2021년 2월 17일 (수) 08:10에 Pythagoras0님의 편집

2021-02-17T08:10:07Z

Pythagoras0: /* 메타데이터 */ 새 문단

2020-12-26T12:18:36Z

메타데이터: 새 문단

Pythagoras0: /* 노트 */ 새 문단

2020-12-21T10:18:43Z

노트: 새 문단

새 문서

== 노트 ==

===위키데이터===
* ID : [https://www.wikidata.org/wiki/Q54871 Q54871]
===말뭉치===
# A query in SPARQL consists of a SELECT clause to specify the variables to return and a WHERE clause to specify which data to match in the graph.<ref name="ref_a4354a41">[https://docs.aws.amazon.com/neptune/latest/userguide/access-graph-sparql.html Accessing the Neptune graph with SPARQL]</ref>
# Set up your reverse proxy to direct requests to the SPARQL-proxy.<ref name="ref_b91594cb">[https://github.com/dbcls/sparql-proxy dbcls/sparql-proxy: SPARQL-proxy: provides cache, job control, and logging for any SPARQL endpoint]</ref>
# If enabled, content negotiation will be disabled; spaql-proxy will always use application/sparql-results+json .<ref name="ref_b91594cb" />
# RDF is the standardized, graph-based data model of the semantic web and SPARQL its query and update language.<ref name="ref_e517f5c7">[https://www.wolfram.com/language/12/rdf-and-sparql/ RDF and SPARQL: New in Wolfram Language 12]</ref>
# In addition to support for "query strings", Version 12 provides a symbolic representation of SPARQL that facilitates writing programs that generate or operate on SPARQL.<ref name="ref_e517f5c7" />
# SPARQL also allows you to query and combine data from a variety of SPARQL endpoints, providing a valuable low-cost alternative to building your own data warehouse.<ref name="ref_df3f2177">[https://www.uniprot.org/help/sparql SPARQL for UniProt]</ref>
# The UniProt SPARQL endpoint is free to use.<ref name="ref_df3f2177" />
# The SPARQL Protocol and RDF Query Language (a recursive acronym, since it contains itself) is a language for formulating queries over RDF data.<ref name="ref_4455d5b5">[https://www.futurelearn.com/courses/linked-data/0/steps/16082 Introducing SPARQL: The standard query language for the Semantic Web]</ref>
# Comparing SPARQL with SQL, the key difference is that it is designed for retrieving information from sets of triples, rather than from data organised into relations (i.e., tables).<ref name="ref_4455d5b5" />
# In the next step, there is an exercise in which you will have an opportunity to formulate your first SPARQL queries.<ref name="ref_4455d5b5" />
# Similar to SQL for databases, SPARQL allows us to carry out queries on RDF data.<ref name="ref_4455d5b5" />
# On http://sparql.wikipathways.org/ WikiPathways content is replicated in a SPARQL endpoint.<ref name="ref_f74d563f">[https://www.wikipathways.org/index.php/Help:WikiPathways_Sparql_queries Help:WikiPathways Sparql queries]</ref>
# These prefixes are automatically used in the SPARQL Endpoint.<ref name="ref_f74d563f" />
# Of course, this can give false positives, because genes can be incorrectly marked as metabolite in some pathway, but that is another SPARQL query.<ref name="ref_f74d563f" />
# The following queries are run on the WikiPathways SPARQL end point.<ref name="ref_f74d563f" />
# URL Parameters query A URL-encoded SPARQL query operation.<ref name="ref_33c426c6">[http://docs.marklogic.com/REST/GET/v1/graphs/sparql sparql — MarkLogic 10 Product Documentation]</ref>
# This parameter only applies when evaluating a SPARQL SELECT query.<ref name="ref_33c426c6" />
# This parameter is only applies when evaluating a SPARQL SELECT query.<ref name="ref_33c426c6" />
# Use this parameter to fetch SPARQL query results based on the database contents at a fixed point-in-time.<ref name="ref_33c426c6" />
# This query is rather verbose because SPARQL lacks an exponent operator or function.<ref name="ref_c54ddfdf">[https://wiki.openstreetmap.org/wiki/SPARQL_examples OpenStreetMap Wiki]</ref>
# VIVO uses the YASQE editor for SPARQL.<ref name="ref_79457656">[https://wiki.lyrasis.org/display/VIVODOC110x/SPARQL+Queries VIVO 1.10.x Documentation]</ref>
# These provides abbreviations for various URLs you use in your SPARQL queries.<ref name="ref_79457656" />
# For more on SPARQL, see Learning SPARQL.<ref name="ref_79457656" />
# Vitro SPARQL supports DESCRIBE queries, but DESCRIBE is not well-defined by W3C standards, allowing implementation specific variations.<ref name="ref_79457656" />
# All sample queries from this less can be pasted directly into DBpedia’s SPARQL UI for testing.<ref name="ref_2c4aabe7">[https://www.cambridgesemantics.com/blog/semantic-university/learn-sparql/sparql-nuts-bolts/ SPARQL Nuts & Bolts]</ref>
# Try this in the DBpedia SPARQL UI.<ref name="ref_2c4aabe7" />
# If you are coming from the SQL world, the SPARQL OPTIONAL operator is equivalent to a Left Outer Join.