基于邮政编码第一部分的HM土地注册网站SPARQL查询_Sparql

基于邮政编码第一部分的HM土地注册网站SPARQL查询

sparql

基于邮政编码第一部分的HM土地注册网站SPARQL查询,sparql,Sparql,我正试图通过HM土地注册处开放数据SPARQL查询找出一个邮编区域的平均房价数据，如果是针对一个邮编区域，例如GL52，那么最好的方法是什么此处给出的“邮政编码中的交易”示例代码显示了如何搜索完整的邮政编码，我已尝试使用值上的STRSTARTS更改代码？邮政编码部分，但返回时出错 prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> prefix rdfs: <http://www.w3.org/2000/01/r

我正试图通过HM土地注册处开放数据SPARQL查询找出一个邮编区域的平均房价数据，如果是针对一个邮编区域，例如GL52，那么最好的方法是什么

此处给出的“邮政编码中的交易”示例代码显示了如何搜索完整的邮政编码，我已尝试使用值上的STRSTARTS更改代码？邮政编码部分，但返回时出错

prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix owl: <http://www.w3.org/2002/07/owl#>
prefix xsd: <http://www.w3.org/2001/XMLSchema#>
prefix sr: <http://data.ordnancesurvey.co.uk/ontology/spatialrelations/>
prefix ukhpi: <http://landregistry.data.gov.uk/def/ukhpi/>
prefix lrppi: <http://landregistry.data.gov.uk/def/ppi/>
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix lrcommon: <http://landregistry.data.gov.uk/def/common/>

# Returns the Price Paid data from the default graph for each transaction record having
# an address with the given postcode.
# The postcode to query is set using SPARQL 1.1's 'values' clause

SELECT ?paon ?saon ?street ?town ?county ?postcode ?amount ?date ?category
WHERE
{
  VALUES ?postcode STRSTARTS({"GL52"^^xsd:string}, {"GL52"^^xsd:string})

  ?addr lrcommon:postcode ?postcode.

  ?transx lrppi:propertyAddress ?addr ;
          lrppi:pricePaid ?amount ;
          lrppi:transactionDate ?date ;
          lrppi:transactionCategory/skos:prefLabel ?category.

  OPTIONAL {?addr lrcommon:county ?county}
  OPTIONAL {?addr lrcommon:paon ?paon}
  OPTIONAL {?addr lrcommon:saon ?saon}
  OPTIONAL {?addr lrcommon:street ?street}
  OPTIONAL {?addr lrcommon:town ?town}
}
ORDER BY ?amount

错误返回为在第18行第20列遇到STRSTARTS STRSTARTS。他期望： {

如果您有任何建议，我们将不胜感激！

恐怕您的语法是错误的。对于这种类型的查询，您将需要一个筛选器，如：

prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix owl: <http://www.w3.org/2002/07/owl#>
prefix xsd: <http://www.w3.org/2001/XMLSchema#>
prefix sr: <http://data.ordnancesurvey.co.uk/ontology/spatialrelations/>
prefix ukhpi: <http://landregistry.data.gov.uk/def/ukhpi/>
prefix lrppi: <http://landregistry.data.gov.uk/def/ppi/>
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix lrcommon: <http://landregistry.data.gov.uk/def/common/>

# Returns the Price Paid data from the default graph for each transaction record having
# an address with the given postcode.
# The postcode to query is set using SPARQL 1.1's 'values' clause

    SELECT ?paon ?saon ?street ?town ?county ?postcode ?amount ?date ?category
    WHERE
    {
      ?addr lrcommon:postcode ?postcode .
    
      ?transx lrppi:propertyAddress ?addr ;
              lrppi:pricePaid ?amount ;
              lrppi:transactionDate ?date ;
              lrppi:transactionCategory/skos:prefLabel ?category.
      FILTER(STRSTARTS(?postcode,"GL52")) #Difference is here
    
      OPTIONAL {?addr lrcommon:county ?county}
      OPTIONAL {?addr lrcommon:paon ?paon}
      OPTIONAL {?addr lrcommon:saon ?saon}
      OPTIONAL {?addr lrcommon:street ?street}
      OPTIONAL {?addr lrcommon:town ?town}
    }
    ORDER BY ?amount

