Data Integration for Open Data on the Web

In this lecture we will discuss and introduce challenges of integrating openly available Web data and how to solve them. Firstly, while we will address this topic from the viewpoint of Semantic Web research, not all data is readily available as RDF or Linked Data, so we will give an introduction to different data formats prevalent on the Web, namely, standard formats for publishing and exchanging tabular, tree-shaped, and graph data. Secondly, not all Open Data is really completely open, so we will discuss and address issues around licences, terms of usage associated with Open Data, as well as documentation of data provenance. Thirdly, we will discuss issues connected with (meta-)data quality issues associated with Open Data on the Web and how Semantic Web techniques and vocabularies can be used to describe and remedy them. Fourth, we will address issues about searchability and integration of Open Data and discuss in how far semantic search can help to overcome these. We close with briefly summarizing further issues not covered explicitly herein, such as multi-linguality, temporal aspects (archiving, evolution, temporal querying), as well as how/whether OWL and RDFS reasoning on top of integrated open data could be help

Towards OpenMath Content Dictionaries as Linked Data

"The term 'Linked Data' refers to a set of best practices for publishing and connecting structured data on the web". Linked Data make the Semantic Web work practically, which means that information can be retrieved without complicated lookup mechanisms, that a lightweight semantics enables scalable reasoning, and that the decentral nature of the Web is respected. OpenMath Content Dictionaries (CDs) have the same characteristics - in principle, but not yet in practice. The Linking Open Data movement has made a considerable practical impact: Governments, broadcasting stations, scientific publishers, and many more actors are already contributing to the "Web of Data". Queries can be answered in a distributed way, and services aggregating data from different sources are replacing hard-coded mashups. However, these services are currently entirely lacking mathematical functionality. I will discuss real-world scenarios, where today's RDF-based Linked Data do not quite get their job done, but where an integration of OpenMath would help - were it not for certain conceptual and practical restrictions. I will point out conceptual shortcomings in the OpenMath 2 specification and common bad practices in publishing CDs and then propose concrete steps to overcome them and to contribute OpenMath CDs to the Web of Data.Comment: Presented at the OpenMath Workshop 2010, http://cicm2010.cnam.fr/om

The RCSB Protein Data Bank: views of structural biology for basic and applied research and education.

The RCSB Protein Data Bank (RCSB PDB, http://www.rcsb.org) provides access to 3D structures of biological macromolecules and is one of the leading resources in biology and biomedicine worldwide. Our efforts over the past 2 years focused on enabling a deeper understanding of structural biology and providing new structural views of biology that support both basic and applied research and education. Herein, we describe recently introduced data annotations including integration with external biological resources, such as gene and drug databases, new visualization tools and improved support for the mobile web. We also describe access to data files, web services and open access software components to enable software developers to more effectively mine the PDB archive and related annotations. Our efforts are aimed at expanding the role of 3D structure in understanding biology and medicine

Computational toxicology using the OpenTox application programming interface and Bioclipse

BACKGROUND: Toxicity is a complex phenomenon involving the potential adverse effect on a range of biological functions. Predicting toxicity involves using a combination of experimental data (endpoints) and computational methods to generate a set of predictive models. Such models rely strongly on being able to integrate information from many sources. The required integration of biological and chemical information sources requires, however, a common language to express our knowledge ontologically, and interoperating services to build reliable predictive toxicology applications. FINDINGS: This article describes progress in extending the integrative bio- and cheminformatics platform Bioclipse to interoperate with OpenTox, a semantic web framework which supports open data exchange and toxicology model building. The Bioclipse workbench environment enables functionality from OpenTox web services and easy access to OpenTox resources for evaluating toxicity properties of query molecules. Relevant cases and interfaces based on ten neurotoxins are described to demonstrate the capabilities provided to the user. The integration takes advantage of semantic web technologies, thereby providing an open and simplifying communication standard. Additionally, the use of ontologies ensures proper interoperation and reliable integration of toxicity information from both experimental and computational sources. CONCLUSIONS: A novel computational toxicity assessment platform was generated from integration of two open science platforms related to toxicology: Bioclipse, that combines a rich scriptable and graphical workbench environment for integration of diverse sets of information sources, and OpenTox, a platform for interoperable toxicology data and computational services. The combination provides improved reliability and operability for handling large data sets by the use of the Open Standards from the OpenTox Application Programming Interface. This enables simultaneous access to a variety of distributed predictive toxicology databases, and algorithm and model resources, taking advantage of the Bioclipse workbench handling the technical layers

ODINet - Online Data Integration Network

Along with the expansion of Open Data and according to the latest EU directives for open access, the attention of public administration, research bodies and business is on web publishing of data in open format. However, a specialized search engine on the datasets, with similar role to that of Google for web pages, is not yet widespread. This article presents the Online Data Integration Network (ODINet) project, which aims to define a new technological framework for access to and online dissemination of structured and heterogeneous data through innovative methods of cataloging, searching and display of data on the web. In this article, we focus on the semantic component of our platform, emphasizing how we built and used ontologies. We further describe the Social Network Analysis (SNA) techniques we exploited to analyze it and to retrieve the required information. The testing phase of the project, that is still in progress, has already demonstrated the validity of the ODINet approach

Halcyon -- A Pathology Imaging and Feature analysis and Management System

Halcyon is a new pathology imaging analysis and feature management system based on W3C linked-data open standards and is designed to scale to support the needs for the voluminous production of features from deep-learning feature pipelines. Halcyon can support multiple users with a web-based UX with access to all user data over a standards-based web API allowing for integration with other processes and software systems. Identity management and data security is also provided.Comment: 15 pages, 11 figures. arXiv admin note: text overlap with arXiv:2005.0646