
WARNING: Illegal reflective access by
com.google.inject.internal.cglib.core.$ReflectUtils$1
(file:/usr/share/maven/lib/guice.jar) to method
java.lang.ClassLoader.defineClass([…])
WARNING: Please consider reporting this to the maintainers of
com.google.inject.internal.cglib.core.$ReflectUtils$1
WARNING: Use –illegal-access=warn to enable warnings of further illegal
reflective access operations
WARNING: All illegal access operations will be denied in a future release
[ERROR] COMPILATION ERROR : package javax.xml.bind does not exist […].

####  5.1.25 RDFox

Summary: RDFox [51] is an RDF store with support for materialisation-based
parallel Datalog reasoning (OWL 2 RL), SWRL reasoning and SPARQL query
answering. According to the developers, it can efficiently process billions of
triples. They provide a detailed overview of the reasoning
capabilities122122122https://docs.oxfordsemantic.tech/reasoning.html. A
license key is required to use the system. Information about conditions or
prices could not be found.

Download and Repository: RDFox can be downloaded for Windows, Linux and Mac OS
from https://www.oxfordsemantic.tech/downloads. To receive the required
license key submit the form from
https://www.oxfordsemantic.tech/tryrdfoxforfree. I received a 30-day
evaluation key by email. A repository containing the source could not be
found.

Installation and Usage: RDFox 6.2 was downloaded and extracted as a ZIP
archive. It contains a file that spawns a CLI when executed in a terminal. To
test its usability I followed the steps in the ”Getting Started” section of
the documentation123123123https://docs.oxfordsemantic.tech/getting-
started.html#getting-started. After starting the store, sample data was
uploaded and a test query was successfully submitted. In comparison to other
reasoners, RDFox is one of the easiest to setup and use.

####  5.1.26 RDFSharp.Semantics

Summary: RDFSharp.Semantics is an API and provides a SWRL-Reasoner with
forward-chaining inference capabilities. It is an extension of the RDFSharp-
API124124124https://github.com/mdesalvo/RDFSharp, which provides functions to
work with RDF data in general.

Download and Repository: It is written in
C#125125125https://en.wikipedia.org/wiki/C_Sharp_(programming_language) and
available as open source on
Github126126126https://github.com/mdesalvo/RDFSharp.Semantics. The latest
version 3.5.0 can be downloaded from Github and
nuget127127127https://www.nuget.org/packages/RDFSharp.Semantics.

Installation and Usage: RDFSharp.Semantics can only be used inside a custom
.NET project. There is a guide with more information about installation and
usage128128128See PDF file in latest release at the bottom, for instance:
https://github.com/mdesalvo/RDFSharp.Semantics/releases/tag/v3.5.0. I have not
conducted any further testing due to lack of knowledge of .NET. However, based
on the development on Github and recent commits (from 2023) the project is
considered usable and maintained.

####  5.1.27 reasonable

Summary: reasonable is an OWL 2 RL reasoner, written in Rust and available as
open source on Github129129129https://github.com/gtfierro/reasonable.
According to the developers, it is much faster than the OWLRL and Allegro
reasoners130130130https://github.com/gtfierro/reasonable#performance. There is
a section about supported OWL 2 rules in the README
file131131131https://github.com/gtfierro/reasonable#owl-2-rules.

Download and Repository: The reasoner can be installed using Cargo (Rust) or
pip (Python). Docker containers are also
available132132132https://github.com/gtfierro?tab=packages&repo_name=reasonable.
The developer is very active and responds promptly to issues. Besides, a
static build is also available 133133133Use file ”reasonable-static ” from
https://github.com/gtfierro/reasonable/releases/tag/nightly.

Installation and Usage: Use Cargo or pip to install the
reasoner134134134https://docs.rs/reasonable/latest/reasonable/ on a local
machine. See the README file for more information on Python
Bindings135135135https://github.com/gtfierro/reasonable#python. At first,
running the binary gave errors, so I created an issue to tell the developer
about it136136136https://github.com/gtfierro/reasonable/issues/24. He was very
helpful and provided a fixed static build binary that ran successfully in the
terminal (show a CLI).

####  5.1.28 Sequoia

Summary: Sequoia [5] is an OWL 2 DL reasoner, written in Scala and released
under the terms of the GPL 3. A Scala environment is required to run Sequoia.

Download and Repository: The project repository is available on
Github137137137https://github.com/andrewdbate/Sequoia. The documentation is
very sparse and it seems that the whole repository has to be downloaded before
any of the Sequoia parts can be used.

Installation and Usage: I have not conducted ay tests due to my lack of
knowledge of Scala. It seems to be maintained and usable as the latest commit
was in 2020 and there are no issues in the bug tracker that indicate
installation or usage problems. An issue has been opened to ask the developers
to provide help with installation and a small usage example, but no response
yet138138138https://github.com/andrewdbate/Sequoia/issues/3.

####  5.1.29 TRILL, TRILLP, TORNADO

Summary: TRILL [98] is a Description Logics reasoner, written in Prolog. It
supports query answering for SHOIN (D) knowledge bases. $TRILL^{P}$ and
TORNADO are based on the source code of TRILL, but are not of interest.

Download and Repository: The source code can be found on
Github139139139https://github.com/rzese/trill. The latest version 6.0.5 is
from November 2022 and can be downloaded there. It is also possible to use a
web based SWI-Prolog environment, which is provided by the linked Docker
image140140140https://github.com/friguzzi/trill-on-swish.

Installation and Usage: TRILL is a SWI-Prolog pack and therefore requires SWI-
Prolog141141141https://www.swi-prolog.org/ to run. There is also a way to try
out TRILL in a browser by using SWISH142142142https://trill-sw.eu/p/thrt.pl.
The team provides a PDF manual for TRILL on
Github143143143https://github.com/rzese/trill/tree/master/doc.