现在，此端点不是最快的端点，因此此查询很遗憾将超时。您可以通过指定county是什么来帮助提高查询性能，并且以下查询也将生成您要查找的内容，而不会超时：

prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix owl: <http://www.w3.org/2002/07/owl#>
prefix xsd: <http://www.w3.org/2001/XMLSchema#>
prefix sr: <http://data.ordnancesurvey.co.uk/ontology/spatialrelations/>
prefix ukhpi: <http://landregistry.data.gov.uk/def/ukhpi/>
prefix lrppi: <http://landregistry.data.gov.uk/def/ppi/>
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix lrcommon: <http://landregistry.data.gov.uk/def/common/>

# Returns the Price Paid data from the default graph for each transaction record having
# an address with the given postcode.
# The postcode to query is set using SPARQL 1.1's 'values' clause

SELECT ?paon ?saon ?street ?town ?county ?postcode ?amount ?date ?category
WHERE
{
  #VALUES ?pc {"GL52"}

  ?addr lrcommon:postcode ?postcode ;
        lrcommon:county "GLOUCESTERSHIRE" .

  ?transx lrppi:propertyAddress ?addr ;
          lrppi:pricePaid ?amount ;
          lrppi:transactionDate ?date ;
          lrppi:transactionCategory/skos:prefLabel ?category.
  FILTER(STRSTARTS(?postcode,"GL52"))

  #OPTIONAL {?addr lrcommon:county ?county}
  OPTIONAL {?addr lrcommon:paon ?paon}
  OPTIONAL {?addr lrcommon:saon ?saon}
  OPTIONAL {?addr lrcommon:street ?street}
  OPTIONAL {?addr lrcommon:town ?town}
}
ORDER BY ?amount

现在，如果您想同时查看多个邮政编码，可以尝试以下方法：

prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix owl: <http://www.w3.org/2002/07/owl#>
prefix xsd: <http://www.w3.org/2001/XMLSchema#>
prefix sr: <http://data.ordnancesurvey.co.uk/ontology/spatialrelations/>
prefix ukhpi: <http://landregistry.data.gov.uk/def/ukhpi/>
prefix lrppi: <http://landregistry.data.gov.uk/def/ppi/>
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix lrcommon: <http://landregistry.data.gov.uk/def/common/>

# Returns the Price Paid data from the default graph for each transaction record having
# an address with the given postcode.
# The postcode to query is set using SPARQL 1.1's 'values' clause

SELECT ?paon ?saon ?street ?town ?county ?postcode ?amount ?date ?category
WHERE
{
  VALUES ?pc {"GL52" "GL51" "GL1 "}

  ?addr lrcommon:postcode ?postcode ;
        lrcommon:county "GLOUCESTERSHIRE" .

  ?transx lrppi:propertyAddress ?addr ;
          lrppi:pricePaid ?amount ;
          lrppi:transactionDate ?date ;
          lrppi:transactionCategory/skos:prefLabel ?category.
  FILTER(STRSTARTS(?postcode,?pc))

  #OPTIONAL {?addr lrcommon:county ?county}
  OPTIONAL {?addr lrcommon:paon ?paon}
  OPTIONAL {?addr lrcommon:saon ?saon}
  OPTIONAL {?addr lrcommon:street ?street}
  OPTIONAL {?addr lrcommon:town ?town}
}
ORDER BY ?amount

这是做同样的事情，但本质上是一个缩写。

恐怕您的语法是错误的。对于这种类型的查询，您需要一个过滤器，如：

prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix owl: <http://www.w3.org/2002/07/owl#>
prefix xsd: <http://www.w3.org/2001/XMLSchema#>
prefix sr: <http://data.ordnancesurvey.co.uk/ontology/spatialrelations/>
prefix ukhpi: <http://landregistry.data.gov.uk/def/ukhpi/>
prefix lrppi: <http://landregistry.data.gov.uk/def/ppi/>
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix lrcommon: <http://landregistry.data.gov.uk/def/common/>

# Returns the Price Paid data from the default graph for each transaction record having
# an address with the given postcode.
# The postcode to query is set using SPARQL 1.1's 'values' clause

    SELECT ?paon ?saon ?street ?town ?county ?postcode ?amount ?date ?category
    WHERE
    {
      ?addr lrcommon:postcode ?postcode .
    
