Implementation of an open chemistry knowledge base with a Semantic Wiki

Network big data refers to the massive data generated via interaction and fusion of the ternary human-machine-thing universe in the cyberspace and available on the Internet.It has a few typical features,such as multi-sourced,heterogeneous,interactive,bursty,and noisy.It contains mainly unstructured data,and has strong real-timeness. Network big data implicitly contains tremendous highly-interconnected knowledge.Building up open Web oriented large-scale knowledge bases is an effective means for obtaining rich knowledge from network big data.This paper compares both the domestic and international mainstream open Web knowledge bases.We specifically analyze the core techniques and methods for constructing open Web knowledge bases,fusing multi-sourced knowledge,and updating the knowledge bases.Furthermore,we summarize the research status and main issues of open Web knowledge base based information search,data mining,and system applications from different aspects,including user intension understanding,query extension,semantic QA,clue mining,relationship referencing,and prediction of relationships and attributes.Finally,we look into the development trends and main challenges of open Web knowledge bases.

Quality management has become a strategic issue for organisations and is very valuable to produce quality software. However, quality management systems (QMS) are not easy to implement and maintain. The authors' experience shows the benefits of developing a QMS by first formalising it using semantic web ontologies and then putting them into practice through a semantic wiki. The QMS ontology that has been developed captures the core concepts of a traditional QMS and combines them with concepts coming from the MPIu+a development process model, which is geared towards obtaining usable and accessible software products. Then, the ontology semantics is directly put into play by a semantics-aware tool, the Semantic MediaWiki. The developed QMS tool is being used for 2 years by the GRIHO research group, where it has manages almost 50 software development projects taking into account the quality management issues. It has also been externally audited by a quality certification organisation. Its users are very satisfied with their daily work with the tool, which manages all the documents created during project development and also allows them to collaborate, thanks to the wiki features.

As more and more open knowledge resources become available, it is interesting to explore opportunities of enhancing autonomous agents' capacities by utilizing the knowledge in these resources, instead of hand-coding knowledge for agents. A major challenge towards this goal lies in the translation of the open knowledge organized in multiple modes, unstructured or semi-structured, into the internal representations of agents. In this paper we present a set of multi-mode NLP techniques to formalize the open knowledge for autonomous agents. Two case studies are reported in which our robot, equipped with the multi-mode NLP techniques, succeeded in acquiring knowledge from the microwave oven manual and from the open knowledge database, OMICS, and solving problems that could not be solved before the robot acquired the knowledge. Experiments for evaluating the performance of our approach show that our approach is promising.

In comparison to metal complexes, organic photosensitive dyes employed in photocatalytic hydrogen production exhibit promising developmental prospects. Utilizing the organic dye molecule TA+0 as the foundational structure, a series of innovative organic dyes, denoted as TA1-1 to TA2-6, were systematically designed. Employing first-principles calculations, we methodically explored the modifying effects of diverse electron-donating groups on the R1 and R2 positions to assess their application potential. Our findings reveal that, relative to the experimentally synthesized TATA+03, the TA2-6 molecule boasts a spatial structure conducive to intramolecular electron transfer, showcasing the most negative reduction potential (Ered = −2.11 eV) and the maximum reaction driving force (△G02 = −1.26 eV). This configuration enhances its compatibility with the reduction catalyst, thereby facilitating efficient hydrogen evolution. The TA2-6 dye demonstrates outstanding photophysical properties and a robust solar energy capture capacity. Its maximum molar extinction coefficient (ε) stands at 2.616 × 104 M−1·cm−1, representing a remarkable 292.8% improvement over TATA+03. In conclusion, this research underscores the promising potential of the TA2-6 dye as an innovative organic photosensitizer, positioning it as an efficacious component in homogeneous photocatalytic systems.

