Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 1
Dietary
Preheat the oven to 200C/400F/Gas 6.
To make the pastry, mix the flour and butter in a food processor until the mixture starts to resemble coarse breadcrumbs.
Add the egg yolk and enough water for the pastry to bind.
Bring the pastry together and, on a floured surface, roll the dough to a ½cm/¼in thickness. Cut out two large pear shapes, then place on a baking tray and bake for 10 minutes.
For the pear, bring the wine, water, sugar and bay leaf to a simmer in a small saucepan. Poach the pear halves in the syrup for 10 minutes, weighed down with a small plate to submerge the pear.
To make the filling, mix together the goats' cheese, chives and chopped salad onion, then season with salt and freshly ground black pepper.
Stuff this mixture into the cored poached pear halves and place the pears on the pastry. Bake in the oven for 10 minutes.
Serve on a large warm plate and garnish with the basil leaf.


WITNESS LIST
Public Education Committee
May 11, 2016 - 9:30 AM
Interim Charge 3 - Broadband and Instructional Technology
On:
Alexander, Cat (RYHT)
Ali, Gulraiz (Self; Temple ISD)
Barnett, Shaun (Texas Rural Education Association, Texas Association Community Schools)
Beasley, Jim (Self)
Bergland, Jennifer (Texas Computer Education Association (TCEA))
Dodson, Amy (Self; Cisco ISD/RYHT)
Driscoll, Terry (Lubbock ISD)
Fields, Keziah (Self; Temple ISD)
Fletcher, Carol (Self; Center for STEM Education, College of Education , The University of
Texas at Austin)
Frazier, Janell (Central Texas 4C, Inc)
Hooker, Carl (Self)
Jackson, Frankie (Cypress fairbanks isd)
Joiner, Caroline (TechNet)
Lovesmith, Deanna (Belton ISD)
Mackin, Shea (Public School Options)
Ojeda, Rosa (Self; Instructional Materials Association of Texas , Texas Computer Educators
Association, Texas Association of community schools)
Penrod, Eric (Self; Gatesville ISD)
Ritchie, Casey (Region 18 Education Service Center)
Rivera, Rosa (Self; Temple ISD)
Rodgers, Randy (Self; Texas Computer Education Association)
Sebek, Tyler (Self; Temple ISD)
Swei, Anthony (EducationSuperHighway)
Turzanski, Michael (EducationSuperHighway)
Wentz, Steve (Pasadena ISD)
Interim Charge 4 - Inappropriate Teacher-Student Relationships
On:
DC. Von Heinkel, Ahren (Self)
Ford, Stacy (Self; Coalition of Human Rights Policy Advocates (CHRPA))
Green, Christina (Children's Advocacy Centers of Texas)
Madrazo, Judith (Self)
Phillips, Doug (Texas Education Agency)
Robert, Catherine (Self)
Suter, Maggie (Self)
Thompson, David (Self)
Wilson, Columba (Self)
1


1 University Avenue, Berekuso
PMB CT 3, Cantonments
Accra, Ghana
Tel: +233 (302) 610 330
Mob: +233 501 318 961 OR +233 204 374 374
Admissions Office
Tel: +233 20 437 4374
Tel: +233 50 131 8961
Tel: +233 50 131 9264
(Mon - Fri, 9 am - 5 pm GMT)
Email<EMAIL_ADDRESS>From Tetteh Quarshie Interchange, Accra
(1) Go North past the University of Ghana
(2) At Atomic Interchange, turn left towards Haatso
(3) Head through Haatso straight to the Atomic Roundabout
(4) Take the first (right) roundabout exit and drive towards Aburi
(5) Go straight until you reach Berekuso
(6) Take first right after the Berekuso police barrier. Look out for the Ashesi directional sign


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Contiki 2.5
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Files | |
| file | avr_flash.c [code] |
This file writes/reads to/from flash memory internal to the AVR. | |
| file | avr_flash.h [code] |
This file writes/reads to/from flash memory internal to the AVR. | |
| file | conf_access.h [code] |
This file contains the possible external configuration of the control access. | |
| file | ctrl_access.c [code] |
This file contains the interface : | |
| file | ctrl_access.h [code] |
This file contains the interface : | |
| file | ctrl_status.h [code] |
This file contains the interface : | |
| file | scsi_decoder.c [code] |
This file is the scsi decoder. | |
| file | scsi_decoder.h [code] |
This file is the scsi decoder. | |
| file | storage_task.c [code] |
This file manages the USB storage. | |
| file | storage_task.h [code] |


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Kind Enumeration
Definition at line
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of
Gdb.hpp
Enumerators
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Value
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execRunning
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consoleOutput
targetOutput
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parsingError
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Showing sessions for {{ location_name }}. All locations. Change location
Click one to filter your results
No results found. Sad Panda. Try typing in the box.
Cancel. Show all my locations.
Online
Total
Avg. Signal
Downloads
| Name | Total | Online |
|---|---|---|
| {{ location.location_name }} | {{ location.total }} | {{ location.online }} |
The total clients at all your locations ({{ info.total }}) may be lower than the sum of users at each location because a client can visit more than one location.


In April of 2016, my husband and I visited Chattanooga from our hometown of Atlanta. On that weekend we visited the aquarium, strolled around the city, and enjoyed some southern comfort foods at Puckett’s. We fell in love with the city and decided we wanted to make Chattanooga our new home. In October of 2016, we took the leap, packed our belongings and cats, and headed to our new favorite city.
During this transition, I realized I needed to find a professional field that I could be passionate about. My Bachelors in Business Management had allowed me to explore marketing and accounting in the consumer electronics sector. While I learned and grew as a professional, I also fell in love with tech. Once I started learning about Javascript and PHP, I knew immediately that I had found the perfect fit for me!
I created this website while folowing along with the instructor during the Tech Workforce Program. The website contains unordered lists, an imbeded map, CSS styling, loops, and even a Javascript game! I used Atom to edit the code, Github to push to the repository, and Firebase to deploy to the internet.


For the final project, I’ve pushed an html file and a CSS to the repository. I have used vim to edit the file and w3 school to help me write the code. I used git to organize the code.
Group Update #1
We got the Vps Working, but took a little while to refresh our memories to use github
Second Update (2021-05-07)
It's due on Februrary 23rd 2021.
Group Update #2
We added the website tab and made the journals, It wasn't too hard but there were some bugs here and there
Third Update (2021-05-09)
Individual: I have Worked on getting the files on the server and tried attaching it to the main server
Group: As Jordano and Geon were working on the files, I was in charge of helping where
they had difficlties and fix the few bugs that appeared here and there


Please refer to the errata for this document, which may include some normative corrections.
See also translations.
Copyright © 2012 W3C® (MIT, ERCIM, Keio), All Rights Reserved. W3C liability, trademark and document use rules apply.
This document describes R2RML, a language for expressing customized mappings from relational databases to RDF datasets. Such mappings provide the ability to view existing relational data in the RDF data model, expressed in a structure and target vocabulary of the mapping author's choice. R2RML mappings are themselves RDF graphs and written down in Turtle syntax. R2RML enables different types of mapping implementations. Processors could, for example, offer a virtual SPARQL endpoint over the mapped relational data, or generate RDF dumps, or offer a Linked Data interface.
This section describes the status of this document at the time of its publication. Other documents may supersede this document. A list of current W3C publications and the latest revision of this technical report can be found in the W3C technical reports index at http://www.w3.org/TR/.
This document has been reviewed by W3C Members, by software developers, and by other W3C groups and interested parties, and is endorsed by the Director as a W3C Recommendation. It is a stable document and may be used as reference material or cited from another document. W3C's role in making the Recommendation is to draw attention to the specification and to promote its widespread deployment. This enhances the functionality and interoperability of the Web.
This document was published by the RDB2RDF Working Group. Comments on this document should be sent to<EMAIL_ADDRESS>a mailing list with a public archive. The following related documents have been made available:
This document was produced by a group operating under the 5 February 2004 W3C Patent Policy. W3C maintains a public list of any patent disclosures made in connection with the deliverables of the group; that page also includes instructions for disclosing a patent. An individual who has actual knowledge of a patent which the individual believes contains Essential Claim(s) must disclose the information in accordance with section 6 of the W3C Patent Policy.
rr:parentTriplesMap
, rr:joinCondition
, rr:child
and rr:parent
)This specification describes R2RML, a language for expressing customized mappings from relational databases to RDF datasets. Such mappings provide the ability to view existing relational data in the RDF data model, expressed in a structure and target vocabulary of the mapping author's choice.
This specification has a companion that defines a direct mapping from relational databases to RDF [DM]. In the direct mapping of a database, the structure of the resulting RDF graph directly reflects the structure of the database, the target RDF vocabulary directly reflects the names of database schema elements, and neither structure nor target vocabulary can be changed. With R2RML on the other hand, a mapping author can define highly customized views over the relational data.
Every R2RML mapping is tailored to a specific database schema and target vocabulary. The input to an R2RML mapping is a relational database that conforms to that schema. The output is an RDF dataset [SPARQL], as defined in SPARQL, that uses predicates and types from the target vocabulary. The mapping is conceptual; R2RML processors are free to materialize the output data, or to offer virtual access through an interface that queries the underlying database, or to offer any other means of providing access to the output RDF dataset.
R2RML mappings are themselves expressed as RDF graphs and written down in Turtle syntax [TURTLE].
