The semantic architecture of the World-Wide Molecular Matrix (WWMM).

The World-Wide Molecular Matrix (WWMM) is a ten year project to create a peer-to-peer (P2P) system for the publication and collection of chemical objects, including over 250, 000 molecules. It has now been instantiated in a number of repositories which include data encoded in Chemical Markup Language (CML) and linked by URIs and RDF. The technical specification and implementation is now complete. We discuss the types of architecture required to implement nodes in the WWMM and consider the social issues involved in adoption.

First-principles thermochemistry for gas phase species in an industrial rutile chlorinator.

This work presents thermochemical data for possible gas phase intermediate species in an industrial rutile chlorinator. An algorithm developed for previous work is employed to ensure that all possible species are considered, reducing the number of important species neglected. Thermochemical data and enthalpies of formation are calculated for 22 new species using density functional theory, post Hartree-Fock coupled cluster calculations, and statistical mechanics. Equilibrium calculations are performed to identify whether any Ti/C intermediates are likely to be important to the high temperature industrial process. These new species are not present at high concentration in the exit stream. It is therefore likely that the two chemical processes do not interact. Rather, the Cl2 rapidly reacts with the solid TiO2 to form TiCl4 and O2. The latter then reacts with the solid C to form CO and CO2 and provide the heat. Data for all the new species is provided as Supporting Information. Finally, a new methodology for data collaboration is investigated in which the data is made openly accessible using the resource description framework. Example scripts are provided to demonstrate how to query and retrieve the data automatically.

SPECTRa-T: machine-based data extraction and semantic searching of chemistry e-theses.

The SPECTRa-T project has developed text-mining tools to extract named chemical entities (NCEs), such as chemical names and terms, and chemical objects (COs), e.g., experimental spectral assignments and physical chemistry properties, from electronic theses (e-theses). Although NCEs were readily identified within the two major document formats studied, only the use of structured documents enabled identification of chemical objects and their association with the relevant chemical entity (e.g., systematic chemical name). A corpus of theses was analyzed and it is shown that a high degree of semantic information can be extracted from structured documents. This integrated information has been deposited in a persistent Resource Description Framework (RDF) triple-store that allows users to conduct semantic searches. The strength and weaknesses of several document formats are reviewed.

SPECTRa: the deposition and validation of primary chemistry research data in digital repositories.

The SPECTRa (Submission, Preservation and Exposure of Chemistry Teaching and Research Data) project has investigated the practices of chemists in archiving and disseminating primary chemical data from academic research laboratories. To redress the loss of the large amount of data never archived or disseminated, we have developed software for data publication into departmental and institutional Open Access digital repositories (DSpace). Data adhering to standard formats in selected disciplines (crystallography, NMR, computational chemistry) is transformed to XML (CML, Chemical Markup Language) which provides added validation. Context-specific chemical metadata and persistent Handle identifiers are added to enable long-term data reuse. It was found essential to provide an embargo mechanism, and policies for operating this and other processes are presented.