      ?transx lrppi:propertyAddress ?addr ;
              lrppi:pricePaid ?amount ;
              lrppi:transactionDate ?date ;
              lrppi:transactionCategory/skos:prefLabel ?category.
      FILTER(STRSTARTS(?postcode,"GL52")) #Difference is here
    
      OPTIONAL {?addr lrcommon:county ?county}
      OPTIONAL {?addr lrcommon:paon ?paon}
      OPTIONAL {?addr lrcommon:saon ?saon}
      OPTIONAL {?addr lrcommon:street ?street}
      OPTIONAL {?addr lrcommon:town ?town}
    }
    ORDER BY ?amount

prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix owl: <http://www.w3.org/2002/07/owl#>
prefix xsd: <http://www.w3.org/2001/XMLSchema#>
prefix sr: <http://data.ordnancesurvey.co.uk/ontology/spatialrelations/>
prefix ukhpi: <http://landregistry.data.gov.uk/def/ukhpi/>
prefix lrppi: <http://landregistry.data.gov.uk/def/ppi/>
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix lrcommon: <http://landregistry.data.gov.uk/def/common/>

# Returns the Price Paid data from the default graph for each transaction record having
# an address with the given postcode.
# The postcode to query is set using SPARQL 1.1's 'values' clause

SELECT ?paon ?saon ?street ?town ?county ?postcode ?amount ?date ?category
WHERE
{
  #VALUES ?pc {"GL52"}

  ?addr lrcommon:postcode ?postcode ;
        lrcommon:county "GLOUCESTERSHIRE" .

  ?transx lrppi:propertyAddress ?addr ;
          lrppi:pricePaid ?amount ;
          lrppi:transactionDate ?date ;
          lrppi:transactionCategory/skos:prefLabel ?category.
  FILTER(STRSTARTS(?postcode,"GL52"))

  #OPTIONAL {?addr lrcommon:county ?county}
  OPTIONAL {?addr lrcommon:paon ?paon}
  OPTIONAL {?addr lrcommon:saon ?saon}
  OPTIONAL {?addr lrcommon:street ?street}
  OPTIONAL {?addr lrcommon:town ?town}
}
ORDER BY ?amount

现在，如果您想同时查看多个邮政编码，可以尝试以下方法：

prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix owl: <http://www.w3.org/2002/07/owl#>
prefix xsd: <http://www.w3.org/2001/XMLSchema#>
prefix sr: <http://data.ordnancesurvey.co.uk/ontology/spatialrelations/>
prefix ukhpi: <http://landregistry.data.gov.uk/def/ukhpi/>
prefix lrppi: <http://landregistry.data.gov.uk/def/ppi/>
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix lrcommon: <http://landregistry.data.gov.uk/def/common/>

# Returns the Price Paid data from the default graph for each transaction record having
# an address with the given postcode.
# The postcode to query is set using SPARQL 1.1's 'values' clause

SELECT ?paon ?saon ?street ?town ?county ?postcode ?amount ?date ?category
WHERE
{
  VALUES ?pc {"GL52" "GL51" "GL1 "}

  ?addr lrcommon:postcode ?postcode ;
        lrcommon:county "GLOUCESTERSHIRE" .

  ?transx lrppi:propertyAddress ?addr ;
          lrppi:pricePaid ?amount ;
          lrppi:transactionDate ?date ;
          lrppi:transactionCategory/skos:prefLabel ?category.
  FILTER(STRSTARTS(?postcode,?pc))

  #OPTIONAL {?addr lrcommon:county ?county}
  OPTIONAL {?addr lrcommon:paon ?paon}
  OPTIONAL {?addr lrcommon:saon ?saon}
  OPTIONAL {?addr lrcommon:street ?street}
  OPTIONAL {?addr lrcommon:town ?town}
}
ORDER BY ?amount

这是做同样的事情，但本质上是一个缩写。

这太棒了，谢谢你解释和给出一些很好的例子！它看起来像是返回了完整的历史，你认为过滤过去两年的最佳方式是什么？试着用它作为过滤器：FILTERSTRSTARTS？邮政编码，GL52&&YEAR？date>2018。也不要这样做如果你认为答案能回答你的问题，请忘记接受答案。谢谢，我使用你的上一个示例测试了它，你可以查找多个邮政编码，但返回了一个错误，我想我一定是遗漏了什么？-FiltersTrstStarts？postcode，？pc&&YEAR？date>2018适合我…有什么错误？嗨，我刚刚发现我也有一个ust before&&这太棒了，谢谢你解释并给出了一些很好的例子！它看起来像是返回了完整的历史，你认为过滤过去两年的最佳方式是什么？试着用它作为你的过滤器：FILTERSTRSTARTS？邮编，GL52&&YEAR？date>2018。如果你认为它符合你的要求，也别忘了接受答案估计。谢谢，我用上一个例子测试了它，你可以查找多个邮政编码，但返回了一个错误，我想我一定是遗漏了什么？-FILTERSTRSTARTS？postcode，？pc&&YEAR？date>2018适合我…什么错误？嗨，我刚刚发现我也有一个邮政编码！就在之前&&