The intended audience of this specification is implementors of software that generates or processes R2RML mapping documents, as well as mapping authors looking for a reference to the R2RML language constructs. The document uses concepts from RDF Concepts and Abstract Syntax [RDF] and from the SQL language specifications [SQL1][SQL2]. A reader's familiarity with the contents of these documents, as well as with the Turtle syntax, is assumed.
The R2RML language is designed to meet the use cases and requirements identified in Use Cases and Requirements for Mapping Relational Databases to RDF [UCNR].
In this document, examples assume the following namespace prefix bindings unless otherwise stated:
| Prefix | IRI |
|---|---|
rr: |
http://www.w3.org/ns/r2rml# |
rdf: |
http://www.w3.org/1999/02/22-rdf-syntax-ns# |
rdfs: |
http://www.w3.org/2000/01/rdf-schema# |
xsd: |
http://www.w3.org/2001/XMLSchema# |
ex: |
http://example.com/ns# |
Throughout the document, boxes containing Turtle markup and SQL data will appear. These boxes are color-coded. Gray boxes contain RDFS definitions of R2RML vocabulary terms:
# This box contains RDFS definitions of R2RML vocabulary terms
Yellow boxes contain example fragments of R2RML mappings in Turtle syntax:
# This box contains example R2RML mappings
Blue tables contain example input into an R2RML mapping:
| ID INTEGER PRIMARY KEY | DESC VARCHAR(100) |
|---|---|
| 1 | This is an example input table. |
| 2 | The table name is EXAMPLE. |
| 3 | It has six rows. |
| 4 | It has two columns, ID and DESC. |
| 5 | ID is the table's primary key and of type INTEGER. |
| 6 | DESC is of type VARCHAR(100) |
Green boxes contain example output:
# This box contains example output RDF triples or fragments
This section gives a brief overview of the R2RML mapping language, followed by a simple example relational database with an R2RML mapping document and its output RDF. Further R2RML examples can be found in the R2RML and Direct Mapping Test Cases [TC].
An R2RML mapping refers to logical tables to retrieve data from the input database. A logical table can be one of the following:
Each logical table is mapped to RDF using a triples map. The triples map is a rule that maps each row in the logical table to a number of RDF triples. The rule has two main parts:
Triples are produced by combining the subject map with a predicate map and object map, and applying these three to each logical table row. For example, the complete rule for generating a set of triples might be:
http://data.example.com/employee/{empno}
is used to generate subject IRIs from the empno
column.ex:name
is used.ename
column is used to produce an RDF literal.By default, all RDF triples are in the default graph of the output dataset. A triples map can contain graph maps that place some or all of the triples into named graphs instead.
The following example database consists of two tables,
EMP
and DEPT
, with one row each:
| EMPNO INTEGER PRIMARY KEY | ENAME VARCHAR(100) | JOB VARCHAR(20) | DEPTNO INTEGER REFERENCES DEPT (DEPTNO) |
|---|---|---|---|
7369 |
SMITH |
CLERK |
10 |
| DEPTNO INTEGER PRIMARY KEY | DNAME VARCHAR(30) | LOC VARCHAR(100) |
|---|---|---|
10 |
APPSERVER |
NEW YORK |
The desired RDF triples to be produced from this database are as follows:
<http://data.example.com/employee/7369> rdf:type ex:Employee. <http://data.example.com/employee/7369> ex:name "SMITH". <http://data.example.com/employee/7369> ex:department <http://data.example.com/department/10>. <http://data.example.com/department/10> rdf:type ex:Department. <http://data.example.com/department/10> ex:name "APPSERVER". <http://data.example.com/department/10> ex:location "NEW YORK". <http://data.example.com/department/10> ex:staff 1.
Note in particular:
ex:Employee
, ex:location
etc.);ex:staff
property has the total number of staff of a department; this value is not stored directly in the database but has to be computed.ex:department
property relates an employee to their department, using the identifiers of both entities;The following partial R2RML mapping document will produce
the desired triples from the EMP
table
(except the
ex:department
triple, which will be added later):
@prefix rr: <http://www.w3.org/ns/r2rml#>. @prefix ex: <http://example.com/ns#>. <#TriplesMap1> rr:logicalTable [ rr:tableName "EMP" ]; rr:subjectMap [ rr:template "http://data.example.com/employee/{EMPNO}"; rr:class ex:Employee; ]; rr:predicateObjectMap [ rr:predicate ex:name; rr:objectMap [ rr:column "ENAME" ]; ].
<http://data.example.com/employee/7369> rdf:type ex:Employee. <http://data.example.com/employee/7369> ex:name "SMITH".
Next, the DEPT
table needs
to be mapped. Instead of using the table directly as the basis
for that mapping, an “R2RML view”
will be defined based on a SQL query.
This allows computation of the staff number.
(Alternatively, one could define this view directly in the database.)
<#DeptTableView> rr:sqlQuery """ SELECT DEPTNO, DNAME, LOC, (SELECT COUNT(*) FROM EMP WHERE EMP.DEPTNO=DEPT.DEPTNO) AS STAFF FROM DEPT; """.
The definition of a triples map that generates the desired
DEPT
triples based on this R2RML view follows.
<#TriplesMap2> rr:logicalTable <#DeptTableView>; rr:subjectMap [ rr:template "http://data.example.com/department/{DEPTNO}"; rr:class ex:Department; ]; rr:predicateObjectMap [ rr:predicate ex:name; rr:objectMap [ rr:column "DNAME" ]; ]; rr:predicateObjectMap [ rr:predicate ex:location; rr:objectMap [ rr:column "LOC" ]; ]; rr:predicateObjectMap [ rr:predicate ex:staff; rr:objectMap [ rr:column "STAFF" ]; ].
<http://data.example.com/department/10> rdf:type ex:Department. <http://data.example.com/department/10> ex:name "APPSERVER". <http://data.example.com/department/10> ex:location "NEW YORK". <http://data.example.com/department/10> ex:staff 1.
To complete the mapping document, the ex:department
triples need to be generated. Their subjects come from
the first triples map (<#TriplesMap1>
),
the objects come from the second triples map
(<#TriplesMap2>
).
This can be achieved by adding another rr:predicateObjectMap
to <#TriplesMap1>
. This one uses the other triples map,
<#TriplesMap2>
, as a parent
triples map:
<#TriplesMap1> rr:predicateObjectMap [ rr:predicate ex:department; rr:objectMap [ rr:parentTriplesMap <#TriplesMap2>; rr:joinCondition [ rr:child "DEPTNO"; rr:parent "DEPTNO"; ]; ]; ].
This performs a join between the EMP
table and the
R2RML view, on the
DEPTNO
columns. The objects will be generated from
the subject map of the parent triples map, yielding the desired
triple:
<http://data.example.com/employee/7369> ex:department <http://data.example.com/department/10>.
This completes the R2RML mapping document. An R2RML processor will generate the triples listed above from this mapping document.
The following example will assume that a many-to-many relationship exists between
the extended versions of EMP
table and the DEPT
table shown below. This
many-to-many relationship is captured by the content of
the EMP2DEPT
table. The database consisting of
the EMP
, DEPT
, and EMP2DEPT
tables are shown below:
| EMPNO INTEGER PRIMARY KEY | ENAME VARCHAR(100) | JOB VARCHAR(20) |
|---|---|---|
7369 |
SMITH |
CLERK |
7369 |
SMITH |
NIGHTGUARD |
7400 |
JONES |
ENGINEER |
| DEPTNO INTEGER PRIMARY KEY | DNAME VARCHAR(30) | LOC VARCHAR(100) |
|---|---|---|
10 |
APPSERVER |
NEW YORK |
20 |
RESEARCH |
BOSTON |
| EMPNO INTEGER REFERENCES EMP (EMPNO) | DEPTNO INTEGER REFERENCES DEPT (DEPTNO) |
|---|---|
7369 |
10 |
7369 |
20 |
7400 |
10 |
<http://data.example.com/employee=7369/department=10> ex:employee <http://data.example.com/employee/7369> ; ex:department <http://data.example.com/department/10> . <http://data.example.com/employee=7369/department=20> ex:employee <http://data.example.com/employee/7369> ; ex:department <http://data.example.com/department/20> . <http://data.example.com/employee=7400/department=10> ex:employee <http://data.example.com/employee/7400> ; ex:department <http://data.example.com/department/10> .
The following R2RML mapping will produce the desired triples listed above:
<#TriplesMap3> rr:logicalTable [ rr:tableName "EMP2DEPT" ]; rr:subjectMap [ rr:template "http://data.example.com/employee={EMPNO}/department={DEPTNO}" ]; rr:predicateObjectMap [ rr:predicate ex:employee; rr:objectMap [ rr:template "http://data.example.com/employee/{EMPNO}" ]; ]; rr:predicateObjectMap [ rr:predicate ex:department; rr:objectMap [ rr:template "http://data.example.com/department/{DEPTNO}" ]; ].
However, if one does not require that the subjects in
the desired output uniquely identify the rows in the EMP2DEPT
table, the desired output
may look as follows:
<http://data.example.com/employee/7369> ex:department <http://data.example.com/department/10> ; ex:department <http://data.example.com/department/20> . <http://data.example.com/employee/7400> ex:department <http://data.example.com/department/10>.
The following R2RML mapping will produce the desired triples:
<#TriplesMap3> rr:logicalTable [ rr:tableName "EMP2DEPT" ]; rr:subjectMap [ rr:template "http://data.example.com/employee/{EMPNO}"; ]; rr:predicateObjectMap [ rr:predicate ex:department; rr:objectMap [ rr:template "http://data.example.com/department/{DEPTNO}" ]; ].
