Cross-Lingual and Cross-Chronological Information Access to Multilingual Historical Documents

In this chapter, we present our work in realizing information access across different languages and periods. Nowadays, digital collections of historical documents have to handle materials written in many different languages in different time periods. Even in a particular language, there are significant differences over time in terms of grammar, vocabulary and script. Our goal is to develop a method to access digital collections in a wide range of periods from ancient to modern. We introduce an information extraction method for digitized ancient Mongolian historical manuscripts for reducing labour-intensive analysis. The proposed method performs computerized analysis on Mongolian historical documents. Named entities such as personal names and place names are extracted by employing support vector machine. The extracted named entities are utilized to create a digital edition that reflects an ancient Mongolian historical manuscript written in traditional Mongolian script. The Text Encoding Initiative guidelines are adopted to encode the named entities, transcriptions and interpretations of ancient words. A web-based prototype system is developed for utilizing digital editions of ancient Mongolian historical manuscripts as scholarly tools. The proposed prototype has the capability to display and search traditional Mongolian text and its transliteration in Latin letters along with the highlighted named entities and the scanned images of the source manuscript

How Large Is the Metabolome? A Critical Analysis of Data Exchange Practices in Chemistry

Calculating the metabolome size of species by genome-guided reconstruction of metabolic pathways misses all products from orphan genes and from enzymes lacking annotated genes. Hence, metabolomes need to be determined experimentally. Annotations by mass spectrometry would greatly benefit if peer-reviewed public databases could be queried to compile target lists of structures that already have been reported for a given species. We detail current obstacles to compile such a knowledge base of metabolites.As an example, results are presented for rice. Two rice (oryza sativa) subspecies have been fully sequenced, oryza japonica and oryza indica. Several major small molecule databases were compared for listing known rice metabolites comprising PubChem, Chemical Abstracts, Beilstein, Patent databases, Dictionary of Natural Products, SetupX/BinBase, KNApSAcK DB, and finally those databases which were obtained by computational approaches, i.e. RiceCyc, KEGG, and Reactome. More than 5,000 small molecules were retrieved when searching these databases. Unfortunately, most often, genuine rice metabolites were retrieved together with non-metabolite database entries such as pesticides. Overlaps from database compound lists were very difficult to compare because structures were either not encoded in machine-readable format or because compound identifiers were not cross-referenced between databases.We conclude that present databases are not capable of comprehensively retrieving all known metabolites. Metabolome lists are yet mostly restricted to genome-reconstructed pathways. We suggest that providers of (bio)chemical databases enrich their database identifiers to PubChem IDs and InChIKeys to enable cross-database queries. In addition, peer-reviewed journal repositories need to mandate submission of structures and spectra in machine readable format to allow automated semantic annotation of articles containing chemical structures. Such changes in publication standards and database architectures will enable researchers to compile current knowledge about the metabolome of species, which may extend to derived information such as spectral libraries, organ-specific metabolites, and cross-study comparisons