Semantic Web Software

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Browse free open source Semantic Web software and projects below. Use the toggles on the left to filter open source Semantic Web software by OS, license, language, programming language, and project status.

  • Cyber Risk Assessment and Management Platform Icon
    Cyber Risk Assessment and Management Platform

    ConnectWise Identify is a powerful cybersecurity risk assessment platform offering strategic cybersecurity assessments and recommendations.

    When it comes to cybersecurity, what your clients don’t know can really hurt them. And believe it or not, keep them safe starts with asking questions. With ConnectWise Identify Assessment, get access to risk assessment backed by the NIST Cybersecurity Framework to uncover risks across your client’s entire business, not just their networks. With a clearly defined, easy-to-read risk report in hand, you can start having meaningful security conversations that can get you on the path of keeping your clients protected from every angle. Choose from two assessment levels to cover every client’s need, from the Essentials to cover the basics to our Comprehensive Assessment to dive deeper to uncover additional risks. Our intuitive heat map shows you your client’s overall risk level and priority to address risks based on probability and financial impact. Each report includes remediation recommendations to help you create a revenue-generating action plan.
  • ThermoGrid Contractor Management Software Icon
    ThermoGrid Contractor Management Software

    ThermoGrid is a specialized contractor management software tool for managing field service operations

    Nail down how you manage your day-to-day and level up your services. Whether you are a plumber, electrician, or HVAC technician, ThermoGrid brings together all areas of your business so you can get the job done right.
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    Web Starter Kit

    Web Starter Kit

    Web Starter Kit - a workflow for multi-device websites

    Web Starter Kit is an opinionated boilerplate for web development. Tools for building a great experience across many devices and performance oriented. Helping you to stay productive following the best practices outlined in Google's Web Fundamentals. A solid starting point for both professionals and newcomers to the industry. A responsive boilerplate optimized for the multi-screen web. Powered by Material Design Lite. You're free to use either this or a completely clean-slate via basic.html. Minify and concatenate JavaScript, CSS, HTML and images to help keep your pages lean. JavaScript code linting is done using ESLint - a pluggable linter tool for identifying and reporting on patterns in JavaScript. Web Starter Kit uses ESLint with eslint-config-google, which tries to follow the Google JavaScript style guide. A built-in server for previewing your site locally while you develop and iterate. Reload the browser in real-time anytime an edit is made without the need for an extension.
    Downloads: 1 This Week
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  • 2
    MRCube

    MRCube

    Meta-Model Management based on RDFs Revision Reflection

    MRCube is a graphical editing tool of RDF-based contents developed for managing a relationship between RDF and RDFS contents.
    Downloads: 29 This Week
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  • 3
    The CDM-Core ontology (CREMA Data Model - core module) is a manufacturing ontology, specialised in the two application sub-domains of 1) exhaust car manufacturing and 2) metallic press maintenance The CDM-Core ontology was developed by: Dr. Luca Mazzola, Msc. Patrick Kapahnke, Marko Vujic, and PD Dr. Matthias Klusch at the German Research Center for Artificial Intelligence DFKI GmbH (http://www.dfki.de ) in Saarbrücken, Germany. Copyright: DFKI, 2016, licence CC BY-SA see http://creativecommons.org/licenses/by-sa/3.0/ For bug reports, technical problems and feature requests please contact: Luca Mazzola: luca.mazzola@dfki.de or mazzola.luca@gmail.com Patrick Kapahnke: patrick.kapahnke@dfki.de
    Downloads: 17 This Week
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  • 4
    Sesame

    Sesame

    Java RDF Framework

    This project is no longer actively maintained. It is succeeded by the Eclipse RDF4J project, which can be found at GitHub and at http://www.rdf4j.org/. Sesame is a de-facto standard framework for processing RDF data. This includes parsing, scalable storage, reasoning and full SPARQL 1.1 query/update support. Sesame offers a fully modular toolkit and an easy-to-use Java API that can be connected to all leading RDF storage solutions.
    Downloads: 2 This Week
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  • Finance Automation that puts you in charge Icon
    Finance Automation that puts you in charge

    Tipalti delivers smart payables that elevate modern business.