Sometimes, database columns contain codes that need to be translated
into IRIs, but a direct syntactic translation using
string templates is not possible.
For example, consider a JOB
column in the EMP
table with the following possible values, and IRIs corresponding to
those database values in the RDF output:
| Value | Corresponding RDF IRI |
|---|---|
CLERK | http://data.example.com/roles/general-office |
NIGHTGUARD | http://data.example.com/roles/security |
ENGINEER | http://data.example.com/roles/engineering |
The IRIs are not found in the original database and therefore the mapping
from database codes to IRIs has to be
specified in the R2RML mapping. Such translations can be achieved using an
“R2RML view”. The view is defined based on a
SQL query that computes the IRI based on the database value.
SQL's CASE
statement is convenient for this purpose.
(Alternatively, one could define this view directly in the database.)
<#TriplesMap1> rr:logicalTable [ rr:sqlQuery """ SELECT EMP.*, (CASE JOB WHEN 'CLERK' THEN 'general-office' WHEN 'NIGHTGUARD' THEN 'security' WHEN 'ENGINEER' THEN 'engineering' END) ROLE FROM EMP """ ]; rr:subjectMap [ rr:template "http://data.example.com/employee/{EMPNO}"; ]; rr:predicateObjectMap [ rr:predicate ex:role; rr:objectMap [ rr:template "http://data.example.com/roles/{ROLE}" ]; ].
With the example input database, this mapping would yield the following triple:
<http://data.example.com/employee/7369> ex:role <http://data.example.com/roles/general-office>.
As well as sections marked as non-normative in the section heading, all diagrams, examples, and notes in this specification are non-normative. Everything else in this specification is normative.
The key words must, must not, required, should, should not, recommended, may, and optional in this specification are to be interpreted as described in RFC 2119 [RFC2119].
This specification describes conformance criteria for:
A collection of test cases for R2RML processors and R2RML data validators is available in the R2RML and Direct Mapping Test Cases [TC].
This specification defines R2RML for databases that conform to Core SQL 2008, as defined in ISO/IEC 9075-1:2008 [SQL1] and ISO/IEC 9075-2:2008 [SQL2]. Processors and mappings may have to deviate from the R2RML specification in order to support databases that do not conform to this version of SQL.
Where SQL queries are embedded into R2RML mappings, SQL version identifiers can be used to indicate the specific version of SQL that is being used.
An R2RML mapping defines a mapping from a relational database to RDF. It is a structure that consists of one or more triples maps.
The input to an R2RML mapping is called the input database.
An R2RML processor is a system that, given an R2RML mapping and an input database, provides access to the output dataset.
There are no constraints on the method of access to the output dataset provided by a conforming R2RML processor. An R2RML processor MAY materialize the output dataset into a file, or offer virtual access through an interface that queries the input database, or offer any other means of providing access to the output dataset.
An R2RML processor also has access to an execution environment consisting of:
The SQL connection is used by the R2RML processor to evaluate SQL queries against the input database. It MUST be established with sufficient privileges for read access to all base tables and views that are referenced in the R2RML mapping. It MUST be configured with a default catalog and default schema that will be used when tables and views are accessed without an explicit catalog or schema reference.
How the SQL connection is established, or how users are authenticated against the database, is outside of the scope of this document.
The base IRI MUST
be a valid IRI. It SHOULD NOT
contain question mark (“?
”) or hash (“#
”)
characters and SHOULD end in a slash
(“/
”) character.
To obtain an absolute IRI from a relative IRI, the term generation rules of R2RML use simple string concatenation, rather than the more complex algorithm for resolution of relative URIs defined in Section 5.2 of [RFC3986]. This ensures that the original database value can be reconstructed from the generated absolute IRI. Both algorithms are equivalent if all of the following are true:
.
” or “..
” path segments.An R2RML data validator is a system that takes as its input an R2RML mapping, a base IRI, and a SQL connection to an input database, and checks for the presence of data errors. When checking the input database, a data validator MUST report any data errors that are raised in the process of generating the output dataset.
An R2RML processor MAY include an R2RML data validator, but this is not required.
An R2RML mapping is represented as an RDF graph. In other words, RDF is used not just as the target data model of the mapping, but also as a formalism for representing the R2RML mapping itself.
An RDF graph that represents an R2RML mapping is called an R2RML mapping graph.
The R2RML vocabulary is the
set of IRIs defined in this specification
that start with the rr:
namespace IRI:
http://www.w3.org/ns/r2rml#
rr:
namespace IRI, but are not defined in the
R2RML vocabulary.rdfs:label
,
rdfs:comment
and similar properties.The R2RML vocabulary also includes the following R2RML classes:
rr:TriplesMap
is the class of
triples maps.rr:LogicalTable
is the class of
logical tables. It has two subclasses:
rr:R2RMLView
is the class of
R2RML views.rr:BaseTableOrView
is the class of
SQL base tables or views.rr:TermMap
is the class of
term maps. It has four subclasses:
rr:SubjectMap
is the class of
subject maps.rr:PredicateMap
is the class of
predicate maps.rr:ObjectMap
is the class of
object maps.rr:GraphMap
is the class of
graph maps.rr:PredicateObjectMap
is the class of
predicate-object maps.rr:RefObjectMap
is the class of
referencing object maps.rr:Join
is the class of
join conditions.The members of these classes are collectively called mapping components.
Many of these classes differ only in capitalization from properties in the R2RML vocabulary.
Explicit typing of the resources in a mapping graph with R2RML classes is OPTIONAL and has no effect on the behaviour of an R2RML processor. The mapping component represented by any given resource in a mapping graph is defined by the presence or absence of certain properties, as defined throughout this specification. A resource SHOULD NOT be typed as an R2RML class if it does not meet the definition of that class.
An R2RML mapping document is any document written in the Turtle [TURTLE] RDF syntax that encodes an R2RML mapping graph.
The media type for R2RML mapping
documents is the same as for Turtle
documents in general: text/turtle
. The content encoding of
Turtle content is always UTF-8 and the charset
parameter
on the media type SHOULD always be used:
text/turtle;charset=utf-8
. The file extension
.ttl
SHOULD be used.
A conforming R2RML processor SHOULD accept R2RML mapping documents in Turtle syntax. It MAY accept R2RML mapping graphs encoded in other RDF syntaxes.
A data error is a condition of the data in the input database that would lead to the generation of an invalid RDF term. The following conditions give rise to data errors:
rr:IRI
results in the generation
of an invalid IRI.When providing access to the output dataset, an R2RML processor MUST abort any operation that requires inspecting or returning an RDF term whose generation would give rise to a data error, and report an error to the agent invoking the operation. A conforming R2RML processor MAY, however, allow other operations that do not require inspecting or returning these RDF terms, and thus MAY provide partial access to an output dataset that contains data errors. Nevertheless, an R2RML processor SHOULD report data errors as early as possible.
The presence of data errors does not make an R2RML mapping non-conforming.
Data errors cannot generally be detected by analyzing the table schema of the database, but only by scanning the data in the tables. For large and rapidly changing databases, this can be impractical. Therefore, R2RML processors are allowed to answer queries that do not “touch” a data error, and the behavior of such operations is well-defined. For the same reason, the conformance of R2RML mappings is defined without regard for the presence of data errors.
R2RML data validators can be used to explicitly scan a database for data errors.
An R2RML processor MAY include an R2RML default mapping generator. This is a facility that introspects the schema of the input database and generates an R2RML mapping, possibly in the form of an R2RML mapping document, intended for further customization by a mapping author. Such a mapping is known as a default mapping.
The default mapping SHOULD be such that its output is the Direct Graph [DM] corresponding to the input database.
Duplicate row preservation: For tables without a primary key, the Direct Graph requires that a fresh blank node is created for each row. This ensures that duplicate rows in such tables are preserved. This requirement is relaxed for R2RML default mappings: They MAY reuse the same blank node for multiple duplicate rows. This behaviour does not preserve duplicate rows. R2RML default mapping generators that provide default mappings based on the Direct Graph MUST document whether the generated default mapping preserves duplicate rows or not.
A logical table is a tabular SQL query result that is to be mapped to RDF triples. A logical table is either
Every logical table has an effective SQL query that, if executed over the SQL connection, produces as its result the contents of the logical table.
A logical table row is a row in a logical table.
A column name is the name of a column of a logical table. A column name MUST be a valid SQL identifier. Column names do not include any qualifying table, view or schema names.
A SQL identifier is the name of
a SQL object, such as a column, table, view, schema, or catalog.
A SQL identifier
MUST match the <identifier>
production in [SQL2]. When
comparing identifiers for equality, the comparison rules
of [SQL2] MUST
be used.
deptno
and "deptno"
are not equivalent
(delimited identifiers that are not all-upper-case are
not equivalent to any undelimited identifiers).DEPTNO
and "DEPTNO"
are equivalent
(all-upper-case delimited and undelimited identifiers are equivalent).deptno
, dept_no
, "dept_no"
,
"Department Number"
,
"Identifier ""with quotes"""
.[] rr:column "deptno". [] rr:column "dept_no". [] rr:column "\"dept_no\"". [] rr:column "\"Department Number\"". [] rr:column "\"Identifier \"\"with quotes\"\"\"".These rules are for Core SQL 2008. See Section 3, Conformance regarding databases that do not conform to this version of SQL.
rr:tableName
)A SQL base table or view is a
logical table containing
SQL data from a base table or view in the
input database.
A SQL base table or view is represented by a resource that
has exactly one rr:tableName
property.
The value of rr:tableName
specifies the
table or view name of the base table or view.
