By Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez, Honghan Wu

This publication addresses the subject of exploiting enterprise-linked info with a particular

focus on wisdom development and accessibility inside of companies. It identifies the gaps among the necessities of company wisdom intake and “standard”

data eating applied sciences through analysing real-world use circumstances, and proposes the

enterprise wisdom graph to fill such gaps.

It presents concrete directions for successfully deploying linked-data graphs within

and throughout company enterprises. it's divided into 3 elements, targeting the key

technologies for developing, realizing and utilizing wisdom graphs.

Part 1 introduces simple historical past info and applied sciences, and offers a

simple structure to explain the most levels and projects required in the course of the lifecycle of data graphs. half 2 specializes in technical elements; it begins with state-of-the artwork knowledge-graph building methods, after which discusses exploration and exploitation suggestions in addition to complex question-answering themes relating wisdom graphs. finally, half three demonstrates examples of winning wisdom graph purposes within the media undefined, healthcare and cultural background, and provides conclusions and destiny visions.

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The syntax is quite straightforward. Put down the constant strings. Wherever you want to have a column value to be part of it, simply put the column name in the right position and surround it with curly brackets. The following example defines our customised project URIs using the Project_Id column as the variable part. [] rr : s u b j e c t M a p [ rr : t e m p l a t e " http :// abc . org / DB / P r o j e c t / ID /{ P r o j e c t _ I d }" ]. Logical Table In R2RML, the logical table is a way to enable the customised data extraction and transformation from the original database using SQL queries.

The term map is essentially a function which is capable of generating customised terms from data rows, which makes a domain ontology reuse possible. • Logical Table A logical table, as its name indicates, is a virtual table which is constructed from “real” tables. This table enables customised data extraction before doing the triple conversion, which meets the requirement of our third example. • Triple Maps This map mechanism is designed for the ability to specify how triples are generated from data rows.

D i r e c t o r . d i r e c t o r dbpedia - owl : b i r t h P l a c e < http :// d b p e d i a . org / r e s o u r c e / Italy > } LIMIT 100 The simple query mentioned above retrieves the first 100 movies having an Italian director. director) could be used to order results and OFFSET 10 may be added to skip initial items. Differently from SQL the FROM clause is optional, which can be used to specify the default RDF graph or the dataset to be used for matching. SPARQL also allows more complex queries which may include union, optional query parts, filters, value aggregation, path expressions, nested queries, etc.

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