####  5.1.30 Vampire

Summary: Vampire [87, 29] is a theorem prover written in C++, but also
supports OWL DL reasoning.

Download and Repository: The source code is available on
Github144144144https://github.com/vprover/vampire. Latest version 4.7 is dated
August 2022 and is available as Linux
binary145145145https://github.com/vprover/vampire/releases. To use it on non-
Linux system, the source code has to be compiled
manually146146146https://vprover.github.io/download.html.

Installation and Usage: The downloaded Linux binary was ready to use. The
following page summarizes first steps of
use147147147https://vprover.github.io/usage.html.

####  5.1.31 VLog

Summary: VLog [10] is a Datalog-engine and rule-based reasoner (e.g. with
existential rules). It is resource-saving and can handle multiple data
sources, according to the
developers148148148https://github.com/karmaresearch/vlog/wiki.

Download and Repository: The source code and extensive documentation are
available on Github149149149https://github.com/karmaresearch/vlog. The latest
version 1.3.7 (from December 2022) can be downloaded
there150150150https://github.com/karmaresearch/vlog/releases.

Installation and Usage: One way to run VLog is to compile it yourself or to
use the Docker container151151151https://github.com/karmaresearch/vlog#Docker.
I had to install some packages (cmake, g++, zlib1g-dev) before the compilation
worked. After compiling, the file ”build/vlog” was available. After executing
it in a terminal, it showed a basic CLI. The wiki contains more information,
such as usage
examples152152152https://github.com/karmaresearch/vlog/wiki/Usage.

####  5.1.32 Whelk

Summary: Whelk is an ELK-based reasoner, but written in Scala. It provides a
Scala API and interface for OWL API. There is an integration with
OBO153153153Open Biomedical Ontologies tool Robot
available154154154https://robot.obolibrary.org/reason as well as a Protégé
plugin155155155https://github.com/balhoff/whelk/releases/tag/v1.1.1.

Download and Repository: The project repository is located on
Github156156156https://github.com/balhoff/whelk. The latest version 1.1.2 is
from November 2022 and can be downloaded
there157157157https://github.com/balhoff/whelk/releases. The developer notes,
that API changes are likely because the project is still under heavy
development.

Installation and Usage: An issue was created due to problems with installation
and first
steps158158158https://github.com/balhoff/whelk/issues/217#issuecomment-1609670170.
The developer responded quickly and provided a detailed answer. The reasoner
can also be tried in a browser on the website https://balhoff.github.io/whelk-
web/. Provided example was tested successfully.

###  5.2 Systems using a third-party reasoner

In the following is a list of all systems, which use a foreign standalone
reasoner. During the research it was not always clear whether a system was a
standalone reasoner or not. This distinction is important to some extent,
because one might want to find out capabilities/functionality of a reasoner,
for instance. They are also listed separately to support future research. Only
a few systems have been tested in detail.

####  5.2.1 AberOWL

AberOWL [74] is a framework for ontology-based access to biological data. It
consists of an ontology repository and some web services for reasoning. It
provides OWL 2 EL reasoning using the ELK reasoner. The project site is
http://aber-owl.net/.

####  5.2.2 BUNDLE

BUNDLE [60] is written in Java and provides reasoning for probabilistic
ontologies using the FaCT++ reasoner (and others). It uses the
DISPONTE159159159https://ml.unife.it/disponte/ approach, i.e. each axiom is
accompanied by a probability number (e.g. 0.6). This number represents the
probability that a certain axiom is considered true (epistemic probability).
The project page https://ml.unife.it/bundle/ contains numerous downloads as
well as documentation. The latest commits were made in 2023. BUNDLE can be
tried out in the browser. The following website contains pre-built examples
https://bundle.ml.unife.it/examples. The Bitbucket repository provides
information on getting started and
usage160160160https://bitbucket.org/machinelearningunife/bundle/src/master/README.md
and
https://bitbucket.org/machinelearningunife/bundle/wiki/BUNDLE%203.0.x.

####  5.2.3 Chainsaw

Chainsaw [86] is a meta reasoner that uses third-party reasoners such as ELK
for a given reasoning task. It was designed to handle large ontologies.
Internally, it uses the following approach: for each reasoning query it
generates a module of the ontology and select the most appropriate reasoner to
process it. They have a Bitbucket
repository161161161https://bitbucket.org/ignazio1977/chainsaw/src/master/,
which contains the source code. The latest commit is from 2022. Downloads can
be found on Sourceforge162162162https://sourceforge.net/projects/chainsaw/.

####  5.2.4 ComR

ComR [92] is a reasoner prototype to demonstrate an approach for faster
ontology classification. According to the authors, the time savings are up to
90% compared to similar reasoners such as HermiT, FaCT++ or Pellet. To achieve
this they combine an OWL 2 EL reasoner with an OWL 2 reasoner for ontology
classification in SROIQ. The non-EL-part is done by a slower OWL 2 reasoner. A
project repository or website could not be found, so it is considered no
longer maintained.

####  5.2.5 COROR

COROR [53] stands for ”COmposable Rule-entailment Owl Reasoner” and is a
reasoner optimized for embedded systems with limited memory and CPUs. It was
developed to research composition algorithms for rule-entailment OWL
reasoners. A project repository or website could not be found, so it is
considered to be no longer maintained.

####  5.2.6 DLEJena

DLEJena [40] combines Apache Jena’s forward-chaining rule engine and the
Pellet reasoner to provide OWL 2 RL reasoning. A project repository or website
could not be found, so it is considered to be no longer maintained.