Its value MUST
be a valid schema-qualified name
that names an existing base table or view in the
input database.
A schema-qualified name
is a sequence of one, two or three valid
SQL identifiers, separated
by the dot character (“.
”). The three identifiers
name, respectively, a catalog, a schema, and a table or view.
If no catalog or schema is specified, then the
default catalog and
default schema of the
SQL connection are assumed.
The effective SQL query of a SQL base table or view is:
SELECT * FROM {table}
with {table}
replaced with the
table or view name.
The following example shows a logical table specified using a schema-qualified table name.
[] rr:tableName "SCOTT.DEPT".
The following example shows a logical table specified using an unqualified table name. The SQL connection's default schema will be used.
[] rr:tableName "DEPT".
rr:sqlQuery
, rr:sqlVersion
)An R2RML view
is a logical table whose contents
are the result of executing a SQL query against the
input database. It is represented
by a resource that has exactly one rr:sqlQuery
property,
whose value is a literal with a
lexical form that is a valid
SQL query.
R2RML mappings sometimes require data transformation, computation,
or filtering before
generating triples from the database. This can be achieved by defining
a SQL view in the input database
and referring to it with
rr:tableName
.
However, this approach
may sometimes not be practical for lack of database privileges or other
reasons. R2RML views
achieve the same effect without requiring changes to the
input database.
Note that unlike “real” SQL views, an R2RML view can not be used as an input table in further SQL queries.
A SQL query is a SELECT
query in the SQL language that can be executed over the
input database.
The string MUST
conform to the production
<direct select statement: multiple rows>
in [SQL2] with an
OPTIONAL trailing semicolon character and
OPTIONAL surrounding white space (excluding
comments) as defined in [TURTLE].
It MUST be valid to execute over
the SQL connection.
The result of the query execution
MUST NOT have duplicate
column names.
Any columns in the SELECT
list derived by projecting an expression SHOULD
be named, because otherwise they cannot be reliably referenced in the
rest of the mapping.
Database objects referenced in the SQL query MAY be qualified with a catalog or schema name. For any database objects referenced without an explicit catalog name or schema name, the default catalog and default schema of the SQL connection are assumed.
For example, the following SELECT
query is
not a valid R2RML SQL query
because the result contains a duplicate column name DEPTNO
:
SELECT EMP.DEPTNO, 1 AS DEPTNO FROM EMP;
As a further example, the following SELECT
query
SHOULD NOT be used, because it
contains an unnamed column derived from a COUNT
expression:
SELECT DEPTNO, COUNT(EMPNO) FROM EMP GROUP BY DEPTNO;
An R2RML view
MAY have one or more
SQL version identifiers.
They MUST be valid IRIs
and are represented as values of the rr:sqlVersion
property. The following SQL version
identifier indicates that the SQL query conforms to
Core SQL 2008:
http://www.w3.org/ns/r2rml#SQL2008
The absence of a SQL version identifier indicates that no claim to Core SQL 2008 conformance is made.
No further identifiers besides rr:SQL2008
are defined in this specification.
The RDB2RDF Working Group intends to maintain a non-normative
list
of identifiers for other SQL versions
[SQLIRIS].
The effective SQL query
of an R2RML view is the value of its
rr:sqlQuery
property.
The following example shows a logical table specified as an R2RML view conforming to Core SQL 2008.
[] rr:sqlQuery """ Select ('Department' || DEPTNO) AS DEPTID , DEPTNO , DNAME , LOC from SCOTT.DEPT """; rr:sqlVersion rr:SQL2008.
A triples map specifies a rule for translating each row of a logical table to zero or more RDF triples.
The RDF triples generated from one row in the logical table all share the same subject.
A triples map is represented by a resource that references the following other resources:
rr:logicalTable
property.

They specify pairs of predicate maps and object maps that,
together with the
subjects generated by the subject map, may form one or more
RDF triples for each row.The referenced columns of all term maps of a triples map (subject map, predicate maps, object maps, graph maps) MUST be column names that exist in the term map's logical table.
The following example shows a triples map including its logical table, subject map, and two predicate-object maps.
[] rr:logicalTable [ rr:tableName "DEPT" ]; rr:subjectMap [ rr:template "http://data.example.com/department/{DEPTNO}" ]; rr:predicateObjectMap [ rr:predicate ex:name; rr:objectMap [ rr:column "DNAME" ]; ]; rr:predicateObjectMap [ rr:predicate ex:location; rr:objectMap [ rr:column "LOC" ]; ].
A subject map is a term map. It specifies a rule for generating the subjects of the RDF triples generated by a triples map.
rr:class
)A subject map MAY
have one or more class IRIs. They are
represented by the rr:class
property. The values
of the rr:class
property
MUST be IRIs.
For each RDF term generated by the subject map,
RDF triples with predicate
rdf:type
and the class IRI as object will be generated.
Mappings where the class IRI is not constant, but needs
to be computed based on the contents of the database, can be achieved by
defining a predicate-object map
with predicate rdf:type
and a non-constant
object map.
In the following example, the generated subject will be asserted
as an instance of the ex:Employee
class.
[] rr:template "http://data.example.com/employee/{EMPNO}"; rr:class ex:Employee.
Using the example EMP
table,
the following RDF triple will be generated:
<http://data.example.com/emp/7369> rdf:type ex:Employee.
A predicate-object map is a function that creates one or more predicate-object pairs for each logical table row of a logical table. It is used in conjunction with a subject map to generate RDF triples in a triples map.
A predicate-object map is represented by a resource that references the following other resources:
One or more predicate maps. Each of them may be specified in one of two ways:
rr:predicateMap
property, whose value
MUST be a
predicate map, orrr:predicate
.One or more object maps or referencing object maps. Each of them may be specified in one of two ways:
rr:objectMap
property, whose value
MUST be either an
object map, or a
referencing object map.rr:object
.A predicate map is a term map.
An object map is a term map.
An RDF term is either an IRI, or a blank node, or a literal.
A term map is a function that generates an RDF term from a logical table row. The result of that function is known as the term map's generated RDF term.
Term maps are used to generate the subjects, predicates and objects of the RDF triples that are generated by a triples map. Consequently, there are several kinds of term maps, depending on where in the mapping they occur: subject maps, predicate maps, object maps and graph maps.
A term map MUST be exactly one of the following:
The referenced columns of a term map are the set of column names referenced in the term map and depend on the type of term map.
rr:constant
)A constant-valued term map
is a term map that ignores the
logical table row and always generates
the same RDF term. A constant-valued term map is represented by a
resource that has exactly one rr:constant
property.
The constant value of a
constant-valued term map
is the RDF term that is the value of its rr:constant
property.
If the constant-valued term map is a subject map, predicate map or graph map, then its constant value MUST be an IRI.
If the constant-valued term map is an object map, then its constant value MUST be an IRI or literal.
The referenced columns of a constant-valued term map is the empty set.
Constant-valued term maps can be expressed more concisely using the
constant shortcut properties
rr:subject
, rr:predicate
,
rr:object
and rr:graph
.
Occurrences of these properties MUST be
treated exactly as if the following triples were present in the
mapping graph instead:
| Triple involving constant shortcut property | Replacement triples |
|---|---|
?x rr:subject ?y. |
?x rr:subjectMap [ rr:constant ?y ]. |
?x rr:predicate ?y. |
?x rr:predicateMap [ rr:constant ?y ]. |
?x rr:object ?y. |
?x rr:objectMap [ rr:constant ?y ]. |
?x rr:graph ?y. |
?x rr:graphMap [ rr:constant ?y ]. |
The following example shows a predicate-object map that uses a constant-valued term map both for its predicate and for its object.
[] rr:predicateMap [ rr:constant rdf:type ]; rr:objectMap [ rr:constant ex:Employee ].
If added to a triples map,
this predicate-object map would add the following triple to
all resources ?x
generated by the triples map:
?x rdf:type ex:Employee.
The following example uses constant shortcut properties and is equivalent to the example above:
[] rr:predicate rdf:type; rr:object ex:Employee.
rr:column
)A column-valued term map
is a term map that is represented by
a resource that has exactly one rr:column
property.
The value of the rr:column
property
MUST be a valid
column name. The
column value of the term map
is the data value of that column in a given
logical table row.
The referenced columns of
a column-valued term map
is the singleton set containing the value of the
term map's rr:column
property.
The following example defines an object map
that generates literals from the
DNAME
column of some logical table.
[] rr:objectMap [ rr:column "DNAME" ].
Using the sample row from the
DEPT
table as a logical table
row, the column value of the object map
would be “APPSERVER
”.
rr:template
)A template-valued term map
is a term map that is represented by
a resource that has exactly one rr:template
property.
The value of the rr:template
property
MUST be a valid
string template.
A string template is a
format string that can be used to build strings from multiple
components. It can reference
column names by enclosing
them in curly braces (“{
” and “}
”).
The following syntax rules apply to valid
string templates:
\
”). This also applies to curly braces within column names.\
”)
MUST be escaped by
preceding them with another backslash character, yielding “\\
”.
