A Flexible Graph-Based Data Model Supporting Incremental Schema Design and Evolution

Web data is characterized by a great structural diversity as well as frequent changes, which poses a great challenge for web applications based on that data. We want to address this problem by developing a schema-optional and flexible data model that supports the integration of heterogenous and volatile web data. Therefore, we want to rely on graph-based models that allow to incrementally extend the schema by various information and constraints. Inspired by the on-going web 2.0 trend, we want users to participate in the design and management of the schema. By incrementally adding structural information, users can enhance the schema to meet their very specific requirements

S2ST: A Relational RDF Database Management System

The explosive growth of RDF data on the Semantic Web drives the need for novel database systems that can efficiently store and query large RDF datasets. To achieve good performance and scalability of query processing, most existing RDF storage systems use a relational database management system as a backend to manage RDF data. In this paper, we describe the design and implementation of a Relational RDF Database Management System. Our main research contributions are: (1) We propose a formal model of a Relational RDF Database Management System (RRDBMS), (2) We propose generic algorithms for schema, data and query mapping, (3) We implement the first and only RRDBMS, S2ST, that supports multiple relational database management systems, user-customizable schema mapping, schema-independent data mapping, and semantics-preserving query translation

A Shared Ontology Approach to Semantic Representation of BIM Data

Architecture, engineering, construction and facility management (AEC-FM) projects involve a large number of participants that must exchange information and combine their knowledge for successful completion of a project. Currently, most of the AEC-FM domains store their information about a project in text documents or use XML, relational, or object-oriented formats that make information integration difficult. The AEC-FM industry is not taking advantage of the full potential of the Semantic Web for streamlining sharing, connecting, and combining information from different domains. The Semantic Web is designed to solve the information integration problem by creating a web of structured and connected data that can be processed by machines. It allows combining information from different sources with different underlying schemas distributed over the Internet. In the Semantic Web, all data instances and data schema are stored in a graph data store, which makes it easy to merge data from different sources. This paper presents a shared ontology approach to semantic representation of building information. The semantic representation of building information facilitates finding and integrating building information distributed in several knowledge bases. A case study demonstrates the development of a semantic based building design knowledge base

An XML Based Architecture for Sharing Heterogeneous Models in Web and Distributed Computing Environments

Model management emerged in the mid-seventies in the context of managing models in decision support systems (DSS). With the recent advances in computer and telecommunication technologies, organizations are ever increasingly dependent on management models for data analysis and decision support. Accordingly, the number and complexity of management models and of modeling platforms dramatically increased rendering such models a corporate (and national) resource. With the advent of the Web and distributed computing environments, there is also an increasing demand to share these often heterogeneous models over corporate intranets as well as the Web. To this end, this paper presents an XML-based architecture for sharing heterogeneous models in Web and distributed computing environments. The architecture includes an XML schema for representing models. The schema is based on the structured modeling paradigm as a formal mathematical environment for conceiving, representing and manipulating a wide variety of models. The architecture allows different types of models, developed in a variety of modeling platform to be represented in a standardized format and shared over the Web. The paper demonstrates the proposed architecture through a case study

Updating database schemas without breaking the UI: Modeling using cognitive semantic categories

PublishedData management user interfaces are ubiquitous in information systems and web-based applications. From the oldest spreadsheet to the most modern database, end users and administrators alike have interacted with tabular data. Usually, each concept is represented by a table and columns. Change to the structure of each concept requires structural change to the tables and columns, which is costly. Tailor-made database and web applications may overcome this obstacle by designing UIs on top of the data layer, providing some degree of data independence. However, changes in their schemas do not automatically propagate into the user interface, and so their maintenance is expensive. In this paper we present a user interface that lets the end user alter the schema without the need for programming skills, eliminating the need for expensive software maintenance. To this end we propose an automatically generated user interface to include schema and data management functions. We built and evaluated an Adaptive Information System user interface (AIS UI), incorporating schema evolution functionality. In usability testing, firsttime users were able to perform various data management tasks equally fast or faster than users using Microsoft Access, and on average ̃43% faster than users using Microsoft Excel. Task completion rates using the AIS significantly exceeded those using Microsoft Access and were comparable (>95%) with those using Microsoft Excel. Copyright © 2014 ACM 978-1-4503-2725-1/14/06

Integration-oriented ontology

The purpose of an integration-oriented ontology is to provide a conceptualization of a domain of interest for automating the data integration of an evolving and heterogeneous set of sources using Semantic Web technologies. It links domain concepts to each of the underlying data sources via schema mappings. Data analysts, who are domain experts but not necessarily have technical data management skills, pose ontology-mediated queries over the conceptualization, which are automatically translated to the appropriate query language for the sources at hand. Following well-established rules when designing schema mappings allows to automate the process of query rewriting and execution.Postprint (author's final draft

Ontology-based data access with databases: a short course

Ontology-based data access (OBDA) is regarded as a key ingredient of the new generation of information systems. In the OBDA paradigm, an ontology defines a high-level global schema of (already existing) data sources and provides a vocabulary for user queries. An OBDA system rewrites such queries and ontologies into the vocabulary of the data sources and then delegates the actual query evaluation to a suitable query answering system such as a relational database management system or a datalog engine. In this chapter, we mainly focus on OBDA with the ontology language OWL 2QL, one of the three profiles of the W3C standard Web Ontology Language OWL 2, and relational databases, although other possible languages will also be discussed. We consider different types of conjunctive query rewriting and their succinctness, different architectures of OBDA systems, and give an overview of the OBDA system Ontop

WIST: toolkit for rapid, customized LIMS development

Summary: Workflow Information Storage Toolkit (WIST) is a set of application programming interfaces and web applications that allow for the rapid development of customized laboratory information management systems (LIMS). WIST provides common LIMS input components, and allows them to be arranged and configured using a flexible language that specifies each component's visual and semantic characteristics. WIST includes a complete set of web applications for adding, editing and viewing data, as well as a powerful setup tool that can build new LIMS modules by analyzing existing database schema