####  5.2.7 DRAOn

DRAOn is written in Java and provides reasoning for networks of ontologies. It
supports both standard Description Logics semantics for non-distributed
reasoning and the Integrated Distributed Description Logics (IDDL) semantics
for distributed reasoning [31]. The OWL API and Alignment API 4.0[12] are used
internally. The HermiT reasoner is used to find inconsistencies in ontologies
and alignments. The official project page is no longer
accessible163163163http://iddl.gforge.inria.fr/ and a source code repository,
or something similar, could not be found.

####  5.2.8 ELOG

ELOG [52] is a prototype of an EL++ log-linear Description Logic reasoner,
written in Java. Its source code is publicly available and can be found on
Google Code164164164https://code.google.com/archive/p/elog-reasoner/. ELOG
uses foreign reasoners, such as HermiT or Pellet. There are some files
available for download, while the file ”elog.zip” contains files to run ELOG.
After extracting the ”elog.zip” archive, run the ”elog.Jar” in a terminal to
spawn a CLI. You can also use a dedicated web
service165165165http://executor.informatik.uni-mannheim.de/systems/elog/, to
check out the reasoner. The last commit was in
2014166166166https://code.google.com/archive/p/elog-
reasoner/source/default/commits. There is no indication that the project is
still maintained.

####  5.2.9 Hoolet

Hoolet167167167http://owl.man.ac.uk/hoolet/ provides OWL 2 DL reasoning using
the theorem prover Vampire. A dedicated publication could not be found, but a
short presentation is
available168168168http://www.daml.org/meetings/2004/05/pi/pdf/Hoolet.pdf. It
is also mentioned in other publications, for instance [25]. The downloadable
file has to be extracted and provides a file called ”hooletGUI”, which opens
an user interface. Based on my findings I consider the project to be no longer
maintained.

####  5.2.10 Hydrowl

Hydrowl [79] is a query answering system for OWL 2 DL ontologies, using
foreign reasoners, such as HermiT or OWLIM. The project page
http://www.image.ece.ntua.gr/g̃stoil/hydrowl/ is no longer available. There is
no evidence that the project is still maintained.

####  5.2.11 HyLAR

HyLAR [81] stands for ”Hybrid Location-Agnostic Reasoner” and partially
supports OWL 2 RL reasoning. It is written in JavaScript and uses the reasoner
of an abandoned project called JSW
Toolkit169169169https://code.google.com/archive/p/owlreasoner/[82]. The
project page is hosted on Github170170170https://github.com/ucbl/HyLAR-
Reasoner and the latest commit was in 2021. HyLAR is also available as an NPM
package171171171https://www.npmjs.com/package/hylar.

####  5.2.12 Minerva

Minerva [68, 99] is an ontology storage and inference system, using the Racer
and Pellet reasoner. The project is mentioned in some publications, but a
project page or source code repository could not be found.

####  5.2.13 MORe

MORe [2] stands for ”Modular OWL Reasoner” and is a system for classifying OWL
2 ontologies. It is written in Java and uses the OWL 2 reasoner HermiT and the
OWL 2 EL Reasoner ELK. It seems that the reasoner is no longer usable
according to one of the issues on
Github172172172https://github.com/anaphylactic/MORe/issues/1. The latest
commit was 7 years ago, the project is considered no longer maintained.

####  5.2.14 NoHR

NoHR [35] stands for ”Nova Hybrid Reasoner” and is a system that uses various
reasoners, such as HermiT or ELK) for reasoning tasks. It is written in Java
and can be used as Protégé plugin or via the Java API. NoHR was included
because it provides reasoning for different OWL profiles and supports a rule
engine (XSB Prolog173173173https://xsb.sourceforge.net/). The project is
hosted on Github174174174https://github.com/NoHRReasoner/NoHR, and I was able
to successfully load the plugin into Protégé, so I assume the project is still
usable. The latest commit was in 2019 though.

####  5.2.15 PAGOdA

PAGOdA [100] provides conjunctive query answering for OWL 2 ontologies.
Internally it uses the Datalog reasoner RDFox and the OWL 2 reasoner HermiT.
It can be used either using a Jar file or via the Java API. The source code is
hosted on Github175175175https://github.com/KRR-Oxford/PAGOdA. The latest
version 2.1.2 was in 2015, but the latest commit was in February 2023. I
assume the project gets small updates sporadically.

####  5.2.16 PROSE

PROSE [94] is a plugin-based paraconsistent OWL reasoner that uses a third-
party reasoner, such as Pellet or HermiT. Paraconsistent OWL ontologies are
characterized by the fact, that they can contain conflicting axioms. No
project page or source code repository could be found.

####  5.2.17 R2O2*

$R_{2}O_{2}*$[33] is a meta reasoner that selects the most appropriate
reasoner, such as ELK or FaCT++, for a given reasoning task. Robustness and
efficiency are used as selection criteria, for instance. It uses the OWL API
3.4. The source code and other material is hosted on
Github176176176https://github.com/liyuanfang/r2o2-star. I tried out the
reasoner, but compilation failed due to unfulfilled
dependencies177177177[ERROR] Failed to execute goal on project r2o2-star:
Could not resolve dependencies for project
edu.monash.infotech:r2o2-star:Jar:1.0: Failed to collect dependencies at
io.wasiluk:weka-xgboost:Jar:0.2.0 -¿ biz.k11i:xgboost-predictor:Jar:0.3.0:
Failed to read artifact descriptor for biz.k11i:xgboost-predictor:Jar:0.3.0:
Could not transfer artifact biz.k11i:xgboost-predictor:pom:0.3.0 from/to
bintray-komiya-atsushi-maven (http://dl.bintray.com/komiya-atsushi/maven):
Transfer failed for http://dl.bintray.com/komiya-
atsushi/maven/biz/k11i/xgboost-predictor/0.3.0/xgboost-predictor-0.3.0.pom:
Unknown host dl.bintray.com:. Latest commit was in 2019.