This also applies to backslashes within column names.rr:IRI
(see note below).The template value of the term map for a given logical table row is determined as follows:
result
be the
template stringresult
:
value
be the data value of the
column whose name is enclosed in the curly bracesvalue
is NULL
,
then return NULL
value
be the
natural RDF lexical form
corresponding to value
rr:IRI
, then replace the pair of curly braces
with an IRI-safe version of
value
; otherwise, replace the pair
of curly braces with value
result
The IRI-safe version of a string
is obtained by applying the following transformation to any character
that is not in the
iunreserved
production in
[RFC3987]:
The following table shows examples of strings and their IRI-safe versions:
| String | IRI-safe version |
|---|---|
| 42 | 42 |
| Hello World! | Hello%20World%21 |
| 2011-08-23T22:17:00Z | 2011-08-23T22%3A17%3A00Z |
| ~A_17.1-2 | ~A_17.1-2 |
| 葉篤正 | 葉篤正 |
R2RML always performs percent-encoding when IRIs are
generated from string templates. If IRIs need to be generated without
percent-encoding, then rr:column
should be used instead
of rr:template
, with an
R2RML view that performs the string
concatenation.
In the case of string templates
that generate IRIs,
any single character that is legal in an IRI, but percent-encoded
in the IRI-safe version of a data value, is a
safe separator.
This includes in particular the eleven sub-delim
characters defined in
[RFC3987]:
!$&'()*+,;=
The referenced columns of a template-valued term map is the set of column names enclosed in unescaped curly braces in the template string.
The following example defines a
subject map that generates
IRIs from the
DEPTNO
column of a logical table.
[] rr:subjectMap [ rr:template "http://data.example.com/department/{DEPTNO}" ].
Using the sample row from the
DEPT
table as a logical table
row, the template value of the subject map
would be:
http://data.example.com/department/10
The following example shows how an IRI-safe template value is created:
[] rr:subjectMap [ rr:template "http://data.example.com/site/{LOC}" ].
Using the sample row from the
DEPT
table as a logical table
row, the template value of the subject map
would be:
http://data.example.com/site/NEW%20YORK
The space character is not in the iunreserved
set,
and therefore percent-encoding is applied to the character, yielding
“%20
”.
The following example shows the use of backslash escapes in string templates. The template will generate a fancy title such as
{{{ \o/ Hello World! \o/ }}}
from a string “Hello World!
” in the TITLE
column. By default, rr:template
generates IRIs. Since
the intention here is to create a literal instead,
the term type has to be set.
[] rr:objectMap [ rr:template "\\{\\{\\{ \\\\o/ {TITLE} \\\\o/ \\}\\}\\}"; rr:termType rr:Literal; ].
Note that because backslashes need to be escaped by a second backslash in the Turtle syntax [TURTLE], a double backslash is needed to escape each curly brace, and to get one literal backslash in the output one needs to write four backslashes in the template.
rr:termType
)The term type of a column-valued term map or template-valued term map determines the kind of generated RDF term (IRIs, blank nodes or literals).
If the term map has an optional rr:termType
property,
then its term type
is the value of that property. The value MUST
be an IRI and MUST be
one of the following options:
rr:IRI
or rr:BlankNode
rr:IRI
rr:IRI
, rr:BlankNode
, or rr:Literal
rr:IRI
If the term map does not have a rr:termType
property,
then its term type is:
rr:Literal
, if it is an
object map and at least one of the following
conditions is true:
rr:language
property (and thus a
specified language tag).rr:datatype
property (and thus a
specified datatype).rr:IRI
, otherwise.Term maps with term type rr:IRI
cause data errors if the value is not a
valid IRI
(see generated RDF term for details).
Data values from the input database may require percent-encoding before
they can be used in IRIs.

Constant-valued term maps
are not considered as having a term type,
and specifying rr:termType
on these term maps has no effect.
The type of the generated RDF term is determined directly by the
value of rr:constant
: If it is an IRI, then an
IRI will be generated; if it is a literal, a literal will be
generated.
rr:language
)A term map with a
term type of rr:Literal
MAY have a
specified language tag.
It is represented by the rr:language
property on a term map.
If present, its value MUST be
a valid language tag.
A specified language tag causes generated literals to be
language-tagged plain literals. In the following example, plain
literals with language tag “en-us
” (U.S. English)
will be generated for the data values in the DNAME
column.
[] rr:objectMap [ rr:column "DNAME"; rr:language "en-us" ].
rr:datatype
)A datatypeable term map is a
term map with a
term type of rr:Literal
that does not have a
specified language tag.
Datatypeable term maps may generate
typed literals. The datatype
of these literals can be automatically determined based on the
SQL datatype of the underlying logical table column (producing a
natural RDF literal), or
it can be explicitly overridden using rr:datatype
(producing a datatype-override
RDF literal).
A datatypeable term map
MAY have a rr:datatype
property.
Its value MUST be an IRI.
This IRI is the specified datatype
of the term map.
A term map MUST NOT have more than one
rr:datatype
value.
A term map that is not a
datatypeable term map
MUST NOT have an rr:datatype
property.
The implicit SQL datatype
of a datatypeable term map is
CHARACTER VARYING
if the term map is a
template-valued term map;
otherwise, it is the SQL datatype of the respective column in the
logical table row.
See generated RDF term for further details on generating literals from term maps.
One cannot explicitly state that a
plain literal without
language tag should be generated.
They are the default for string columns. To generate one from a
non-string column, a
template-valued term map
with a template such as "{MY_COLUMN}"
and a
term type of rr:Literal
can be used.
The following example shows an object map
that overrides the default datatype of the logical table with
an explicitly specified xsd:positiveInteger
type.
A datatype-override
RDF literal of that datatype will be generated from whatever
is in the EMPNO
column.
[] rr:objectMap [ rr:column "EMPNO"; rr:datatype xsd:positiveInteger ].
rr:inverseExpression
)An inverse expression is a
string template associated with
a column-valued term map or
template-value term map.
It is represented by the value of the rr:inverseExpression
property. This property is OPTIONAL and there
MUST NOT be more than one for a term map.
Inverse expressions are useful for optimizing term maps that reference derived columns in R2RML views. An inverse expression specifies an expression that allows “reversing” of a generated RDF term and the construction of a SQL query that efficiently retrieves the logical table row from which the term was generated. In particular, it allows the use of indexes on the underlying relational tables.
Every pair of unescaped curly braces in the inverse expression is a column reference in an inverse expression. The string between the braces MUST be a valid column name.
An inverse expression MUST satisfy the following condition:
SELECT * FROM ({query}) AS tmp WHERE {expr}where
{query}
is the
effective SQL query
of t, and {expr}
is
instantiation(r)NULL
, same-term(r)
MUST be exactly the set of logical table rows
in t whose
generated RDF term is
also g.For example, for the DEPTID
column in the
logical table used for
mapping the DEPT
table in
this example mapping,
an inverse expression could be defined as follows:
[] rr:column "DEPTID"; rr:inverseExpression "{DEPTNO} = SUBSTRING({DEPTID}, CHARACTER_LENGTH('Department')+1)";
This facilitates the use of an existing index on the DEPTNO
column of the DEPT table.
A quoted and escaped data value
is any SQL string that matches the <literal>
or
<null specification>
productions of
[SQL2]. This string can be used in
a SQL query to specify a SQL data value. Examples:
27
'foo'
'foo''bar'
TRUE
DATE '2011-11-11'
NULL
rr:parentTriplesMap
, rr:joinCondition
, rr:child
and rr:parent
)A referencing object map allows using the subjects of another triples map as the objects generated by a predicate-object map. Since both triples maps may be based on different logical tables, this may require a join between the logical tables. This is not restricted to 1:1 joins.
A referencing object map is represented by a resource that:
rr:parentTriplesMap
property, whose value
MUST be a
triples map, known as the
referencing object map's parent
triples map.rr:joinCondition
properties, whose values
MUST be
join conditions.A join condition is represented by a resource that has exactly one value for each of the following two properties:
rr:child
, whose value is known as the join condition's
child column and
MUST be a
column name that exists in the
logical table of the
triples map that contains the
referencing object maprr:parent
, whose value is known as the join condition's
parent column and
MUST be a
column name that exists in the
logical table of the
referencing object map's
parent triples map.The child query of a referencing object map is the effective SQL query of the logical table of the term map containing the referencing object map.
The parent query of a referencing object map is the effective SQL query of the logical table of its parent triples map.
If the child query and parent query of a referencing object map are not identical, then the referencing object map MUST have at least one join condition.
The joint SQL query of a referencing object map is:
SELECT * FROM ({child-query}) AS tmp
SELECT * FROM ({child-query}) AS child, ({parent-query}) AS parent WHERE child.{child-column1}=parent.{parent-column1} AND child.{child-column2}=parent.{parent-column2} AND ...where
{child-query}
is the referencing object map's
child query,
{parent-query}
is its
parent query,
{child-column1}
and
{parent-column1}
are the
child column and
parent column of its first
join condition, and so on.
The order of the join conditions is chosen arbitrarily.The joint SQL query is used when generating RDF triples from referencing object maps.
The following example shows a referencing object map as part of a predicate-object map:
[] rr:predicateObjectMap [ rr:predicate ex:department; rr:objectMap [ rr:parentTriplesMap <#TriplesMap2>; rr:joinCondition [ rr:child "DEPTNO"; rr:parent "DEPTNO"; ]; ]; ].
If the logical table of the surrounding
triples map is EMP
, and the logical table
of <#TriplesMap2>
is DEPT
,
this would result in a join between these two tables
with the condition
EMP.DEPTNO = DEPT.DEPTNO
and the objects of the triples would be generated using
the subject map of <#TriplesMap2>
.
Given the two example tables, and subject maps as defined in the example mapping, this would result in a triple:
<http://data.example.com/employee/7369> ex:department <http://data.example.com/department/10>.
The following example shows a
referencing object map
that does not have a join condition.
It creates two kinds of resources from the
DEPT
table:
departments and sites.