    Our robust pre-built connectors and our no-code, drag-and-drop interface makes it easy and fast to automatically sync vendors, invoices, and invoice payment data between Tipalti and your ERP or accounting software.
  • 5

    rdf2rdf

    This Java tool converts RDF data from any RDF format to any other.

    This Java tool converts your RDF files from any RDF format to any other format. It is based on the openRDF.org Sesame project and is wrapped into one single jar file for easy usage.
    Downloads: 6 This Week
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  • 6
    The Common Lisp Reasoner extends the Common Lisp Object System (CLOS) to incorporate a powerful rule language suitable for all kinds of reasoning tasks, vanilla XML and RDF/XML interfaces, and support for a variety of AI-related applications, such as scheduling, planning and diagnosis.
    Downloads: 2 This Week
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  • 7
    A lightweight IDE for Artificial Intelligence. Started as GUI for the Euler reasoning engine. The sources can be N3, RDF, OWL, UML, eCore, plain XML or XSD, files or URL's. Wraps Drools (or CWM, FuXi) as N3 rules engines. Model based app. generation.
    Downloads: 2 This Week
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  • 8
    HERAKLES is a reasoning broker framework for OWL (Web Ontology Language) reasoning systems.
    Downloads: 2 This Week
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  • 9
    SPARQL to Object Oriented eNgine allows users to expose their traditional data sources (RDBMS, OODBMS, XML, LDAP, ecc) as RDF data, through a SPARQL endpoint.
    Downloads: 2 This Week
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  • Claims Processing solution for healthcare practitioners. Icon
    Claims Processing solution for healthcare practitioners.

    Very easy to use for medical, dental and therapy offices.

    Speedy Claims became the top CMS-1500 Software by providing the best customer service imaginable to our thousands of clients all over America. Medical billing isn't the kind of thing most people get excited about - it is just a tedious task you have to do. But while it will never be a fun task, it doesn't have to be as difficult or time consumimg as it is now. With Speedy Claims CMS-1500 software you can get the job done quickly and easily, allowing you to focus on the things you love about your job, like helping patients. With a simple interface, powerful features to eliminate repetitive work, and unrivaled customer support, it's simply the best HCFA 1500 software available on the market. A powerful built-in error checking helps ensure your HCFA 1500 form is complete and correctly filled out, preventing CMS-1500 claims from being denied.
  • 10
    Similarity Algorithm based on WikipediA
    SAWA calculates a semantic similarity coefficient between two sentences. Coefficient is expressed between "0" and "1", where: 0 means there is not semantic similarity among them; 1 vice versa.
    Downloads: 2 This Week
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  • 11
    ICT-Alive
    The aim of ALIVE is to develop new approaches to the engineering of flexible, adaptable distributed service-oriented systems based on the adaptation of social coordination and organisation mechanisms.
    Downloads: 1 This Week
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  • 12
    Our aim is to enable Web applications to consume linked data from the Web. With SQUIN (Semantic Web Query Interface) we will provide a Web data query service as an addition to the LAMP technology stack. This service executes queries over the whole We
    Downloads: 1 This Week
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  • 13

    MELO

    Machine Executable Language Ontology (MELO)

    This project is intended to fill the gap between the semantic web and the mainstream of software engineering, especially to integrate the semantic web with programming languages, and find an ontological representation of programming languages, including abstract syntax code execution, and global interoperability in execution environments. The machine executable language is modelled in OWL 2 DL using OWL API in C++ developed in this project.
    Downloads: 1 This Week
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  • 14
    Some tools related to the Music Ontology - including domain-specific Semantic Web crawlers, audio collection management and mapping tools
    Downloads: 1 This Week
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  • 15
    PoliMaR (Policy Matchmaker and Ranker) is a framework that permits a Semantic Web Service matchmaking and ranking based on Non-Functional Properties (NFPs).
    Downloads: 1 This Week
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  • 16