####  5.2.18 REQUIEM

REQUIEM is an OWL 2 QL reasoner to demonstrate a specific query rewriting
algorithm. It uses HermiT reasoner for reasoning tasks. The project page
https://www.cs.ox.ac.uk/isg/tools/Requiem/ mentions [59] as the primary
publication, but does not contain any reference to REQUIEM. It was mentioned
in passing in [95]. On Github there is one repository containing the source
code178178178https://github.com/ghxiao/requiem and another repository that
provides access to REQUIEM via a Docker
container179179179https://github.com/justin2004/pomify-REQUIEM. The latest
commit to the source code repository was in 2013.

####  5.2.19 RuQAR

RuQAR [3] is a query answering and reasoning framework for OWL 2 RL
ontologies. It uses the HermiT reasoner for TBox reasoning. RuQAR has been
mentioned in passing a few times in some publications. No project page could
be found.

####  5.2.20 Screech

Screech [23] seems to be a prototype for OWL ABox reasoning with approximation
using KAON2. This approach is useful in applications where efficient queries
are mot important than correctness. The project page http://logic.aifb.uni-
karlsruhe.de/screech is no longer available.

####  5.2.21 TrOWL: Quill and REL

TrOWL [54, 83] is a reasoning infrastructure for OWL 2. It uses Quill reasoner
and REL, an OWL 2 EL reasoner, which is based on ELK reasoner. The official
links to both reasoners are
broken180180180https://www.w3.org/2001/sw/wiki/OWL/Implementations. The source
code of TrOWL is hosted on Github, but without
documentation181181181https://github.com/TrOWL/core. Fun fact: the repository
links to the page http://trowl.eu/, which contains pornographic content!

####  5.2.22 WSClassifier and WSReasoner

WSClassifier [75] is a reasoner for ALCHI(D) ontologies. In the reasoner
list182182182http://owl.cs.manchester.ac.uk/tools/list-of-reasoners/ another
reasoner with the same name (WSReasoner [76]) is mentioned. It uses the ConDOR
and HermiT reasoner internally. There is a Google Code repository for
WSClassifier, but it only provides some information and a handful download
links183183183https://code.google.com/archive/p/wsclassifier/. Each download
link leads to a Google Drive folder.

###  5.3 (Probably) unusable OWL reasoners

In this section you will find a list of all OWL reasoners that are considered
(probably) not usable. Some of the reasoners have been manually tested.

####  5.3.1 BOSSAM

BOSSAM [25] is a RETE-based inference machine that supports reasoning for OWL
and SWRL ontologies, and RuleML rules. In comparison to similar reasoners, it
supports negation-as-failure and classical negation. According to the authors,
it handles dynamic and conflicting knowledge bases better than the
competition. It is written in Java, but is closed source. The project page
does not provide a working download
link184184184https://bossam.wordpress.com/. Latest activity was in
2007185185185https://bossam.wordpress.com/2007/08/18/new-api/.

####  5.3.2 CB OWL 2 Horn Reasoner

CB [26] is a reasoner for Horn SHIQ ontologies. It is written in OCaml and has
been developed as part of the
ConDOR186186186https://www.cs.ox.ac.uk/isg/projects/ConDOR/ project. They host
the source code on Github187187187https://github.com/ykazakov/cb-reasoner and
the latest commit is 13 years old. There are no binaries to download, so
compilation is required before the reasoner can be used. The reasoner should
run on Windows, Linux and MacOS X, but there are problems indicating that this
may no longer be the case anymore (e.g. on Ubuntu
14.04188188188https://github.com/ykazakov/cb-reasoner/issues/2). The
compilation189189189https://github.com/ykazakov/cb-
reasoner/blob/master/INSTALL failed on my local machine190190190I had to
install ocamlbuild, which fixed one error, but I ran into the following which
I couldn’t solve: ”/bin/sh: 1: ocamlopt: not found”.

####  5.3.3 Cereba Engine

It was difficult to find enough information about the Cereba Engine. In [45,
28] it is described as a software that provides logical reasoning through ABox
and TBox for DAML+OIL191191191https://www.w3.org/TR/daml+oil-reference/, OWL
and ontologies. In [28] there is a reference to a website with further
information192192192https://www2003.org/cdrom/papers/poster/p087/Poster87.html.
A dedicated project page or source code repository could not be found, so the
project is considered abandoned.

####  5.3.4 CICLOP

CICLOP is a Description Logic reasoner that supports role hierarchy and
inverse roles, for instance. There is no primary publication, but it is
mentioned in [84] and [17]. Binaries or source code for own tests could not be
found.

####  5.3.5 DBOWL

DBOWL [36] is a scalable reasoner (ABox focus), optimized for ontologies with
billions of triples. It provides extensive support for OWL 1 Description
Logic. DBOWL uses RDBMS for ontology storage and instance classification. The
official project page is https://khaos.uma.es/dbowl, but it does not contain
any information. Other web sites could not be found.

####  5.3.6 Deslog

Deslog [93] is a shared-memory parallel reasoner for Description Logic ALC. It
is written in Java and uses the OWL API. It uses parallel computing to speed
up reasoning, which distinguishes it from the more classic reasoners. Web
sites such as the project page or a Github repository could not be found.

####  5.3.7 DistEL

DistEL [49] is a Peer-to-Peer based, distributed reasoner that can be used to
classify EL+ ontologies. It is written in Java and uses
Redis193193193https://redis.io/ for data storage. The source code is hosted on
Github194194194https://github.com/raghavam/DistEL. The latest commit was in
2016. The code needs to be compiled before use as there are no binaries or
scripts available for download.

####  5.3.8 DLP

DLP [58] stands for ”Description Logic Programs” and is a Description Logic
system that contains sound and complete reasoners for expressive Description
Logics. It can be used for satisfiability checks for propositional modal
logics. DLP was developed to study various optimization techniques. The
official site http://www.bell-labs.com/user/pfps/dlp still exists, but only
shows a 404 page not found error.