<#DeptTriplesMap> rr:logicalTable [ rr:tableName "DEPT" ]; rr:subjectMap [ rr:template "department/{DEPTNO}"; rr:class ex:Department; ]; rr:predicateObjectMap [ rr:predicate ex:location; rr:objectMap [ rr:parentTriplesMap <#SiteTriplesMap> ]; ]. <#SiteTriplesMap> rr:logicalTable [ rr:tableName "DEPT" ]; rr:subjectMap [ rr:template "site/{LOC}"; rr:class ex:Site; ]; rr:predicateObjectMap [ rr:predicate ex:siteName; rr:objectMap [ ex:column "LOC" ]; ].
An ex:Site
resource is created
for each distinct value in the LOC
column, using the
<#SiteTriplesMap>
. Departments and sites are
linked by ex:location
triples, and the objects
of these triples are specified using a
referencing object map
that references the sites triples map. No join condition is
needed as both triples maps use the same logical table
(the base table DEPT
). Given the example table,
this mapping would result in four triples
(assuming an appropriate base IRI):
<http://data.example.com/department/10> rdf:type ex:Department. <http://data.example.com/department/10> ex:location <http://data.example.com/site/NEW%20YORK>. <http://data.example.com/site/NEW%20YORK> rdf:type ex:Site. <http://data.example.com/site/NEW%20YORK> ex:siteName "NEW YORK".
Each triple generated from an R2RML mapping is placed into one or more graphs of the output dataset. Possible target graphs are the unnamed default graph, and the IRI-named named graphs.
Any subject map or predicate-object map MAY have one or more associated graph maps. They are specified in one of two ways:
rr:graphMap
property, whose value
MUST be a
graph map,rr:graph
.Graph maps are themselves term maps. When RDF triples are generated, the set of target graphs is determined by taking into account any graph maps associated with the subject map or predicate-object map.
If a graph map generates the special
IRI rr:defaultGraph
, then the target graph is the
default graph of the
output dataset.
In the following subject map example,
all generated RDF triples will be stored in the named graph
ex:DepartmentGraph
.
[] rr:subjectMap [ rr:template "http://data.example.com/department/{DEPTNO}"; rr:graphMap [ rr:constant ex:DepartmentGraph ]; ].
This is equivalent to the following example, which uses a constant shortcut property:
[] rr:subjectMap [ rr:template "http://data.example.com/department/{DEPTNO}"; rr:graph ex:DepartmentGraph; ].
In the following example, RDF triples are placed into named graphs according to the job title of employees:
[] rr:subjectMap [ rr:template "http://data.example.com/employee/{EMPNO}"; rr:graphMap [ rr:template "http://data.example.com/jobgraph/{JOB}" ]; ].
The triples generated from the EMP
table would be placed in the named graph with the following IRI:
<http://data.example.com/jobgraph/CLERK>
Blank nodes in the output dataset are scoped to a single RDF graph. If the same blank node identifier occurs in multiple RDF triples that are in the same graph, then the triples will share the same blank node. If, however, the same blank node identifier occurs in multiple graphs, then a distinct blank node be created for each graph. An R2RML-generated blank node can never be shared by two triples in two different graphs.
This implies that triples generated from a single logical table row will have different subjects if the subjects are blank nodes and the triples are placed into different graphs.
This section defines mappings from SQL data values to RDF literals.
This section defines the following mappings from SQL data values:
TIMESTAMP
is used in an IRI
template.rr:datatype
.The mappings cover all predefined Core SQL 2008 datatypes except
INTERVAL
. The natural mappings may be
extended with custom handling
for other types, such as vendor-specific
SQL datatypes. In the absence of such extensions, the natural mappings
fall back on a simple cast to string
for all unsupported SQL datatypes.
The mappings are referenced in the R2RML term generation rules.
An informative summary of XSD lexical forms is provided to aid implementers.
The natural RDF literal corresponding to a SQL data value is the result of applying the following steps:
CHARACTER
, CHARACTER VARYING
, CHARACTER
LARGE OBJECT
, NATIONAL CHARACTER
, NATIONAL
CHARACTER VARYING
, NATIONAL CHARACTER LARGE OBJECT
),
then the result is a
plain literal without
language tag whose
lexical form is the SQL data value.1
, +1
, 1.0
and
1.0E0
), then the choice is implementation-dependent.
However, the choice MUST be made so that
given a target RDF datatype and value, the same lexical form
is chosen consistently (e.g., INTEGER 5
and
BIGINT 5
must be mapped to the same lexical form,
as both are mapped to the RDF datatype xsd:integer
and
are equal values; mapping one to 5
and the other to
+5
would be an error). The
canonical lexical representation
[XMLSCHEMA2]
MAY be chosen.
(See also: Summary of XSD Lexical Forms)| SQL datatype | RDF datatype | Lexical transformation (informative) |
|---|---|---|
BINARY , BINARY VARYING , BINARY LARGE OBJECT |
xsd:hexBinary |
xsd:hexBinary lexical mapping |
NUMERIC , DECIMAL |
xsd:decimal |
none required |
SMALLINT , INTEGER , BIGINT |
xsd:integer |
none required |
FLOAT , REAL , DOUBLE PRECISION |
xsd:double |
none required |
BOOLEAN |
xsd:boolean |
ensure lowercase (true , false ) |
DATE |
xsd:date |
none required |
TIME |
xsd:time |
none required |
TIMESTAMP |
xsd:dateTime |
replace space character with “T ” |
INTERVAL |
undefined | undefined |
R2RML extensions that handle vendor-specific or user-defined datatypes beyond those of Core SQL 2008 are expected to behave as if the table above contained additional rows that associate the SQL datatypes with appropriate RDF-compatible datatypes (e.g., the XML Schema built-in types [XMLSCHEMA2]), and appropriate lexical transformations where required. Note however that future versions of R2RML may also normatively add additional rows to this table.
The translation of INTERVAL
is left
undefined due to the complexity of the translation.
[SQL14] describes a translation of
INTERVAL
to xdt:yearMonthDuration
and
xdt:dayTimeDuration
.
In [SQL2],
the precision of many SQL datatypes is not fixed, but left
implementation-defined. Therefore, the mapping to XML Schema datatypes
must rely on arbitrary-precision types such as
xsd:decimal
, xsd:integer
and
xsd:dateTime
. Implementers of the mapping
may wish to set upper limits for the supported precision of these XSD types.
The XML Schema specification allows such partial implementations of
infinite datatypes [XMLSCHEMA2],
and defines specific minimum requirements.
The natural RDF datatype corresponding to a SQL datatype is the value of the RDF datatype column in the row corresponding to the SQL datatype in the table above.
The natural RDF lexical form corresponding to a SQL data value is the lexical form of its corresponding natural RDF literal, with the additional constraint that the canonical lexical representation [XMLSCHEMA2] SHOULD be chosen.
The canonical RDF lexical form corresponding to a SQL data value is the lexical form of its corresponding natural RDF literal, with the additional constraint that the canonical lexical representation [XMLSCHEMA2] MUST be chosen.
Cast to string is an
implementation-dependent function that maps SQL data values
to equivalent Unicode strings. It is undefined for the following
kinds of SQL datatypes:
collection types, row types, user-defined types without a user-defined
string CAST
, reference types whose referenced type does
not have a user-defined string CAST
, binary types.
Cast to string
is a fallback that handles vendor-specific and user-defined datatypes
not supported by the R2RML processor. It can be implemented in a number
of ways, including explicit SQL casts (“CAST(value
AS VARCHAR(n))
”, where n is an arbitrary
large integer), implicit SQL casts
(concatenation with the empty string), or by employing a
database access API that presents return values as strings.
The datatype-override RDF literal corresponding to a SQL data value v and a datatype IRI dt, is a typed literal whose lexical form is the natural RDF lexical form corresponding to v, and whose datatype IRI is dt. If the typed literal is ill-typed, then a data error is raised.
A typed literal is ill-typed in R2RML if its datatype IRI denotes a validatable RDF datatype and its lexical form is not in the lexical space of the RDF datatype identified by its datatype IRI. (See also: Summary of XSD Lexical Forms)
The set of validatable RDF datatypes includes all datatypes in the RDF datatype column of the table of natural datatype mappings, as defined in [XMLSCHEMA2]. This set MAY include implementation-defined additional RDF datatypes.
For example, "X"^^xsd:boolean
is ill-typed because
xsd:boolean
is a validatable RDF datatype in R2RML, and
“X
” is not in the
lexical space of
xsd:boolean
[XMLSCHEMA2].
The same non-character-string SQL data value can typically be
represented in multiple different string forms. For example,
the DOUBLE
value 1 can be represented as
1
, +1
, 1.0
and 1.0E0
.
This can cause interoperability issues when such values
are used in string contexts, for example when using them to generate
IRIs. Two IRIs that are character-for-character
equivalent, except one contains 1
where the other
contains 1.0
, will not “link up” in an RDF graph – they
are two different nodes.
To reduce portability issues arising from such conversions, this specification recommends that implementations convert non-string data values to a canonical form (see natural RDF lexical form). However, this is not a strict requirement. Therefore, when portability between R2RML implementations is a concern, mapping authors SHOULD NOT use non-character-string columns in contexts where strings are produced:
rr:column
when IRIs or blank nodes are
produced,rr:column
when rr:language
or an rr:datatype
other than the
natural RDF datatype is used,
andrr:template
.In these contexts, if portability is to be maximized, then mapping authors SHOULD use an R2RML view instead and explicitly convert the non-string column to a string column using an SQL expression.
Note that this is not a problem when natural RDF literals are generated from such columns, because the resulting literal has a corresponding non-string XSD datatype, and equivalences between different lexical forms within these datatype are well-defined.