We are currently witnessing an explosion of advances in database technology, that cover all phases of database application design: non-functional requirements, conceptual modeling, logical modeling, deployment, physical design and exploitation. Researchers and engineers cooperate to integrate these advances in the database design. Their proposed solutions have to be confronted with similar studies whose results have been either published in scientific papers or on specific websites such as that of TPC (the Transaction Processing Council). Recently, several researchers have highlighted difficulties in reproducing the results of existing studies. As a consequence, certain research communities require that the environment and the results of the testing activities have to be published in order to facilitate their reproduction, to publish their simulator environments, in order to allow evaluators to perform by their own the experiments. This is quite similar to the Volkswagen fake pollution controls scandal. In this paper, we firstly, advocate the transparency of testing in the database field. Secondly, we propose the use of a repository dedicated to store testing environment and results. The environment includes used data sets, deployment platform, non-functional requirements, used algorithms, hypotheses, etc. and the results completed with their measurement units.

Semantic web i.e. web with meanings attached to it is getting popular these days. One of the most common application of this technology is question answering system which takes natural language input from user in the form of questions and returns answer from open domain knowledge base such as DBpedia Freebase etc. This paper presents a regex-based approach for answering factoid questions from a Tourism QA system. The system first detects the type of question and converts it into a NL triple. Next, it generates SPARQL query based on the object and predicate identified in the first step and returns the answer to the user. The results show an overall accuracy of 80% from TREC 8 and 9 questions which are related to tourism domain.

Bridging the gap between linked open data-based recommender systems and distributed representations

A figure from the article, outlining the idea of using SPARQL queries to extract data from the open knowledge base. As a reader of my blog, you know I have been doing quite some research where Wikidata has some role. I am preparing a paper on the work I have done around chemicals in Wikidata, based on what I presented at the ICCS with a poster.

Wikidata is the central data management platform of Wikipedia. By the efforts of thousands of volunteers, the project has produced a large, open knowledge base with many interesting applications. The data is highly interlinked and connected to many other datasets, but it is also very rich, complex, and not available in RDF. To address this issue, we introduce new RDF exports that connect Wikidata to the Linked Data Web. We explain the data model of Wikidata and discuss its encoding in RDF. Moreover, we introduce several partial exports that provide more selective or simplified views on the data. This includes a class hierarchy and several other types of ontological axioms that we extract from the site. All datasets we discuss here are freely available online and updated regularly.KeywordsLink DataClass HierarchyQuery AnsweringExternal DatasetSite LinkThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Natural Language Inference (NLI) is fundamental to many Natural Language Processing (NLP) applications including semantic search and question answering. The NLI problem has gained significant attention due to the release of large scale, challenging datasets. Present approaches to the problem largely focus on learning-based methods that use only textual information in order to classify whether a given premise entails, contradicts, or is neutral with respect to a given hypothesis. Surprisingly, the use of methods based on structured knowledge – a central topic in artificial intelligence – has not received much attention vis-a-vis the NLI problem. While there are many open knowledge bases that contain various types of reasoning information, their use for NLI has not been well explored. To address this, we present a combination of techniques that harness external knowledge to improve performance on the NLI problem in the science questions domain. We present the results of applying our techniques on text, graph, and text-and-graph based models; and discuss the implications of using external knowledge to solve the NLI problem. Our model achieves close to state-of-the-art performance for NLI on the SciTail science questions dataset.

News360 is the news aggregation system with personalization. Initially created for English, it was recently adapted for German. In this paper, we show that it is possible to adapt such systems automatically, without any manual labour, using only open knowledge bases and Wikipedia dumps. We propose a method for adaptation named entity linking and classification to target language. We show that even though the quality of German system is worse than the quality of English one, this method allows to bootstrap a new language for the system very quickly and fully automatically.