####  5.3.9 DReW

DReW [97] is a query answering system for LDL+ ontologies and provides
reasoning for Description Logic programs over LDL+ ontologies. According to
the authors, it is optimized to handle large ontologies very well. It is
written in Java and the source code is hosted on
Github195195195https://github.com/ghxiao/drew. The latest version 0.3.0 beta 3
was released in March 3, 2013 and the latest activity in the repository was in
2015. I downloaded and extracted the 0.3.0 beta 3 archive and started the CLI
on Ubuntu 20.04. But first I had to complete the following steps: (1) set the
global variable DREW_HOME to the path of the extracted ZIP folder. (2) rename
the file drew-0.3-beta-3.Jar to drew-0.3-beta-2.Jar in the lib folder. Without
the second step, an error will occur196196196Error: Unable to access Jarfile
…. DReW requires DLV197197197http://www.dlvsystem.com/dlv/ to run (at least
partly), but DLV is no longer available.

####  5.3.10 ELLY

ELLY [71] is an ELP reasoner that is based on the ISIS Datalog
reasoner198198198https://www.iris-reasoner.org/. ELP is the decidable part of
the Semantic Web Rule Language (SWRL), that allows polynomial time reasoning.
By using the OWL API it supports reasoning for OWL 2 EL and OWL 2 RL. Further
information about the ISIS Datalog reasoner could not be found. This website
is incomplete and contains unrelated content. ELLYs project page is hosted on
Sourceforge199199199https://elly.sourceforge.net/.

####  5.3.11 FLOwer

$FL_{0}$wer [44] is a reasoner for the Description Logic $FL_{0}$ that
provides efficient TBox reasoning with value restrictions. It is a prototype
and was developed as part of a bachelor thesis200200200in German:
https://lat.inf.tu-dresden.de/research/theses/2017/Mic-Bac-17.pdf, is written
in Java. The source code is available on
Github201201201https://github.com/attalos/fl0wer, but there are no binaries to
download. For your own testing, you need to build the code using
Maven202202202https://maven.apache.org/. The latest commit was in 2019, so an
issue was opened to find out if there are plans for future
development203203203https://github.com/attalos/fl0wer/issues/1. There has been
no response yet.

####  5.3.12 F-OWL

F-OWL [101] is an F-Logic based inference machine for RDF and OWL. It uses the
XSB logic programming system with the Flora-2 extension, which provides an
F-logic frame-based representation layer. Neither a project page nor source
code repository could be found, so the project is considered abandoned.

####  5.3.13 HS-Reasoner

HS-Reasoner is an OWL 2 DL reasoner written in Haskell. The project is hosted
on Github204204204https://github.com/agnantis/hs-reasoner. According to the
developer, HS-Reasoner was developed to study possibilities of functional
programming for reasoners. An issue has been created for a short introduction
on how to install and use it205205205https://github.com/agnantis/hs-
reasoner/issues/1. I don’t have any knowledge in Haskell and without any
information on install and use, there was no way for me to determine if it is
usable or not. The latest commit was in 2019, so it is possible that the
project is still maintained.

####  5.3.14 leancor

leancor is a Description Logic reasoner and a fork of leanCoR. It is written
in Prolog and the source code is hosted on
Github206206206https://github.com/adrianomelo/leancor. Information about
installation and usage was scarce and scattered in various files. The
installation failed on my local machine (Ubuntu 20.04). It seems that leancor
uses the leanCoP theorem prover207207207http://www.leancop.de/index.html
internally208208208https://github.com/adrianomelo/leancor/blob/master/leancop.sh.
leancor is considered abandoned because the latest commit was in 2015 and the
project page http://www.leancor.org/ is no longer accessible.

####  5.3.15 LillyTab

LillyTab [96] is an OWL 2 reasoner for SHOF(D) Description Logic. It is
written in Java and its source code is hosted on
Github209209209https://github.com/pwub/lillytab. The latest version 1.12 was
released in 2015. According to the developer, LillyTab was developed as part
of his thesis ([96], page 79). For this reason and the fact that latest
development activity was in 2018, I assume that the project is no longer
maintained.

####  5.3.16 Mini-ME and Mini-ME Swift

Mini-ME [64] (short for Mini Matchmaking Engine) is a reasoner for ALN
(attributive language with unqualified number restrictions) Description Logic
(DL). It is written in Java and optimized for use on mobile devices (Semantic
Web of Things). There are two variants available: Tiny-
ME210210210http://swot.sisinflab.poliba.it/tinyme/ comes with a C-, Java- and
Object-C API. Mini-ME Swift211211211http://swot.sisinflab.poliba.it/minime-
swift/index.html is an iOS port, written in Swift212212212Swift project page:
https://developer.apple.com/swift/. Mini-ME is only distributed for the
purpose of academic evaluation and review only, no other use is allowed. On
the download page http://swot.sisinflab.poliba.it/minime/#download many links
are broken. Mini-ME Swift is only available for iOS and
MacOS213213213http://swot.sisinflab.poliba.it/minime-swift/. No source code
repository could be found. Mini-ME was tried locally. After downloading and
extracting the ”Mini-ME OWLLink package”, the file ”start-minime.sh” was
executed on the terminal. It started a server which was accessible at
localhost:8080, but a 404 error was displayed. Exception messages were
displayed on the terminal each time I visited the index page. The library
versions weren’t tried, so they may still be usable. Protégé plugin is
reported to work with Protégé 4.3 and
5.1214214214http://swot.sisinflab.poliba.it/minime/plugin.html, but no local
tests have been conducted due to missing plugin files.

####  5.3.17 O-DEVICE

O-DEVICE [39] is a rule-based object oriented OWL reasoner using the CLIPS
rule engine. The latest activity in the project repository was in 2013 and the
latest version is from 2010. For this reason the project is considered
abandoned. No local testing has been done, as most of the files are from 2009.