The natural mappings make reference to various XSD datatypes and require that SQL data values be converted to strings that are appropriate as lexical forms for these datatypes. This subsection gives examples of these lexical forms in order to aid implementers of the mappings. This subsection is non-normative; the normative definitions of the lexical spaces as well as the canonical lexical mappings are found in W3C XML Schema Definition Language (XSD) 1.1 Part 2: Datatypes [XMLSCHEMA2].
A general approach that may be used for implementing the natural mappings is as follows:
xsd:hexBinary
,
xsd:dateTime
and xsd:boolean
.| RDF datatype | Non-canonical lexical forms | Canonical lexical forms | Comments |
|---|---|---|---|
xsd:hexBinary |
5232524d4c |
5232524D4C |
Convert from SQL by applying xsd:hexBinary lexical mapping. |
xsd:decimal |
.224 |
0.224 |
|
+001 |
1 |
||
42.0 |
42 |
||
-5.9000 |
-5.9 |
||
xsd:integer |
-05 |
-5 |
|
+333 |
333 |
||
00 |
0 |
||
xsd:double |
-5.90 |
-5.9E0 |
Also supports INF , -INF , NaN and -0.0E0 ,but these do not appear in standard SQL. |
+0.00014770215000 |
1.4770215E-4 |
||
+01E+3 |
1.0E3 |
||
100.0 |
1.0E2 |
||
0 |
0.0E0 |
||
xsd:boolean |
1 |
true |
Must be lowercase. |
0 |
false |
||
xsd:date |
2011-08-23 |
Dates in SQL don't have timezone offsets. They are optional in XSD. |
|
xsd:time |
22:17:34.885+00:00 |
22:17:34.885Z |
May or may not have timezone offset. |
22:17:34.000 |
22:17:34 |
||
22:17:34.1+01:00 |
22:17:34.1+01:00 |
||
xsd:dateTime |
2011-08-23T22:17:00.000+00:00 |
2011-08-23T22:17:00Z |
May or may not have timezone offset. Convert from SQL by replacing space wiht “ T ”. |
The output dataset of an R2RML mapping is an RDF dataset that contains the generated RDF triples for each of the triples maps of the R2RML mapping. The output dataset MUST NOT contain any other RDF triples or named graphs besides these. However, R2RML processors MAY provide access to datasets that contain additional triples or graphs beyond those in the output dataset, such as inferred triples or provenance information.
If a table or column is not explicitly referenced in a triples map, then no RDF triples will be generated for that table or column.
Conforming R2RML processors MAY rename blank nodes when providing access to the output dataset. This means that client applications may see actual blank node identifiers that differ from those produced by the R2RML mapping. Client applications SHOULD NOT rely on the specific text of the blank node identifier for any purpose.
RDF syntaxes
and RDF APIs generally represent
blank nodes with
blank node identifiers.
But the characters allowed in blank node identifiers differ between
syntaxes, and not all characters occurring in the values produced by
a term map may be allowed, so a bijective
mapping function from values to valid blank node identifiers may be
required. The details of this mapping function are
implementation-dependent, and
R2RML processors may have to use
different functions for different output syntaxes or access interfaces.
Strings matching the regular expression
[a-zA-Z_][a-zA-Z_0-9-]*
are valid blank node identifiers
in all W3C-recommended RDF syntaxes (as of this document's publication).
RDF datasets may contain empty named graphs. R2RML cannot generate such output datasets.
This subsection describes the process of generating RDF triples from a triples map. This process adds RDF triples to the output dataset. Each generated triple is placed into one or more graphs of the output dataset.
The generated RDF triples are determined by the following algorithm. R2RML processors MAY use other means than implementing this algorithm to compute the generated RDF triples, as long as the result is the same.
sm
be the
subject map of the triples maprows
be the result of evaluating the
effective SQL query
of the triples map's
logical table using the
SQL connectionclasses
be the
class IRIs of sm
sgm
be the set of
graph maps of sm
row
in rows
,
apply the following steps:
subject
be the
generated RDF term that results
from applying sm
to
row
subject_graphs
be the set of
the generated RDF terms
that result from applying each term map in sgm
to row
class
in
classes
,
add triples to the output dataset
as follows:
Subject: subject
Predicate: rdf:type
Object: class
Target graphs: If sgm
is empty:
rr:defaultgraph
;
otherwise: subject_graphs
predicates
be the set of
generated RDF terms that result
from applying each of the predicate-object map's
predicate maps
to row
objects
be the set of
generated RDF terms that result
from applying each of the predicate-object map's
object maps (but not
referencing object maps)
to row
pogm
be the set of
graph maps of the predicate-object mappredicate-object_graphs
be the set of
generated RDF terms
that result from applying each graph map
in pogm
to row
predicate
,
object
>
where predicate
is a member of
predicates
and object
is a member of objects
,
add triples to the output dataset
as follows:
Subject: subject
Predicate: predicate
Object: object
Target graphs: If sgm
and
pogm
are empty: rr:defaultGraph
;
otherwise: union of subject_graphs
and predicate-object_graphs
psm
be the
subject map of the
parent triples map of the
referencing object mappogm
be the set of
graph maps of the predicate-object mapn
be the number of columns
in the logical table of the
triples maprows
be the result of evaluating the
joint SQL query
of the referencing object maprow
in rows
,
apply the following steps:
child_row
be the logical table row
derived by taking the first n
columns of
row
parent_row
be the logical table row
derived by taking all but the first n
columns of
row
subject
be the
generated RDF term that results
from applying sm
to
child_row
predicates
be the set of
generated RDF terms that result
from applying each of the predicate-object map's
predicate maps
to child_row
object
be the
generated RDF term that results
from applying psm
to
parent_row
subject_graphs
be the set of
generated RDF terms
that result from applying each
graph map of sgm
to child_row
predicate-object_graphs
be the set of
generated RDF terms
that result from applying each
graph map in pogm
to child_row
predicate
in predicates
,
add triples to the output dataset
as follows:
Subject: subject
Predicate: predicate
Object: object
Target graphs: If neither sgm
nor pogm
has any graph
maps: rr:defaultGraph
; otherwise: union of
subject_graphs
and predicate-object_graphs
“Add triples to the output dataset” is a process that takes the following inputs:
Execute the following steps:
rr:defaultGraph
,
add the triple to the default graph
of the output dataset.rr:defaultGraph
,
add the triple to a named graph
of that name in the output dataset.
If the output dataset does not contain a named graph with that IRI,
create it first.RDF graphs cannot contain duplicate RDF triples. Placing multiple equal triples into the same graph has the same effect as placing it into the graph only once. Also note the scope of blank nodes.
A term map is a function that generates an RDF term from a logical table row. The result of that function can be:
NULL
value,The generated RDF term of a term map for a given logical table row is determined as follows:
The term generation rules, applied to a value, are as follows:
NULL
, then no RDF term
is generated.rr:IRI
:
rr:BlankNode
:
rr:Literal
:
This appendix lists some terms normatively defined in other specifications.
The following terms are defined in RDF Concepts and Abstract Syntax [RDF] and used in R2RML:
The following terms are defined in SPARQL Query Language for RDF [SPARQL] and used in R2RML:
This appendix lists all the classes, properties and other terms defined by this specification within the R2RML vocabulary.
An RDFS representation of the vocabulary is available from the namespace IRI.
The following table lists all R2RML classes.
The third column contains minimum conditions that a resource has to fulfil in order to be considered member of the class. Where multiple conditions are listed, all must be fulfilled.
| Class | Represents | Minimum conditions |
|---|---|---|
rr:BaseTableOrView |
SQL base table or view | Having an rr:tableName property |
rr:GraphMap |
graph map | Being an rr:TermMap Being value of an rr:graphMap property |
rr:Join |
join condition | Having an rr:parent propertyHaving an rr:child property |
rr:LogicalTable |
logical table | Being one of its subclasses, rr:BaseTableOrView or rr:R2RMLView |
rr:ObjectMap |
object map | Being an rr:TermMap Being value of an rr:objectMap property |
rr:PredicateMap |
predicate map | Being an rr:TermMap Being value of an rr:predicateMap property |
rr:PredicateObjectMap |
predicate-object map | Having at least one of rr:predicate and rr:predicateMap Having at least one of rr:object and rr:objectMap |
rr:R2RMLView |
R2RML view | Having an rr:sqlQuery property |
rr:RefObjectMap |
referencing object map | Having an rr:parentTriplesMap property |
rr:SubjectMap |
subject map | Being an rr:TermMap Being value of an rr:subjectMap property |
rr:TermMap |
term map | Having exactly one of rr:constant , rr:column , rr:template |
rr:TriplesMap |
triples map | Having an rr:logicalTable propertyHaving exactly one of rr:subject and rr:subjectMap |
As noted earlier, a single node in an R2RML mapping graph may represent multiple mapping components and thus be typed as several of these classes. However, the following classes are disjoint:
rr:TermMap
and rr:RefObjectMap
rr:BaseTableOrView
and rr:SQLQuery
rr:constant
, rr:column
and rr:template
,
respectively)The following table lists all properties in the R2RML vocabulary.