A management knowledge graph approach for critical infrastructure protection: Ontology design, information extraction and relation prediction

Reports results of a questionnaire sur vey of UK academic libraries to deter mine the level of use of online public access catalogues (OPACs) and the development of inhouse subject indexes. Seventy-five respondents reported having commercial systems and seven reported inhouse systems. Data includes: named systems in use and numbers of libraries using each system; percentages of bibliographic records in machine-readable format; types of materials; and record formats (UKMARC, LC MARC etc). Reports the most common access points for searching the OPACs (author, key word), methods of generating terms to be used for subject searching, sub ject heading sources (LCSH, MeSH, PRECIS) and classification schemes (Dewey, UDC). Results show that all universities and polytechnics now have OPACs and only the smaller colleges do not. OPACs are moving towards comprehensive coverage of academic library stocks with the MARC record the most popular for mat. The three main subject access strategies involve: Library of Congress Subject Headings; inhouse strategies; and strategies not based on controlled terminology. Draws heav ily on the results of an earlier survey by Fran Slack (1988) Vine,(72) (November), 8-15.

<p>Essential Biodiversity Variables (EBVs) are harmonized biodiversity variables and their asssociated measurements needed for developing indicators of global biodiversity change. EBVs can serve the important purpose of aligning biodiversity monitoring efforts, much as Essential Climatic Variables (ECVs) help align allied efforts in climate science. One of six initially proposed EBV classes is devoted to species' traits, since traits form the crucial link between the evolutionary history of organisms, their assembly into communities, and the nature and dynamic functioning of ecosystems. Despite their importance, prevalence, and scientific promise, the biodiversity community is still developing the conceptual, informatics, technical, and legal frameworks required for the large scale implementation and uptake. As part of an international consortium called GLOBIS-B, and in coordination with the The Group on Earth Observations Biodiversity Observation Network (GEO BON; geobon.org), we report on recent efforts to synthesize current efforts in trait data collection and trait datasets, computational workflows, ways to standardize data and metadata, and assessments of the openness and accessibility of existing species trait datasets. Members of the GLOBIS-B (www.globis-b.eu/) consortium also produced a set of candidate EBVs within the broader trait class ('Phenology', 'Organism morphology', 'Reproduction', 'Physiology' and 'Movement'). In this presentation, we begin by introducing the concept of EBVs, the current working definition of traits in the context of the EBV process, and workflows that have been developed for other EBV classes ('Species Populations') and the importance of standardizing EBV classes and the trait class, in particular. Building on this introduction, we discuss how the EBV concept is operationalized, focusing on workflows for trait integration, and the importance of data and metadata standards,following work from Kissling et al. 2017 (http://onlinelibrary.wiley.com/doi/10.1111/brv.12359/full). On the legal front, we suggest that the Creative Commons (CC) framework provides effective tools for designating legally interoperable and open data, especially when trait data are in the public domain (CC0, CC PDM) or assigned with a CC BY license, and metadata citation and other forms of attribution are available in both human and machine-readable form. We also suggest how EBVs can inform policy at national and global scales. Moving forward, renewed efforts of repeated trait data collection as well as standardised protocols for data and metadata collection are needed to improve the empirical basis of species traits EBVs. Moreover, open data as well as computational workflows are required for comprehensively assessing progress towards conservation policy targets and sustainable development goals. We conclude with a call to action for the TDWG community to consider their role in further developing, implementing, and scaling biodiversity monitoring under the EBV framework.</p>

Quantitative social research has been considered necessary to understand the nature of our past and present society and its problems, carry out the research process, and understand the impact of social programs. For almost two centuries, social researchers have utilized governmental statistics to examine a wide range of social phenomena on individuals and social structures and to offer competing analyses of social research and policy. As early as 1828, Melchiorre Gioja, in his, Filosfia della Statistica, indicated that the essential scope of social science also embraced the collection of data on a wide range of social phenomena, such as affluence, poverty, knowledge, ignorance, happiness, civilization, and morality, "the set of data relative to a country, which in the daily conduct of affairs, can be useful to each one or to the majority of its citizens, or to its government, which is their agent, delegate, or representative..." In the late nineteenth century, Durkheim relied on published summaries of statistical data to illuminate the causes of suicide. Since the beginning of the twentieth century, technological and intellectual advances have made possible the recording of these statistics in machine readable form, the collection of new types of data, and increased utilization of governmental records.