####  5.3.18 OWLgres

OWLgres [78] is a Description Logic lite reasoner using PostgreSQL. A project
page or source code repository could not be found. At
https://www.semanticweb.org/wiki/Owlgres.html there is a link to the project
page http://pellet.owldl.com/owlgres, but it is no longer accessible.

####  5.3.19 OWLIM

OWLIM [7] is a family of Semantic Web components and contains a reasoner. A
project page or source code repository could not be found.

####  5.3.20 Pocket KRHyper and KRHyper

Pocket KRHyper [70] is a Description Logic reasoner, highly optimized to run
on embedded systems. Its predecessor is KRHyper. Own tests weren’t possible
due to the official download link http://www.uni-
koblenz.de/$\sim$%7B%7Diason/downloads is not working anymore.

####  5.3.21 Pronto

PROTON [55] is a reasoner for managing temporal information in OWL ontologies.
The project is hosted on Github and provides the source code, documentation
and help scripts215215215https://github.com/klinovp/pronto. The installation
instructions weren’t sufficient enough and own tests on Ubuntu 20.04 failed,
because of a missing file216216216Running ”pronto.sh” in the terminal resulted
in the error that ”dist/lib/pronto.Jar” is not available.

####  5.3.22 QueryPIE

QueryPIE [90] is a reasoner that uses backward reasoning and is optimized to
handle ontologies with billions of triples. The project is hosted on
Github217217217https://github.com/jrbn/querypie. Its worth mentioning, because
it is one of the few reasoners that can handle large ontologies. The latest
activity on the repository was in 2017. Downloading and building with Ant was
successful, but using it requires a custom Java program and involves
additional software such as Hadoop218218218https://hadoop.apache.org/, so I
stopped further testing.

####  5.3.23 SPOR

SPOR [1] stands for ”SPatial Ontology Reasoner” and supports efficient
reasoning on Geographic Object-Based Image Analysis (GEOBIA) ontologies using
fuzzy, spatial, and multi-scale representations. The project is hosted on
Github, but no binaries are
provided219219219https://github.com/ArArgyridis/SPOR. No installation or usage
instructions are provided, so no tests have been performed. The reasoner can
also be used via Gnorasi220220220https://github.com/gnorasi/gnorasi according
to [1].

####  5.3.24 QuOnto

QuOnto [32] is a OWL reasoner for the OWL 2 QL profile, optimized to achieve
superior performance in classifying OWL 2 QL ontologies, compared to similar
reasoners. No project page or source code repositories could be found.

####  5.3.25 Racer and RacerPro

Racer is a Description Logic SRIQ(D) reasoner. It was written in Java and
Common Lisp. According to the project page221221221https://www.ifis.uni-
luebeck.de/ moeller/racer/index.html it is the successor of RacerPro [22].
This is interesting, because publications about RacerPro are 11 years older
than the release date of Racer. The source code of Racer is hosted on
Github222222222https://github.com/ha-mo-we/Racer and licensed under the terms
of the BSD-3-clause license. The latest release was in 2014 and the latest
commit was in 2018. Because of the advanced knowledge in Common Lisp skills
required, no testing has been done. Although, Racer and Racer Pro may run
still, but are considered unusable, e.g. because downloads are no longer
available223223223User Guide: https://github.com/ha-mo-
we/Racer/blob/master/doc/users-guide-2-0.pdf, on page 6 it links to
http://www.racer-systems.com/products/download/index.phtml which is not
available anymore, for instance. The project appears to have been abandoned.

####  5.3.26 Rat-OWL

Rat-OWL [19] is a reasoner for the non-monotonic extension of Description
Logic. According to the publication it is only available for Protégé 4.3
(released in
2013224224224https://protegewiki.stanford.edu/wiki/P4_3_Release_Announcement),
using OWL API 3.4. A project page or source code repository could not be
found. The Protégé plugin was also no longer available225225225Checked
https://protegewiki.stanford.edu/wiki/Protege_Plugin_Library and did a basic
Internet search.

####  5.3.27 SHER

SHER [14] stands for ”scalable highly expressive reasoner” and has a good
performance, according to the authors. However, the project website is no
longer accessible 226226226http://www.alphaworks.ibm.com/tech/sher.

####  5.3.28 Snorocket

Snorocket [43] is a highly optimized reasoner for a specific subset of the OWL
2 EL profile. The project is hosted on
Github227227227https://github.com/aehrc/snorocket and can be used via the OWL
API or via the Protégé
plugin228228228https://protegewiki.stanford.edu/wiki/Snorocket. The version
3.0.0 is listed as the latest version, but no downloads could be
found229229229https://protegewiki.stanford.edu/wiki/Snorocket_3.0.0. The same
goes for version
2.0.0230230230https://protegewiki.stanford.edu/wiki/Snorocket_2.0.0. Although
the latest commit was in 2019, the project is considered abandoned due to the
lack of download links.

####  5.3.29 SoftFacts

SoftFacts [80] is an information retrieval system for relational databases
that provides reasoning, e.g. instance query answering. There is a project
with the same name, but it is
empty231231231https://github.com/straccia/SoftFacts. No usable source code or
binaries could be found.

####  5.3.30 SparkEL

SparkEL [48] is a distributed OWL 2 EL reasoner using Apache
Spark232232232http://spark.apache.org/. It is written in Scala and the source
code is hosted on Github233233233https://github.com/raghavam/sparkel. The
latest commit was in 2016 and the binaries provided are outdated. I tried to
install it using the install
script234234234https://github.com/raghavam/sparkel/blob/master/script/install-
all.sh, but it failed because dependencies, such as SBT 0.13.9, weren’t
accessible anymore. SparkEL may still be usable, but it is doubtful due to
outdated dependencies.