The cardinality column indicates how often this property occurs within its context. Note that additional constraints not stated in this table might apply. The actual cardinality of some properties may depend on the presence or absence of other properties, and their values. Properties where this applies are indicated by an exclamation mark.
| Term | Denotes | Used with property |
|---|---|---|
rr:defaultGraph |
default graph | rr:graph |
rr:SQL2008 |
Core SQL 2008 | rr:sqlVersion |
rr:IRI |
IRI | rr:termType |
rr:BlankNode |
blank node | rr:termType |
rr:Literal |
literal | rr:termType |
The Editors would like to give special thanks to the following contributors: David McNeil greatly improved the quality of the specification with detailed reviews and comments. Nuno Lopes and Eric Prud'hommeaux contributed to the design of the mapping from SQL data values to RDF literals. Eric also worked on the mechanism for SQL compatibility. Boris Villazón-Terrazas drew the diagrams throughout the text, and kept them up-to-date throughout many iterations.
In addition, the Editors gratefully acknowledge contributions from: Marcelo Arenas, Sören Auer, Samir Batla, Alexander de Leon, Orri Erling, Lee Feigenbaum, Enrico Franconi, Howard Greenblatt, Wolfgang Halb, Harry Halpin, Michael Hausenblas, Patrick Hayes, Ivan Herman, Nophadol Jekjantuk, Li Ma, Nan Ma, Ashok Malhotra, Ivan Mikhailov, Percy Enrique Rivera Salas, Juan Sequeda, Ben Szekely, Ted Thibodeau, and Edward Thomas.


@hanwestby
"FollowMill has helped me grow my account like crazy. I didn't think it would work! But it DID!"
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There are a few proven methods for getting followers on Instagram. Most people that are actively growing their accounts use these methods and get results. (Targeting Hashtags, Liking Photos, Following/Unfollowing Accounts, Endless Swiping/Tapping, for Hours and Hours...) Long story short—it's A LOT of work.
That's where FollowMill comes in. We will use those proven methods to grow your account (automatically in the cloud). What does that mean? Choose some hashtags to target and our smart service will like photos and follow related accounts through your account, and you will see results.
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"FollowMill has helped me grow my account like crazy. I didn't think it would work! But it DID!"
"Since I signed up for FollowMill, I've received thousands of followers. Highly recommend!""
Quite affectionate and outgoing. She loves to get chin scratches and will roll around on the floor waiting for you give her more of them.
At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi
At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi
At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi
At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi


Games
Implementing the game logic is probably one of the hardest things,
but it's useful to at least acquaint yourself with the shape
of this type after you have made your Player
class.
public abstract class GameBase<TPlayer>
where TPlayer : Player
{
protected GameBase(
IMessageChannel channel,
IEnumerable<TPlayer> players,
bool setFirstPlayerImmediately = false);
protected IMessageChannel Channel { get; }
protected CircularLinkedList<TPlayer> Players { get; }
public Task<IEnumerable<IDMChannel>> PlayerChannels() { get; }
public Node<TPlayer> TurnPlayer { get; protected set; }
protected bool IsTurnPlayerFirstPlayer();
protected bool IsTurnPlayerLastPlayer();
protected virtual Task OnPlayerAdded(TPlayer player);
protected virtual Task OnPlayerKicked(TPlayer player);
public abstract string GetGameState();
public abstract Embed GetGameStateEmbed();
public abstract Task SetupGame();
public abstract Task StartGame();
public abstract Task NextTurn();
public Task EndGame(string endmsg);
public virtual async Task OnGameEnd();
}
This type is abstract, which means it must be inherited before it can be used.
Any abstract
members must also be overridden because the behavior is implementation-specific.
You'll also have to declare your Player
type when you inherit the base class.
Continuing on with our card game example:
public class CardGame : GameBase<CardPlayer> // Any player in a 'CardGame' is of type 'CardPlayer'.
{
// Example property that's needed for the game.
private CardDeck Deck { get; }
// Again, you need to call the base constructor.
public CardGame(
IMessageChannel channel,
IEnumerable<CardPlayer> players,
IEnumerable<Card> cards)
// Use the 'setFirstPlayerImmediately' flag to control
// where or not to set the 'TurnPlayer' to the first player
// or to an empty node. Default is 'false' (sets an empty node).
: base(channel, players, setFirstPlayerImmediately: false)
{
Deck = new CardDeck(cards);
}
public override Task SetupGame()
{
// Use this method to perform pre-game setup, like
// shuffling the Deck if you have a method for that at hand.
// If you're not 'await'ing anything, you can avoid
// warnings by using the following:
return Task.CompletedTask;
}
public override async Task StartGame()
{
// This method represents the 'real' start of the game,
// for example: dealing out cards to all players.
for (int i = 0; i < 5; i++)
{
foreach (var p in Players)
{
p.AddCard(Deck.Draw());
}
}
foreach (var p in Players)
{
await Task.Delay(1000);
// Ideally, you would have a '.ToString()' override on the 'Card' type for this.
await p.SendMessageAsync($"Your hand:\n{String.Join("\n", p.Hand)}");
}
}
// Example items for keeping track of the game state:
private int _turn = 0;
internal GameState State { get; private set; } = GameState.Setup;
public override Task NextTurn()
{
// This is where you put the logic that happens
// at the start of every turn.
_turn++;
State = GameState.StartOfTurn;
// Use 'TurnPlayer.Next' and assign it as the new TurnPlayer.
// The list will automatically cycle through once it reaches the end.
TurnPlayer = TurnPlayer.Next;
// On the other hand, if you would like to stop the game
// automatically once everyone has had a turn (or a set number of turns),
// you can use this method from the base class to check.
if (!IsTurnPlayerLastPlayer())
{
// Use 'TurnPlayer.Value' to get the
// actual instance value of the player.
TurnPlayer.Value.AddCard(Deck.Draw());
}
}
public override string GetGameState()
{
// This method should provide a summary of the state that the game is in.
// Starting in v1.2, you can also choose to implement 'GetGameStateEmbed()' instead
// if you want to get real fancy.
// You do not need to implement *both* methods, just make sure that your
// 'GameState' command doesn't call the one that remains unimplemented.
var sb = new StringBuilder($"State of the board at turn {_turn}:\n")
.AppendLine($"Turn state is {State.ToString()}.")
.AppendLine($"There are {Deck.Count} cards in the deck.")
.AppendLine($"It is {TurnPlayer.Value.User.Username}'s turn.");
foreach (var p in Players)
{
sb.AppendLine($"Player {p.User.Username} has {p.Hand.Count} cards in hand.");
}
return sb.ToString();
}
// Many more methods...
}
// Make an enum like this so you can use it in
// a custom precondition for your commands (see section 7).
internal enum GameState
{
Setup,
StartOfTurn,
//....
}


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There are eight predefined standard stream objects that are automatically created and initialized at program startup if the header <iostream> is included. These standard stream objects are associated with the C standard files stdin, stdout, and stderr, as shown in Table 26:
| Narrow character stream | Wide character stream | Associated C standard files |
cin | wcin | stdin |
cout | wcout | stdout |
cerr | wcerr | stderr |
clog | wclog | stderr |
Like the C standard files, these stream objects are all associated by default with the terminal.
The difference between clog and cerr is that clog is fully buffered, whereas output to cerr is written to the external device after each formatting. With a fully buffered stream, output to the actual external device is written only when the buffer is full. Thus clog is more efficient for redirecting output to a file, while cerr is mainly useful for terminal I/O. Writing to the external device after every formatting, to the terminal in the case of cerr, serves the purpose of synchronizing output to and input from the terminal. Also, the predefined streams are synchronized with their associated C standard files. See Section 35.6 for details.
The standard stream objects are initialized in such a way that they can be used even in constructors and destructors of non-local objects with static storage duration. However, care must be taken to always include the header <iostream> prior to the definition of any such object.
Since the initialization of the standard iostream objects is a fairly resource-intensive operation it is not advisable to include the header <iostream> just as a convenience to gain access to either or both of basic_istream and basic_ostream in translation units that do not refer to the objects. In such cases, include the headers <istream> and <ostream> instead.


Plotly/Dash Chart Demo
Line
MultiLine
3D
3D with Contours
Sankey Diagram
Bar and Lines
Sunburst Diagram
Gapminder Form
Animation Scatter
Gapminder Dash app
Tips Dash app


Documentation¶
sectionproperties is a python package for the analysis of arbitrary cross-sections using the finite element method written by Robbie van Leeuwen. sectionproperties can be used to determine section properties to be used in structural design and visualise cross-sectional stresses resulting from combinations of applied forces and bending moments.
A list of the current features of the package and implementation goals for future releases can be found in the README file on github.
Here’s a quick example that harnesses some of the power of sectionproperties and shows its simplicity:
import sectionproperties.pre.sections as sections
from sectionproperties.analysis.cross_section import CrossSection
# create geometry of the cross-section
geometry = sections.ISection(d=203, b=133, t_f=7.8, t_w=5.8, r=8.9, n_r=8)
# generate a finite element mesh
mesh = geometry.create_mesh(mesh_sizes=[2.5])
# create a CrossSection object for analysis
section = CrossSection(geometry, mesh)
# calculate various cross-section properties
section.calculate_geometric_properties()
section.calculate_warping_properties()
# print some of the calculated section properties
print(section.get_area()) # cross-section area
>>>3231.80
print(section.get_ic()) # second moments of area about the centroidal axis
>>>(23544664.29, 3063383.07, 0.00)
print(section.get_j()) # torsion constant
>>>62907.79
print(section.get_As()) # shear areas in the x & y directions
>>>(1842.17, 1120.18)
Support¶
Contact me on my email<EMAIL_ADDRESS>or raise an issue on the github issue tracker using one of the issue templates. If you have a request for a feature to be added to the sectionproperties package, please don’t hesitate to get in touch
License¶
The project is licensed under the MIT license.