<ref name="ref_2c4aabe7" />
# For SPARQL endpoints, SELECT and ASK queries return XML (application/sparql-results+xml) as the standard query result format for a SPARQL query.<ref name="ref_2c4aabe7" />
# For a complete documentation of the language, the specifications of SPARQL can be found on the W3C web site .<ref name="ref_3213eb69">[https://data.europa.eu/euodp/en/sparql Open Data Portal]</ref>
# Stardog Knowledge Graph supports the SPARQL query language, a W3C standard for querying RDF graphs.<ref name="ref_534e8c69">[https://www.stardog.com/tutorials/sparql/ Learn SPARQL - Tutorial]</ref>
# The main query form in SPARQL is a SELECT query which, by design, looks a bit like a SQL query.<ref name="ref_534e8c69" />
# But SPARQL provides a special kind of filter for this purpose: NOT EXISTS .<ref name="ref_534e8c69" />
# As we have just seen SPARQL property paths can be used to find pairs of nodes connected via a complex path of edges.<ref name="ref_534e8c69" />
# SPARQL is the standard language for querying RDF data.<ref name="ref_759744b2">[https://dl.acm.org/doi/10.1145/1567274.1567278 Semantics and complexity of SPARQL]</ref>
# In this article, we address systematically the formal study of the database aspects of SPARQL, concentrating in its graph pattern matching facility.<ref name="ref_759744b2" />
# We provide a compositional semantics for the core part of SPARQL, and study the complexity of the evaluation of several fragments of the language.<ref name="ref_759744b2" />
# Among other complexity results, we show that the evaluation of general SPARQL patterns is PSPACE-complete.<ref name="ref_759744b2" />
# SPARQL builds on previous RDF query languages such as rdfDB, RDQL, and SeRQL, and has several valuable new features of its own.<ref name="ref_47b1f710">[https://developer.ibm.com/articles/j-sparql/ Search RDF data with SPARQL]</ref>
# Now let’s look at a very simple SPARQL query over the bloggers model.<ref name="ref_47b1f710" />
# SPARQL variables are prefixed with either ?<ref name="ref_47b1f710" />
# In addition to implementing SPARQL, ARQ’s query engine can also parse queries expressed in RDQL or its own internal query language.<ref name="ref_47b1f710" />
# SPARQL can be used to express queries across diverse data sources, whether the data is stored natively as RDF or viewed as RDF via middleware.<ref name="ref_04398e10">[https://link.springer.com/10.1007/978-1-4614-8265-9_80803 SPARQL]</ref>
# The results of SPARQL queries can be result sets or RDF graphs.<ref name="ref_04398e10" />
# Named Graphs can be used to speed up your search by excluding the data that you do not care about - this can be done by using the from statement in your SPARQL query (see examples on this page).<ref name="ref_682864f2">[https://www.ebi.ac.uk/rdf/documentation/sparql-endpoints/ Using Sparql < RDF platform < EMBL-EBI]</ref>
# If you want to learn more about SPARQL, we recommend the How to SPARQL and Wikibooks SPARQL tutorial.<ref name="ref_c3b18a9e">[https://pro.europeana.eu/page/sparql Europeana Pro]</ref>
# We also recommend reading the Finding Europeana audio with SPARQL and SPARQL for humanists as they were the inspiration for us to provide this API.<ref name="ref_c3b18a9e" />
# SPARQL specifications can be found on the W3C web site .Please note that this is a tool for SPARQL experts.<ref name="ref_e37dbd3c">[https://www.europeandataportal.eu/sparql-manager/en/ SPARQL Manager]</ref>
# This page contains a collection of basic SPARQL examples which can be applied to data in Nomisma.org.<ref name="ref_b87bd310">[http://nomisma.org/documentation/sparql nomisma.org: SPARQL examples]</ref>
# The Apache Fuseki triplestore and SPARQL endpoint has been extended to support spatial queries by interacting with a Solr search index.<ref name="ref_b87bd310" />
# The objective of this SPARQL tutorial is to give a fast course in SPARQL.<ref name="ref_715edc32">[https://jena.apache.org/tutorials/sparql.html SPARQL Tutorial]</ref>
# If you are looking for a short introduction to SPARQL and Jena try Search RDF data with SPARQL.<ref name="ref_715edc32" />
# As a query language, SPARQL is “data-oriented” in that it only queries the information held in the models; there is no inference in the query language itself.<ref name="ref_715edc32" />
# SPANG can generate and execute simple queries by specifying a set of SPARQL shortcuts and additional options.<ref name="ref_ff067a08">[https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1531-1 SPANG: a SPARQL client supporting generation and reuse of queries for distributed RDF databases]</ref>
# the target SPARQL endpoint and the ensuing arguments are SPARQL shortcuts and an option.<ref name="ref_ff067a08" />
# The SPARQL endpoint can be specified in a URL or in a nickname for simplicity.<ref name="ref_ff067a08" />
# More generally, the shortcut mode can generate a SPARQL code containing a certain triple pattern (see Additional file 1).