Datasets

This document describes the dataset that is used for the Linköping GraphQL Benchmark (LinGBM). The dataset of LinGBM is generated by the BSBM data generator, which is based on an e-commerce use case. The dataset contains 9 entities and 8 relationships. Producers produce a set of products, which is offered by different vendors and different consumers have posted reviews about products.

Graph model

This part shows the Graph model of the dataset. The detailed information of cardinalities of the relationships refers to Relationships.

The namespaces in the diagram are shown as following:

Prefix	Namespace
rdf:	http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs:	http://www.w3.org/2000/01/rdf-schema#
foaf:	http://xmlns.com/foaf/0.1/
dc:	http://purl.org/dc/elements/1.1/
xsd:	http://www.w3.org/2001/XMLSchema#
rev:	http://purl.org/stuff/rev#
bsbm:	http://www4.wiwiss.fu-berlin.de/bizer/bsbm/v01/vocabulary/
bsbm-inst:	http://www4.wiwiss.fu-berlin.de/bizer/bsbm/v01/instances/

There are two graph representations of the dataset: RDF triple representation and Named Graphs representation. The examples of the representations refer to here.

Relational model

The dataset is also able to use relational representation. To make the graph model and relational model represent the same semantics, the BSBM data generator could output the dataset as a MySQL dump. This dump uses the following entity relationship and relational schema:

Relational schema:

Vendor (nr, label, comment, homepage, country, publisher, publishDate)
Offer (nr, product, producer, vendor, price, validFrom, validTo, deliveryDays, offerWebpage, publisher, publishDate)
Producer (nr, label, comment, homepage, country, publisher, publishDate)
Product (nr, label, comment, producer, propertyNum1, propertyNum2, propertyNum3, propertyNum4, propertyNum5, propertyNum6, propertyTex1, propertyTex2, propertyTex3, propertyTex4, propertyTex5, propertyTex6, publisher, publishDate)
Person (nr, name, mbox_sha1sum, country, publisher, publishDate)
Review (nr, product, producer, person, reviewDate, title, text, language, rating1, rating2, rating3, rating4, publisher, publishDate, ratingSite)
ProductFeature (nr, label, comment, publisher, publishDate)
ProductType (nr, label, comment, parent, publisher, publishDate)
ProductTypeProduct (product, productType)
ProductFeatureProduct (product, productFeature)

Data Generator

The data generator supports the following output formats: TODO: detailed description

Format	Option
N-Triples	-s nt
Turtle	-s ttl
XML	-s xml
TriG	-s trig
(My-)SQL dump	-s sql

Characteristics

The dataset is scalable to different sizes based on a given scale factor, the number of products. This tale gives an overview about the characteristics of BSBM datasets with different scale factors:

Scale Factor	1000	2000	5000	10,000
triples	27,886	377,241	1,620,320	3,421,251
Producers	22	42	106	206
Number of Vendors	12	23	48	99
Number of Offers	20,000	40,000	100,000
Number of Persons	503	1017	2553	5102
Number of Reviews	10,000	20,000	50,000	100,000
Number of Rating Sites	1	2	5	11
Product Features	4,745	4,745	10,519	10,519
Product Types	151	151	329	329

Generation Rules

This part introduces the data generation rules that are used to populate the dataset according to the given scale factor.

Product

Attribute	Data Type	range	note
Label	String	1-3 words
Comment	String	50-150 words
productPropertyTextualX	Literal	3-15 words
productPropertyNumericX	Integer	1-2000	normal distribution
productFeature			Every Product has about 10 -20 features
publishDate	date	2000-09-20 to 2006-12-23

Product Type

Attribute	Data Type	range
Label	String	1-3 words
Comment	String	20-50 words
publishDate	date	2000-05-20 to 2000-06-23

Product Features

Attribute	Data Type	range
Label	String	1-3 words
Comment	String	20-50 words
publishDate	date	2000-05-20 to 2000-06-23

Producer

Attribute	Data Type	range
Label	String	1-3 words
Comment	String	20-50 words
foaf:homepage	URI	the namespace of the producer
country	ISO3166	US 40%, UK 10%, JP 10%, CN 10%, 5% DE, 5% FR, 5% ES, 5% RU, 5% KR, 5% AT
publishDate	date	2000-07-20 to 2005-06-23

Offer

Attribute	Data Type	range
price		US-$ 5 to 10000
validFrom	date	0-180 days before the publication date
validTo	date	7-180 days after the publication date
deliveryDays	Integer	1-21
offerWebpage	URI	within the namespace of the producer
publishDate	date	today - 97 days) to today

Vendor

Attribute	Data Type	range
Label	String	1-3 words
Comment	String	20-50 words
foaf:homepage	URI	the namespace of the vendor
country	ISO3166	US 40%, UK 10%, JP 10%, CN 10%, 5% DE, 5% FR, 5% ES, 5% RU, 5% KR, 5% AT
publishDate	date	2000-09-20 to 2006-12-23

Person

Attribute	Data Type	range	note
Name	String	2-4 words
mbox_sha1sum	literal	random sha1 value	email address
country	ISO3166	US 40%, UK 10%, JP 10%, CN 10%, 5% DE, 5% FR, 5% ES, 5% RU, 5% KR, 5% AT
publishDate	date	2000-09-20 to 2006-12-23

Review

Attribute	Data Type	range	note
Title	String	4-15 words
Text	String	50-200	lang: (EN 50%, JA 10%, ZH 10%, 5% DE, 5% FR, 5% ES, 5% RU, 5% KR, 5% AT)
Review Date	date	Random date within the last year
RatingX	Integer	1 to 10	Reviews might include up to 4 types of ratings. The likelihood that a review has a rating of type X is 70%
publishDate	date	from Review Date to 2008-06-20

Relationship

Relationship	cardinalities	note
Producer-Product	1: N	One producer per Product; 50 products on average per producer
Product-Review	1: N	10 reviews per product on average; 1 product per Review, selection follows a normal distribution
Product-Offer	1: N	20 Offers on average per product; one Product per offer, selection follows a normal distribution
Person- Review	1: N	one author per Review; 20 reviews per person on average
Ratingsite-Review	1: N	Every Review belongs to one rating site; A rating site generated 10000 reviews on average
Vendors-Offers	1: N	one offer belongs to a vendor; 2000 offers on average per vendor
Product-ProductType	N:1	1 ProductType per product (leaves only)
Product-ProductFeature	M: N	10-20 ProductFeatures per product