    RDFConvert

    commandline syntax convertor for RDF

    RDFConvert is a simple command-line tool for converting RDF file betweeen different syntax formats. It is based on the OpenRDF Rio parser toolkit, and currently supports RDF/XML, Trig, Trix, Turtle, N3, N-Triples, RDF/JSON, JSON-LD, Sesame Binary RDF and N-Quads.
    Downloads: 1 This Week
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  • 17
    *** PROJECT NOT MAINTAINED ANYMORE *** RDFStats generates statistics for RDF datasets behind SPARQL-endpoints and within single RDF documents.
    Downloads: 1 This Week
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  • 18

    Researchers Ontology

    Researchers Ontology Search Engine

    This project is a search engine that gathers data from an ontology. We took as exemple an ontology of researchers. The search uses the properties and works with partial queries and substrings. The client searching doesn't have to use the DLQuery nor the Manchester OWL Syntax, the engine we made builds the query in these syntaxes.
    Downloads: 1 This Week
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  • 19
    A simple tool for sketching out ontology structures, including OWL export. Developed at the University of Manchester as a third-year project.
    Downloads: 1 This Week
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  • 20
    Some More Individual - Yes! A couple of projects around Semantic Web technologies to help to establish a better accessible Web and personalize this access.
    Downloads: 1 This Week
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  • 21
    This project is dedicated for semantic annotation of video and image files and development of a unified page ranking for them.
    Downloads: 1 This Week
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  • 22

    ontocomp

    OntoComP is a Protégé 4 plug-in for completing OWL ontologies

    OntoComP is a Protégé 4 plug-in for completing OWL ontologies. It enables the user to check whether an OWL ontology contains "all relevant information" about the application domain, and extends the ontology appropriately if this is not the case. It achieves this by asking the user questions of the form "are instances of classes C1 and C2 also instances of class C3?". If the user confirms such a question, then a new axiom of the application domain that does not follow from the ontology has been discovered, and it is added to the ontology. If the user rejects it, the user has to give a counterexample to this question, i.e., an individual that is an instance of C1, C2 and not C3. When all such questions (about some initially given classes) have been answered, the ontology is complete with respect to the application domain.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 23
    ASI to Smart-M3 SIB synchronization agent
    Downloads: 0 This Week
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  • 24
    AnnoCultor: porting cultural repositories to the Semantic Web.
    Downloads: 0 This Week
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  • 25
    Arastreju is a Java based engine for ontology based information management.
    Downloads: 0 This Week
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Open Source Semantic Web Software Guide

Open source semantic web software is a type ofprogram which allows users to organize, store, and share data in an easy-to-understand format. This type of software makes use of what are known as semantics or meanings that describe how things and concepts relate to each other. Data stored with open source semantic web software is organized into relationships such as classes, properties, and instances which makes it easier for computers to understand the data.

One advantage of open source semantic web software is that users can create specific schemas, or sets of rules describing how all the data must be organized in order to make sense of it. This feature helps maintain consistency in the quality of the stored information regardless if different people are entering the data or if multiple databases are being used. Another benefit is that new information can easily be added without needing to change existing database structures making it easier for organizations to expand their database capabilities over time.

Additionally, open source semantic web software gives organizations more control over their data by allowing them to define any number of domain models for different purposes including but not limited to customer relations management (CRM), enterprise resource planning (ERP), finance operations and analytics systems, among others. This flexibility empowers users by allowing them tailor their databases according to their individual preferences while still keeping compatibility with industry standards like OWL and RDFa languages.

Finally, another great benefit provided by open source semantic web technology is its security features which protect all confidential user data from unauthorized access or manipulation. By using standard encryption protocols based on public/private key pairs between sender/recipient nodes any transmission over the network will remain secure at all times guaranteeing privacy for anyone who participates in this system.

