Interpolation of Spatial Data, Some Theory for Kriging View Full Text


Ontology type: schema:Book     


Book Info

DATE

1999

GENRE

Monograph

AUTHORS

Michael L. Stein

PUBLISHER

Springer New York

ABSTRACT

N/A

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4612-1494-6

DOI

http://dx.doi.org/10.1007/978-1-4612-1494-6

ISBN

978-1-4612-7166-6 | 978-1-4612-1494-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004000982


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "author": [
      {
        "affiliation": {
          "name": [
            "Department of Statistics, University of Chicago, 60637, Chicago, IL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Stein", 
        "givenName": "Michael L.", 
        "type": "Person"
      }
    ], 
    "datePublished": "1999", 
    "datePublishedReg": "1999-01-01", 
    "genre": "monograph", 
    "id": "sg:pub.10.1007/978-1-4612-1494-6", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isbn": [
      "978-1-4612-7166-6", 
      "978-1-4612-1494-6"
    ], 
    "name": "Interpolation of Spatial Data, Some Theory for Kriging", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "130fd99c918d839ebee022da769fdd06e8c3e4e14def30406c68e18b9b0cec24"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-4612-1494-6"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1004000982"
        ]
      }
    ], 
    "publisher": {
      "location": "New York, NY", 
      "name": "Springer New York", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-4612-1494-6", 
      "https://app.dimensions.ai/details/publication/pub.1004000982"
    ], 
    "sdDataset": "books", 
    "sdDatePublished": "2019-04-12T03:50", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000371_0000000371/records_130794_00000000.jsonl", 
    "type": "Book", 
    "url": "https://link.springer.com/10.1007%2F978-1-4612-1494-6"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-1-4612-1494-6'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-4612-1494-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-4612-1494-6'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-4612-1494-6'


 

This table displays all metadata directly associated to this object as RDF triples.

44 TRIPLES      18 PREDICATES      23 URIs      18 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-1-4612-1494-6 schema:author N627c1e732f4e4826be51ff196712c781
2 schema:datePublished 1999
3 schema:datePublishedReg 1999-01-01
4 schema:genre monograph
5 schema:inLanguage en
6 schema:isAccessibleForFree false
7 schema:isbn 978-1-4612-1494-6
8 978-1-4612-7166-6
9 schema:name Interpolation of Spatial Data, Some Theory for Kriging
10 schema:productId Na0338461180c45828e9610ccc45f3e7a
11 Nd795038f8c8f4856828e3de0845acecf
12 Ne1360376daef46af972700bc0f9f6d77
13 schema:publisher N40e97f5fbb2743d9bcb16cc0e7edfe45
14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004000982
15 https://doi.org/10.1007/978-1-4612-1494-6
16 schema:sdDatePublished 2019-04-12T03:50
17 schema:sdLicense https://scigraph.springernature.com/explorer/license/
18 schema:sdPublisher Nb76a3308cfc5459abf0d40cff0249aca
19 schema:url https://link.springer.com/10.1007%2F978-1-4612-1494-6
20 sgo:license sg:explorer/license/
21 sgo:sdDataset books
22 rdf:type schema:Book
23 N40e97f5fbb2743d9bcb16cc0e7edfe45 schema:location New York, NY
24 schema:name Springer New York
25 rdf:type schema:Organisation
26 N50df9c2fa2514fa3b46e7c8b66e40418 schema:name Department of Statistics, University of Chicago, 60637, Chicago, IL, USA
27 rdf:type schema:Organization
28 N627c1e732f4e4826be51ff196712c781 rdf:first Ne80946091e4c408ea670870eb61666c4
29 rdf:rest rdf:nil
30 Na0338461180c45828e9610ccc45f3e7a schema:name readcube_id
31 schema:value 130fd99c918d839ebee022da769fdd06e8c3e4e14def30406c68e18b9b0cec24
32 rdf:type schema:PropertyValue
33 Nb76a3308cfc5459abf0d40cff0249aca schema:name Springer Nature - SN SciGraph project
34 rdf:type schema:Organization
35 Nd795038f8c8f4856828e3de0845acecf schema:name doi
36 schema:value 10.1007/978-1-4612-1494-6
37 rdf:type schema:PropertyValue
38 Ne1360376daef46af972700bc0f9f6d77 schema:name dimensions_id
39 schema:value pub.1004000982
40 rdf:type schema:PropertyValue
41 Ne80946091e4c408ea670870eb61666c4 schema:affiliation N50df9c2fa2514fa3b46e7c8b66e40418
42 schema:familyName Stein
43 schema:givenName Michael L.
44 rdf:type schema:Person
 




Preview window. Press ESC to close (or click here)


...