GeoKnow: Making the Web an Exploratory Place for Geospatial Knowledge
The GeoKnow project aims to make geospatial data accessible on the Web of Data, transforming the Web into a place where geospatial data can be published, queried, reasoned, and interlinked, according to Linked Data principles.
Today decision makers in enterprises have to rely more and more on a variety of data sets that are internally but also externally available in heterogeneous formats. Therefore, intelligent processes are required to build an integrated knowledge base. Unfortunately, the adoption of the Linked Data lifecycle within enterprises, which targets the extraction, interlinking, publishing, and analytics of distributed data, lags behind the public domain due to the lack of frameworks which are efficient to deploy and easy to use. In this paper we present our adoption of the lifecycle through our generic, enterprise-ready Linked Data workbench. To judge its benefits, we describe its application within a real-world Customer Relationship Management (CRM) scenario. It shows (1) that sales employees could significantly reduce their workload and (2) that the integration of sophisticated Linked Data tools come with an obvious positive Return on Investment (ROI).
This book constitutes the refereed proceedings of the 6th Conference on Knowledge Engineering and the Semantic Web, KESW 2015, held in Moscow, Russia, in September/October 2015. The 17 revised full papers presented together with 6 short system descriptions were carefully reviewed and selected from 35 submissions. The papers address research issues related to semantic web, linked data, ontologies, natural language processing, knowledge representation.
The LOD Russia research project funded by the Ministry of Education aims to create a first Linked Open Data Set in Russia enabling scientists, researchers and commercial users to share, access, analyse and reuse knowledge related to scientific data. The position paper is highlighting challenges of the life-cycle management of LOD data, especially focuses on the process of entity linking and the creation of a unique identifier (UID) based on the concept of the Identification Knowledge Base (IKB).
The Republic of Tatarstan is one of the most economically developed regions of Russia. Large-scale projects implemented in the republic make high demands for labor resource security. Understanding of the status and trends of the dynamics of labor resource potential of the Republic of Tatarstan will allow the region to build a competent management of key factors for future economic development. The article describes the results of investigation of the dynamics of labor resource potential of the Republic of Tatarstan. It highlights an attempt to use cartographic research method in combination with the geostatistical methods of analysis of statistical data on the population based on the current capabilities of GIS.
The rapid growth of geospatial data in the world enables the implementation of data mining techniques to mine the patterns in geospatial data. In this paper the authors have applied the algorithms that were previously used for mining slightly changing patterns in time series to geospatial data of the real estate market. So the paper discusses mining the patterns that slightly change in space (instead of time). The paper uses data on the real estate market. The predicted variable (square meter price) is analyzed respective to the district, distance to the city center, stations of public transport, highways, shops, sports, entertainment, healthcare, education centers, offices, parks etc. The proposed approach for mining slightly changing patterns in geospatial data is highly applicable to any data with geo-tag, e.g. space image recognition, geo-targeted marketing etc.
Semantic web technologies promise to bring companies closer to their customers and deliver to consumers more relevant content than ever before. Two technologies in particular will help build sustainable advantage for the investor relations team. The first is natural language processing and second content enhancement. Intuitively, semantic content should help establish a higher quality of communication between information providers and consumers. This chapter describes the state-of-the-art in digital text information extraction, specifically the application of semantic technology to confront the challenges of the investor relations department. We discuss the roots of human language technology and ontology-driven information extraction and how such extracted semantic metadata can be used for better decision making, market monitoring and competitor intelligence. We will consider ontology as a sound semantic platform for defining the meaning of content and consequently supporting the prudent access to data for business intelligence. Examples are given on dynamic hypertext views, a solution that links different web pages together based on their semantic meaning. The foundation of the proposed solution relies on an ontology-driven information extraction approach, a framework that merges same entities and stores the semantic metadata in a knowledge base. This framework supports the complete transformation process, including web page crawling, the extraction of knowledge, the creation of unique identifiers and presentations offering access to the portal. In this context, we describe how these technologies are being used in real customer scenarios and compare the classical search approach to a more intelligent approach based on ontology and information extraction. In particular, we describe semantic indexing, building a knowledge base from various sources and give an introduction on how to create domain ontology based on customer queries. Then we tackle issues of merging information from text with semi-structured information from the Web, highlighting the relation to Linked Data using standards like RDF/XML. Finally, we present possible user interfaces which display the aggregated semantic metadata inside a portal and other third party software tools. The chapter concludes by looking beyond the current solution to how semantic technology will add more information in the near future, including a short survey of recent thinking that offers potential extensions to today’s model.
Spatial Data: the Needs of the Economy in the Context of Digitalization / E. Belogurova, V. Vorobyev, O. Gvozdev et al.; The Federal Service for State Registration, Cadastre and Cartography; National Research University Higher School of Economics; Institute for Scientiﬁ c Research of Aerospace Monitoring ”AEROCOSMOS“. – Moscow: HSE, 2020.
With an increased interest in machine processable data and with the progress of semantic technologies, many datasets are now published in the form of RDF triples for constituting the so-called Web of Data. Data can be queried using SPARQL but there are still needs for integrating, classifying and exploring the data for data analysis and knowledge discovery purposes. This research work proposes a new approach based on Formal Concept Analysis and Pattern Structures for building a pattern concept lattice from a set of RDF triples. This lattice can be used for data exploration and in particular visualized thanks to an adapted tool. The specific pattern structure introduced for RDF data allows to make a bridge with other studies on the use of structured attribute sets when building concept lattices. Our approach is experimentally validated on the classification of RDF data showing the efficiency of the underlying algorithms.
Data integration in enterprises is a crucial but at the same time costly and challenging problem. While business-critical information is stored in ERP, CRM, SCM and in Content Management systems the integration of such becomes even more critical when integrating with the growing information space on the Web. The IT industry has developed over the last decade integration solutions based on Master Data Management, Business Intelligence and the Service Oriented Architecture. However, we become increasingly aware that such technologies are not sufficient to ultimately solve all data integration challenges. Under the vision of context-aware services and integration we propose to apply the technology of the Linked Data paradigm. This approach seems to be promising, as scientists in the evolution of the Semantic Web have used it. We discuss Linked Data approaches in relation to the value chain and information integration of heterogeneous content and present an example of a CRM business process applying the Linked Data principles.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.