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Cross-Lingual Querying and Comparison of Linked Financial and Business Data

Cross-lingual querying of financial and business data from multi-lingual sources requires that inherent challenges posed by the diversity of financial concepts and languages used in different jurisdictions be addressed. Ontologies can be used to semantically align financial concepts and integrate financial facts with other company information from multilingual, semi-structured, and unstructured Open Data sources. Availability as Linked Data then allows cross-lingual interrogation of the interlinked multi-lingual data set. This paper presents how the use of semantics and Linked Data enables the alignment and integration of business and financial facts provided by the different European Business Registers. The demonstrator allows business users to query multilingual data, perform comparisons, and review generated financial metrics.

Accepting the XBRL Challenge with Linked Data for Financial Data Integration

Analysts spend a disproportionate amount of time with financial data curation before they are able to compare company performances in an analysis. The Extensible Business Reporting Language (XBRL) for annotating financial facts is suited for automatic processing to increase information quality in financial analytics. Still, XBRL does not solve the problem of data integration as required for a holistic view of companies. Semantic Web technologies promise benefits for financial data integration, yet, existing literature lacks concrete case studies. Here presented the Financial Information Observation System (FIOS) that uses Linked Data and multidimensional modeling based on the RDF Data Cube Vocabulary for accessing and representing relevant financial data. FIOS fulfills the information-seeking policy of “overview first, zoom and filter, then details on demand”, integrates yearly and quarterly balance sheets, daily stock quotes as well as company and industry background information and helps analysts creating their own analyses with Excel-like functionality.

Policy Intelligence in the Era of Social Computing: Towards a Cross-Policy Decision Support System

PADGETS presents a policy analysis framework developed through a process of interdisciplinary integration as well as through a process of end-users needs elicitation. The proposed framework constitutes the theoretical foundation for the Decision Support Component of a technological platform bringing together Social Media and System Dynamics simulation developed within the PADGETS project. The main novelties introduced have to do with the possibility to provide decision-makers with a set of concise, fresh, and relevant data in a cost-effective and easily understandable way.

The Global R&D System

Organized knowledge is often considered to be a key factor in the evolution of the man-made world. All civilizations have rested upon a continuous flow of information, diversified and instrumental, in order to effectively utilize and further develop the forces of production. New knowledge has always been needed to better control the natural and social environments.

Scientific and technical information (STI) is made by and for people. Even if we believe in the universality of science and technology, different people may perceive STI in a variety of ways. Already because of the overflow of information, the task to grasp the meaning of STI and to judge its credibility, its exhaustiveness, its applicability, as well as its limitation for development work is for the industrialized countries not only formidable, but also a task which gives rise to different interpretations, and even contradictions.

Cyber-Physical-Social Intelligence involves

  • Human-machine-nature symbiosis – a reciprocal mechanism for structuring and evolving reality
  • Multi-dimensional methodology for exploring the emerging cyber-physical-social space

The interactions between philosophy, social sciences, and computer science around social intelligence are manifold, and many concepts and theories from social science have found their way into artificial intelligence and agent-based research. In the latter, coordination and cooperation between largely independent, autonomous computational entities are modeled. Conversely, logical and computational models and their implementations have been used in the social sciences to help improve simulations, hypotheses, and theories. Among the most prominent subjects at the interface are action and agency, communicative interaction, group attitudes, socio-technical epistemology, and social coordination. In computer science, these concepts from social science are sometimes deployed at a more metaphorical level rather than in the form of rigorous implementations of the genuine concepts and their corresponding theories. Equally, the computer models used in social science are not always convincing.

“Cyber-Physical-Social Intelligence emerges and evolves with interactions among cyberspace, physical space, social space, and mental space. It may be the Computing with Known and Unknown.”

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