Features Offered by Open Source Semantic Web Software

  • Resource Description Framework (RDF): RDF is a data model used to represent information as web-based resources. It uses triples, which are statements that consist of a subject, predicate, and object. This allows information to be linked together and accessed in a more organized manner.
  • SPARQL Protocol and RDF Query Language (SPARQL): SPARQL is the language used for querying data from an RDF database. The queries can be run over the web using commands like SELECT, ASK, CONSTRUCT, DESCRIBE and UPDATE. This makes it possible to access large amounts of semantic data quickly and easily.
  • Ontologies: Ontologies are used to describe entities within a certain domain or knowledge area by creating hierarchies of class structure and relationships between classes. This provides more structure for understanding how different types of data connect and helps automate tasks such as classification and reasoning.
  • Reasoners: Reasoners are programs that can process an ontology and make deductions based on the facts stated in it. They can also detect any inconsistencies in the ontology so they can be corrected before use.
  • Natural Language Processing (NLP): NLP tools analyze text written in natural languages like English or Spanish in order to extract structured information from it. For example, they might recognize named entities such as people or organizations mentioned within the text which could then be stored in an ontology or queried using SPARQL commands later on.

Different Types of Open Source Semantic Web Software

  • RDF/XML Parsers: These components of open source semantic web software allow for the conversion of data from one form to another, such as from HTML to XML, or from DBMS to XML.
  • Sparql Query Engines: These components enable Semantic Web developers to write queries in a language (typically SPARQL) that can match up content in distributed databases.
  • Ontology Development Tools: Ontology tools are used to create and maintain network graphs of related concepts, producing a visual representation of knowledge and relationships.
  • Natural Language Processing Libraries: NLP libraries enable developers to process natural language expressions; they also enable machines to interpret human language and generate responses with some degree of understanding.
  • Semantic Reasoning Engines: A reasoning engine helps users build and manage rules that give computers instructions regarding how to act upon certain conditions or events.
  • Knowledge Representation Software: This type of software helps store information in a structured way so it can be easily understood by people, machines, or both. It is especially useful for representing complex information about relationships between different entities like people or organizations.
  • Content Management Systems: Content management systems provide ways for managing digital assets including documents, images, audio and video files on a website or intranet environment while allowing easy collaboration between multiple parties. They also often integrate with other business systems such as those dealing with customer relationship management and enterprise resource planning solutions .

Advantages Provided by Open Source Semantic Web Software

  1. Cost Savings: Open source semantic web software is available for free or at a very low cost compared to proprietary software solutions. This can provide significant savings in both the short and long term, as there are no ongoing licensing fees or maintenance costs associated with open source software.
  2. Scalability: Semantic web technology offers flexibility and scalability that allows developers to quickly grow an application by adding new features and capabilities as needed. For organizations with rapidly changing requirements, the ability to easily scale up and down makes open source semantic web software an attractive option.
  3. Quality Assurance: Many open source projects go through rigorous code reviews, which helps ensure quality code releases. This can be especially beneficial for larger projects where multiple developers may need to access and maintain the same codebase.
  4. Collaboration: The collaborative nature of many open source communities means that you have access to thousands of experienced professionals who can help troubleshoot any issues you may face while developing your semantic web project. Additionally, individuals can contribute their own ideas to improve existing projects or even create entirely new ones.
  5. Security: Open source security measures such as strong encryption protocols are often used in order to protect sensitive data from malicious actors. Since these protocols are typically built into the software’s code base, they make it much more difficult for attackers to bypass them in order obtain private information stored on a server running this type of application.