####  5.3.31 SPOWL

SPOWL [34] uses Apache Spark to provide reasoning for large OWL ontologies. It
acts as a compiler that maps TBox axioms to Spark programs. No source code or
binaries were available, so the project is considered abandoned.

####  5.3.32 SWRL-IQ

SWRL-IQ [16] is a plugin for the outdated Protégé version 3. According to the
authors it combined features that no other reasoning/query system had at the
time, such as constraint-solving based on CLP(R) (Constraint Logic Programming
with Reals) as well as SWRL extensions for non-monotonic aggregation, limited
higher order logic. The plugin
page235235235https://protegewiki.stanford.edu/wiki/SWRL-IQ on the Protégé wiki
was updated in 2012. The manual may still be useful
236236236https://protegewiki.stanford.edu/images/5/57/SWRL-IQ_manual.pdf. The
project page 237237237https://www.onistt.org/display/SWRLIQ/SWRL-IQ is no
longer accessible and the project is considered abandoned.

####  5.3.33 TReasoner

TReasoner [21] is a reasoner for SHOIQ(D) that implements a tableau algorithm.
The project is hosted on Google
Code238238238https://code.google.com/archive/p/treasoner/. The latest commit
was in 2014. There is no documentation available, so I assume it is only
usable within a custom Java project.

####  5.3.34 WebPIE

WebPIE [89] is an OWL/RDFS inference machine using
Hadoop239239239https://hadoop.apache.org/. The reasoning is being mapped on
Map and Reduce operations, allowing distributed, more performant processing of
large quantities of data. According to the project website
https://www.few.vu.nl/ jui200/webpie.html#sourcecode the project is no longer
maintained. Some links in the documentation are broken and the only available
file was published in 2012. Due to the outdated files and the need to setup a
cluster on your own240240240https://www.few.vu.nl/
jui200/webpie.html#tutorial, no further testing have been conducted. WebPIE
might still usable, but it is doubted.

####  5.3.35 Wolpertinger

Wolpertinger [63] is a fixed-domain OWL reasoner. OWL is based on the Open
World assumption, which means, an axiom can be true regardless if it is known
to be true or not. There are applications where this can lead to undesirable
(because contradictory) situations. The reasoner doesn’t use the standard
model-theoretical semantics, instead the domain is reduced to an explicitly
given set of axioms. Wolpertinger is written in Java and the source code is
hosted on Github241241241https://github.com/wolpertinger-reasoner/Wolpertinger
(latest commit was in 2019). There are no binaries available. I tried to build
one myself but ran into errors, that have been reported in an
issue242242242https://github.com/wolpertinger-reasoner/Wolpertinger/issues/2.

##  6 Conclusion

In this work 73 OWL reasoners and 22 systems (using a third-party reasoner)
were analyzed and metadata such as usability and maintenance status was
collected. All the OWL reasoners found that were considered usable and
maintained, need to be analyzed in more detail and with regards to their
applications. For instance, not all OWL 2 DL reasoners fully support the OWL 2
DL profile. Also, some systems were developed using outdated development
environments such as Java 1.5, which was released 2011. All systems are
described in a more general terms as they are currently exist.

In the following is a list of positive observations:

  1. 1.

Rooted in science: Most of the analyzed systems are mentioned in at least one
publication. It is either a system description paper or an
evaluation/comparison of two or more reasoners. Many papers on the underlying
methods and describe them in detail, which helps to understand the inner
workings of a system.

  2. 2.

Diverse software: OWL reasoners are developed in a variety of languages and
environments. Java is the most prominent one. The functional scope of each
individual system is also diverse. Each language/environment has its own
advantages that make it ideal for specific use cases, such as high performance
computing or embedded systems.

  3. 3.

Constant interest: New projects have been started in recent years, which may
be an indicator that there is still sufficient research interest in this area.
Many projects host their code on Github, which also encourages new people to
contribute.

The negative observations are summarized below:

  1. 1.

Inadequate documentation: Most of the projects provide little or no
documentation to their users. It seems that the authors assume that their
users have the necessary knowledge in any software environment they use, be it
a simple Java binary, a Hadoop or Haskell/Scala setup. Also, some projects
have split their documentation into different files, or even whole web sites,
making it much harder to learn about a particular system. Scientific
publications may be considered as part of the documentation, but they usually
do not contain any end-user information (such as installation manual or usage
introductions).

  2. 2.

Short term usage: A large percentage of the OWL reasoners had prototype status
to demonstrate a novel approach. This may partly explain why the documentation
was scarce in comparison to other projects. However, prototypes are not of
interest to people who want to use a stable basement for a new software,
whether they are scientists or not. Poor documentation can also hinder new
users who want to learn about a software.

  3. 3.

Bad maintenance situation: Only 28 out of 73 OWL reasoners are actively
maintained, which means they have had some development activity during the
last 3 years. Few had project repositories set up in a way that would support
long-term development. Continuous integration pipelines or even (unit-,
system-, …) tests were scarce. Some projects on Github had more than 10 open
pull requests unanswered, meaning that there were people who wanted to
contribute code changes, but the author ignored them. Similar observations
have been made in [30].

##  7 Future work

As mentioned in the previous section, all usable and maintained OWL reasoners
found need to be analyzed in more detail and with regard to their
applications. Verification of my findings, especially for those systems where
my knowledge is very limited, would be important. In some cases I have created
an issue in the project repository, which could be a good starting point for
further investigation. Performance comparisons are also of interest due to the
hardware developments in the recent years (e.g. parallel computing, GPU
computing). Only a few OWL reasoners have used parallel computing at all.

The part of the Semantic Web/Logic community working with OWL reasoners should
consolidate the current state. It is important to find out, which systems are
still sufficient enough to handle current use cases. It is also important to
provide the necessary documentation for end users to try them out. I am afraid
we can only salvage what is left of systems like HermiT, but this could be the
first step towards new developments.

