Related papers: Restpark: Minimal RESTful API for Retrieving RDF T…
RESTful APIs based on HTTP are one of the most important ways to make data and functionality available to applications and software services. However, the quality of the API design strongly impacts API understandability and usability, and…
In recent years, artificial intelligence (AI) has aroused much attention among both industrial and academic areas. However, building and maintaining efficient AI systems are quite difficult for many small business companies and researchers…
Current approaches for knowledge graph construction with RML focus on full RDF graph materialization without considering user queries. As a result, mapping engines are inefficient in dynamic query environments, materializing large graphs…
Developing and testing modern RDF-based applications often requires access to RDF datasets with certain characteristics. Unfortunately, it is very difficult to publicly find domain-specific knowledge graphs that conform to a particular set…
The Resource Description Framework (RDF) is a framework for describing metadata, such as attributes and relationships of resources on the Web. Machine learning tasks for RDF graphs adopt three methods: (i) support vector machines (SVMs)…
GraphQL provides a schema-based, strongly typed query language that enables highly efficient client-server communication. This paper introduces GraphQLify, an automated framework designed to migrate existing REST APIs to GraphQL. Unlike…
With the ever proliferating size and scale of the WWW [1] efficient ways of exploring content are of increasing importance. How can we efficiently retrieve information from it through crawling? And in this era of tera and multi-core…
The Web of Linked Data is composed of tons of RDF documents interlinked to each other forming a huge repository of distributed semantic data. Effectively querying this distributed data source is an important open problem in the Semantic Web…
In recent years, the open source operating system OpenWrt has become a popular option for replacing proprietary firmware on networking devices such as home routers or access points. In order to configure an OpenWrt system, like setting up…
RDF data is often treated as incomplete, following the Open-World Assumption. On the other hand, SPARQL, the standard query language over RDF, usually follows the Closed-World Assumption, assuming RDF data to be complete. This gives rise to…
The abundance of the data in the Internet facilitates the improvement of extraction and processing tools. The trend in the open data publishing encourages the adoption of structured formats like CSV and RDF. However, there is still a…
Modern web services routinely provide REST APIs for clients to access their functionality. These APIs present unique challenges and opportunities for automated testing, driving the recent development of many techniques and tools that…
Segment Routing is a form of loose source routing. It provides the ability to include a list of instructions (called segments), in the packet headers. The Segment Routing architecture has been first implemented with the MPLS dataplane and…
Data visualisation assists domain experts in understanding their data and helps them make critical decisions. Enhancing their cognitive insight essentially relies on the capability of combining domain-specific semantic information with…
This paper introduces the L-ReLF (Low-Resource Lexical Framework), a novel, reproducible methodology for creating high-quality, structured lexical datasets for underserved languages. The lack of standardized terminology, exemplified by…
This article introduces the Data Retrieval Web Engine (also referred to as doctor web), a flexible and modular tool for extracting structured data from web pages using a simple query language. We discuss the engineering challenges addressed…
REpresentational State Transfer (REST) is considered as one standard software architectural style to build web APIs that can integrate software systems over the internet. However, while connecting systems, RESTful APIs might also break the…
Various research domains use machine learning approaches because they can solve complex tasks by learning from data. Deploying machine learning models, however, is not trivial and developers have to implement complete solutions which are…
What should a data integration framework for knowledge engineers look like? Recent research on Knowledge Graph construction proposes the design of a fa\c{c}ade, a notion borrowed from object-oriented software engineering. This idea is…
The modern day semantic applications store data as Resource Description Framework (RDF) data.Due to Proliferation of RDF Data, the efficient management of huge RDF data has become essential. A number of approaches pertaining to both…