<ref name="ref_ff067a08" />
# Let’s use SPARQL, the query language for RDF graphs, to create a graph.<ref name="ref_63e64502">[https://graphdb.ontotext.com/documentation/free/devhub/sparql.html SPARQL — GraphDB Free 9.5.0 documentation]</ref>
# Thus the query is easily written in SPARQL by matching Fred’s children and then matching his children’s children.<ref name="ref_63e64502" />
# SELECT query Used to extract raw values from a SPARQL endpoint, the results are returned in a table format.<ref name="ref_b5328926">[https://en.wikipedia.org/wiki/SPARQL Wikipedia]</ref>
# CONSTRUCT query Used to extract information from the SPARQL endpoint and transform the results into valid RDF.<ref name="ref_b5328926" />
# ASK query Used to provide a simple True/False result for a query on a SPARQL endpoint.<ref name="ref_b5328926" />
# The SPARQL query processor will search for sets of triples that match these four triple patterns, binding the variables in the query to the corresponding parts of each triple.<ref name="ref_b5328926" />
# The combination of the flexibility of RDF and the expressiveness of SPARQL provides a powerful mechanism to model, integrate and query data.<ref name="ref_4e54b436">[https://www.sciencedirect.com/science/article/pii/S1570826814001061 On the formulation of performant SPARQL queries]</ref>
# However, these properties also mean that it is nontrivial to write performant SPARQL queries.<ref name="ref_4e54b436" />
# Moreover, we empirically verify the efficacy of the heuristics using a set of openly available datasets and corresponding SPARQL queries developed by a large pharmacology data integration project.<ref name="ref_4e54b436" />
# In addition, a SPARQL query can also be executed on any database that can be viewed as RDF via a middleware.<ref name="ref_d3242967">[https://www.ontotext.com/knowledgehub/fundamentals/what-is-sparql/ What is SPARQL?]</ref>
# In contrast to SQL, SPARQL queries are not constrained to working within one database: federated queries can access multiple data stores (endpoints).<ref name="ref_d3242967" />
# It is also an HTTP-based transport protocol, where any SPARQL endpoint can be accessed via a standardized transport layer.<ref name="ref_d3242967" />
# SPARQL is designed to enable Linked Data for the Semantic Web.<ref name="ref_d3242967" />
# SPARQL is the language used to query these databases.<ref name="ref_bb95da50">[https://programminghistorian.org/en/lessons/retired/graph-databases-and-SPARQL Using SPARQL to access Linked Open Data]</ref>
# Unfortunately, many tutorials on SPARQL use extremely simplified data models that don’t resemble the more complex datasets released by cultural heritage institutions.<ref name="ref_bb95da50" />
# This tutorial gives a crash course on SPARQL using a dataset that a humanist might actually find in the wilds of the Internet.<ref name="ref_bb95da50" />
# It is useful to think of a SPARQL query as a Mad Lib - a set of sentences with blanks in them.<ref name="ref_bb95da50" />
# This specification defines the syntax and semantics of the SPARQL query language for RDF.<ref name="ref_bab815fd">[https://www.w3.org/TR/sparql11-query/ SPARQL 1.1 Query Language]</ref>
# SPARQL contains capabilities for querying required and optional graph patterns along with their conjunctions and disjunctions.<ref name="ref_bab815fd" />
# SPARQL also supports aggregation, subqueries, negation, creating values by expressions, extensible value testing, and constraining queries by source RDF graph.<ref name="ref_bab815fd" />
# Although work on this document by the SPARQL Working Group is complete, comments may be addressed in the errata or in future revisions.<ref name="ref_bab815fd" />
# SPARQL also supports extensible value testing and constraining queries by source RDF graph.<ref name="ref_8e001785">[https://www.w3.org/TR/rdf-sparql-query/ SPARQL Query Language for RDF]</ref>
# This section of the document, section 1, introduces the SPARQL query language specification.<ref name="ref_8e001785" />
# Section 2 of the specification introduces the SPARQL query language itself via a series of example queries and query results.<ref name="ref_8e001785" />
# Section 4 presents details of the SPARQL query language's syntax.<ref name="ref_8e001785" />
===소스===
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 * ID :  [https://www.wikidata.org/wiki/Q54871 Q54871]

← 이전 판		2020년 12월 26일 (토) 12:18 판
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	===소스===		===소스===
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		+	* ID : [https://www.wikidata.org/wiki/Q54871 Q54871]

SPARQL - 편집 역사

2021년 2월 17일 (수) 08:10에 Pythagoras0님의 편집

Pythagoras0: /* 메타데이터 */ 새 문단

Pythagoras0: /* 노트 */ 새 문단