Types of Users That Use Open Source Semantic Web Software

  • Developers: Use open source semantic web software to create applications, websites, and other programs. They are possible contributors to the software as well.
  • Researchers: Utilize open source semantic web software for research purposes, such as better understanding of data structures or extracting usable information from large datasets.
  • Students: Open source semantic web software is used by students in classes to study different aspects related to computing sciences. The practical exercises they run with this technology can help them develop a deeper understanding of its underlying structure and principles.
  • Hobbyists: People who use open source semantic web software as a passion project or just out of curiosity are hobbyists who want to explore new technologies without any commercial-oriented goals or ambitions.
  • Integrators: Organizations and companies looking for comprehensive solutions make use of open source semantic web software due to its scalability and flexibility in integration with existing systems and platforms.
  • Educators/Instructors: Instructors teaching computer science courses often introduce open source semantic web software into their curriculums to provide students with the opportunity of learning about new technologies in action rather than just theoretical explanations.

How Much Does Open Source Semantic Web Software Cost?

Open source semantic web software is completely free to use. There are no upfront costs associated with any of the open source semantic web software options available. This means you don't have to pay any licensing fees, or purchase a license in order to use the software. Furthermore, since open source software is developed collaboratively by communities of developers, anyone can make improvements and additions to the codebase which can be freely shared with others. As such, there is no need to invest time and resources into developing custom solutions for your particular application or platform. With open source semantic web software you get access to an ever-evolving set of tools that are constantly being optimized and improved without additional cost or effort on your part.

What Software Does Open Source Semantic Web Software Integrate With?

Open source semantic web software can be integrated with a variety of software, including content management systems (CMS), text editors, and search engines. CMS can be used to create and manage webpages, which simplifies the process of building and maintaining websites for those who do not want to write HTML code. Text editors can be used to modify existing texts or documents developed according to Semantic Web standards in an easier way than writing HTML code. Finally, search engines can utilize the data added into Semantic Web databases to develop more complex searches that lead users directly to more relevant results.

What Are the Trends Relating to Open Source Semantic Web Software?

  1. Increased accessibility: Open source semantic web software is becoming more accessible to a wider range of users due to its open source nature. This allows users to customize and modify the software to their needs and requirements, as well as providing a platform for collaboration between developers and users.
  2. Streamlined integration: Open source semantic web software makes it easier for developers to integrate various services, applications, and databases quickly and efficiently. This means that organizations can develop applications faster and with greater scalability.
  3. Enhanced scalability: As open source software continues to become more popular, scalability becomes an increasingly important factor in the development of applications. Scalability refers to the ability of a system to grow and adapt in response to increased demand or load. Open source solutions are highly scalable, allowing developers to create large-scale solutions without significant additional cost or complexity.
  4. Improved customization: Open source solutions allow users to make changes as needed, allowing them to tailor their solutions precisely according to their needs. This means that organizations can create customized solutions without having to invest heavily in developing from scratch.
  5. Greater interoperability: Open source solutions provide better interoperability between different components of the system, making it easier for developers to integrate various pieces into a cohesive whole. This improved interoperability leads to greater flexibility for organizations as they can easily switch components or add new ones without incurring extra costs or effort.

How Users Can Get Started With Open Source Semantic Web Software

Getting started with open source semantic web software is relatively straightforward. Many of the most popular applications are free to access, making it easy to get up and running quickly.

The first step is to find a good platform for hosting your application. You can choose from a variety of options, such as Sandbox or Heroku, or you can host your own server. Once you have chosen a platform, ensure that the necessary software packages are installed, including an RDF parser and query language implementation like Jena or Sesame.

Next, create an ontology for your app's data model by building its classes and relationships in an editor like Protégé. This will provide structure and organization for your application’s data so that it can be understood by other systems or applications. You should also define labels and comments for each class and relationship using natural-language terms that make sense in context; this makes data easier to understand by humans.

Once the ontology is built out, you will need to generate some instance data - sample objects that populate the ontology graph with real-world values - through either manual entry or automated scripts (such as SPARQL). Then you'll want to load this instance data into your chosen triple store solution (e.g., Apache Jena Fuseki). Finally, use one of many available libraries (such as Javascript/NodeJS) to write code which interact with underlying semantic web services in order to utilize their full power in your applications.