For all the reasons mentioned above, I claim that a large number of analyzed
OWL reasoners are not of interest to companies, especially in the areas of
software development and knowledge organization. Many systems are almost black
boxes to their users, with poor documentation, outdated dependencies and no
support from their developers. OWL reasoners such as HermiT are still widely
used, although they are being abandoned, because there are not many
alternatives available. Therefore surveys/studies that further investigate
this issue are very important.

##  8 Acknowledgement

This work was supported by a grant from the German Federal Ministry of
Education and Research (BMBF) for the KI-Werk Projekt
(https://www.cbasynergy.net/cba/ki-werk.html).

##  9 Appendix

OWL Reasoner
---
AllegroGraph
Arachne
BaseVISor
BORN
CEL
ElepHant
ELK
Expressive Reasoning Graph Store (IBM)
EYE
EYE.js
jcel
JFact
Konclude
LiFR
LiRoT
Ontop (with Query reasoner)
Openllet
OWLRL
RDFox
RDFSharp.Semantics
reasonable
TRILL (and TRILLP and TORNADO)
Vampire
VLog
Whelk
Table 3: List of usable and maintained OWL reasoners  Reasoner | Maintenance | Is usable
---|---|---
AllegroGraph | maintained | usable
Arachne | maintained | usable
BaseVISor | maintained | usable
BORN | maintained | usable
Bossam | abandoned | no files to try available
CB (Consequence-based reasoner) | abandoned | no, compilation failed
CEL | maintained | usable
Cerebra Engine | abandoned | no files to try available
CICLOP | abandoned | no files to try available
Clipper | abandoned | usable
DBOWL | abandoned | no files to try available
Deslog | abandoned | no files to try available
DistEL | abandoned | no, missing info about how to compile it
DLP | abandoned | no files to try available
DReW | abandoned | no, DLV required, but not available
ElepHant | maintained | usable
ELK | maintained | usable
ELLY | abandoned | no, jar files seem broken
Expressive Reasoning Graph Store (IBM) | maintained | usable
EYE | maintained | usable
EYE.js | maintained | usable
F-OWL | abandoned | no files to try available
FaCT++ | abandoned | usable
Flower | abandoned | no, Maven build failed
fuzzyDL | abandoned | not tried, because Protégé 4.3 didn‘t run
HAM-ALC | abandoned | no files to try available
HermiT | abandoned | usable
HS-Reasoner | abandoned | not tried, no knowledge about Haskell
jcel | maintained | usable
JFact | maintained | usable
KAON2 | abandoned | usable
Konclude | maintained | usable
leanCoR | abandoned | no, SWI setup in Ubuntu 20.04. failed
LiFR | maintained | usable
LillyTab | abandoned | no, jar files seem broken
LiRoT | maintained | usable
Mini-ME | maintained | no, download links for plugin broken [… ]
Mini-ME Swift | no information available | usable
NORA | maintained | not tried, because it requires additional software […]
ODevice | abandoned | not tried, because files are outdated
Ontop (with Query reasoner) | maintained | usable
Openllet | maintained | usable
Owlgres | abandoned | no files to try available
OWLIM | abandoned | no files to try available
OWLRL | maintained | usable
Pellet | abandoned | usable
Pocket KRHyper | abandoned | no files to try available
Pronto | abandoned | no, start script seems faulty
QueryPIE | abandoned | not tried, because it requires additional software
Quill (part of TrOWL) | abandoned | no files to try available
QuOnto | abandoned | no files to try available
RACER / RacerPro | abandoned | no files to try available
RAT-OWL | abandoned | no files to try available
RDFox | maintained | usable
RDFSharp.Semantics | maintained | usable
reasonable | maintained | usable
REL (part of TrOWL) | abandoned | no files to try available
Sequoia | maintained | not tried, because it requires a Scala environment
SHER | abandoned | no files to try available
Snorocket | abandoned | no files to try available
SoftFacts | abandoned | no files to try available
SparkEL | abandoned | no, setup script seems faulty
SPOR | abandoned | not tried, no knowledge in compiling C++ programs
SPOWL | abandoned | no files to try available
SWRL-IQ | abandoned | no, outdated Protégé required
Tiny-ME | no information available | usable
TReasoner | abandoned | not tried, it requires a custom Java project
TRILL (and TRILLP and TORNADO) | maintained | usable
Vampire | maintained | usable
VLog | maintained | usable
WebPIE | abandoned | not tried, because it requires additional software
Whelk | maintained | usable
Wolpertinger | abandoned | no, Maven build failed
Table 4: List of all analyzed OWL reasoners  Systems using foreign reasoners | Maintenance | Is usable
---|---|---
AberOWL | maintained | usable
BUNDLE | maintained | usable
Chainsaw | maintained | not tried, because custom Java project required
ComR | abandoned | no files to try available
COROR | abandoned | no files to try available
DLEJena | abandoned | no files to try available
DRAOn | abandoned | no files to try available
ELOG | abandoned | usable
Hoolet | abandoned | usable
HydrOWL | abandoned | no files to try available
HyLAR | maintained | useable
Minerva | abandoned | no files to try available
MORe | abandoned | not tried, because custom Java project required
NoHR | abandoned | useable
PAGOdA | maintained | useable
PROSE | abandoned | no files to try available
R2O2* | abandoned | no, compilation failed
REQUIEM | abandoned | yes, Docker container was tried
RuQAR | abandoned | no files to try available
Screech | abandoned | no files to try available
TrOWL | abandoned | not tried, I assume custom Java project is required
WSClassifier (and WSReasoner) | abandoned | not tried, because files in various Google Drive folders
Table 5: List of all analyzed systems using a third-party reasoner

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