In this paper, we propose the problem of implementing an efficient query processing system for incomplete temporal and geospatial information in RDFi as a challenge to the SSTD community.
Presented in : JIST2015, Yichang, China
Prototype: http://rc.lodac.nii.ac.jp/rdf4u/
Video: https://www.youtube.com/watch?v=z3roA9-Cp8g
Abstract: It is known that Semantic Web and Linked Open Data (LOD) are powerful technologies for knowledge management, and explicit knowledge is expected to be presented by RDF format (Resource Description Framework), but normal users are far from RDF due to technical skills required. As we learn, a concept-map or a node-link diagram can enhance the learning ability of learners from beginner to advanced user level, so RDF graph visualization can be a suitable tool for making users be familiar with Semantic technology. However, an RDF graph generated from the whole query result is not suitable for reading, because it is highly connected like a hairball and less organized. To make a graph presenting knowledge be more proper to read, this research introduces an approach to sparsify a graph using the combination of three main functions: graph simplification, triple ranking, and property selection. These functions are mostly initiated based on the interpretation of RDF data as knowledge units together with statistical analysis in order to deliver an easily-readable graph to users. A prototype is implemented to demonstrate the suitability and feasibility of the approach. It shows that the simple and flexible graph visualization is easy to read, and it creates the impression of users. In addition, the attractive tool helps to inspire users to realize the advantageous role of linked data in knowledge management.
Triplewave: a step towards RDF Stream Processing on the WebDaniele Dell'Aglio
The slides of my talk at INSIGHT Centre for Data Analytics (in NUI Galway) where I presented TripleWave (http://streamreasoning.github.io/TripleWave/), an open-source framework to create and publish streams of RDF data.
Large-Scale Geographically Weighted Regression on SparkViet-Trung TRAN
Geographically Weighted Regression (GWR) is a local version of spatial regression that captures spatial dependency in regression analysis. GWR has many application in practice as a visualization and prediction tool for spatial exploration- (e.g in climate, economy, medical). However, this locally regression model is slow in process upon the volume of calculations and the spatial getting bigger. Improving performance of GWR is an critical issue, but their distributed implementations have not been studied. Recently, with the advent of Spark as well MapReduce framework, the development of machine learning applications and parallel programming becomes easier. In this article, we propose several large-scale implementations of distributed GWR, leveraging Spark framework. We implemented and evaluated these approaches with large datasets. To our best knowledge, this is the first work addressing GWR at large-scale.
Presented in : JIST2015, Yichang, China
Prototype: http://rc.lodac.nii.ac.jp/rdf4u/
Video: https://www.youtube.com/watch?v=z3roA9-Cp8g
Abstract: It is known that Semantic Web and Linked Open Data (LOD) are powerful technologies for knowledge management, and explicit knowledge is expected to be presented by RDF format (Resource Description Framework), but normal users are far from RDF due to technical skills required. As we learn, a concept-map or a node-link diagram can enhance the learning ability of learners from beginner to advanced user level, so RDF graph visualization can be a suitable tool for making users be familiar with Semantic technology. However, an RDF graph generated from the whole query result is not suitable for reading, because it is highly connected like a hairball and less organized. To make a graph presenting knowledge be more proper to read, this research introduces an approach to sparsify a graph using the combination of three main functions: graph simplification, triple ranking, and property selection. These functions are mostly initiated based on the interpretation of RDF data as knowledge units together with statistical analysis in order to deliver an easily-readable graph to users. A prototype is implemented to demonstrate the suitability and feasibility of the approach. It shows that the simple and flexible graph visualization is easy to read, and it creates the impression of users. In addition, the attractive tool helps to inspire users to realize the advantageous role of linked data in knowledge management.
Triplewave: a step towards RDF Stream Processing on the WebDaniele Dell'Aglio
The slides of my talk at INSIGHT Centre for Data Analytics (in NUI Galway) where I presented TripleWave (http://streamreasoning.github.io/TripleWave/), an open-source framework to create and publish streams of RDF data.
Large-Scale Geographically Weighted Regression on SparkViet-Trung TRAN
Geographically Weighted Regression (GWR) is a local version of spatial regression that captures spatial dependency in regression analysis. GWR has many application in practice as a visualization and prediction tool for spatial exploration- (e.g in climate, economy, medical). However, this locally regression model is slow in process upon the volume of calculations and the spatial getting bigger. Improving performance of GWR is an critical issue, but their distributed implementations have not been studied. Recently, with the advent of Spark as well MapReduce framework, the development of machine learning applications and parallel programming becomes easier. In this article, we propose several large-scale implementations of distributed GWR, leveraging Spark framework. We implemented and evaluated these approaches with large datasets. To our best knowledge, this is the first work addressing GWR at large-scale.
Full version of http://www.slideshare.net/valexiev1/gvp-lodcidocshort. Same is available on http://vladimiralexiev.github.io/pres/20140905-CIDOC-GVP/index.html
CIDOC Congress, Dresden, Germany
2014-09-05: International Terminology Working Group: full version.
2014-09-09: Getty special session: short version
Knowledge Discovery tools using Linked Data techniques - {resentation for the Linked Data 4 Knowledge Discovery Workshop at ECML/PKDD2015 conference - http://events.kmi.open.ac.uk/ld4kd2015/ -
I summarize requirements for an "Open Analytics Environment" (aka "the Cauldron"), and some work being performed at the University of Chicago and Argonne National Laboratory towards its realization.
OpenML.org: Networked Science and IoT Data Streams by Jan van Rijn, Universit...EuroIoTa
OpenML enables truly collaborative machine learning. Scientists can post important data, inviting anyone to help analyze it. OpenML structures and organizes all results online to show the state of the art and push progress.
OpenML is being integrated in most popular machine learning environments, so you can automatically upload all your data, code, and experiments. And if you develop new tools, there's an API for that, plus people to help you.
OpenML allows you to search, compare, visualize, analyze and download all combined results online. Explore the state of the art, improve it, build on it, ask questions and start discussions
The aim of the EU FP 7 Large-Scale Integrating Project LarKC is to develop the Large Knowledge Collider (LarKC, for short, pronounced “lark”), a platform for massive distributed incomplete reasoning that will remove the scalability barriers of currently existing reasoning systems for the Semantic Web. The LarKC platform is available at larkc.sourceforge.net. This talk, is part of a tutorial for early users of the LarKC platform, and describes the data model used within LarKC.
Wi2015 - Clustering of Linked Open Data - the LODeX toolLaura Po
Presentation of the tool LODeX (http://www.dbgroup.unimore.it/lodex2/testCluster) at the 2015 IEEE/WIC/ACM International Conference on Web Intelligence, Singapore, December 6-8, 2015
Full version of http://www.slideshare.net/valexiev1/gvp-lodcidocshort. Same is available on http://vladimiralexiev.github.io/pres/20140905-CIDOC-GVP/index.html
CIDOC Congress, Dresden, Germany
2014-09-05: International Terminology Working Group: full version.
2014-09-09: Getty special session: short version
Knowledge Discovery tools using Linked Data techniques - {resentation for the Linked Data 4 Knowledge Discovery Workshop at ECML/PKDD2015 conference - http://events.kmi.open.ac.uk/ld4kd2015/ -
I summarize requirements for an "Open Analytics Environment" (aka "the Cauldron"), and some work being performed at the University of Chicago and Argonne National Laboratory towards its realization.
OpenML.org: Networked Science and IoT Data Streams by Jan van Rijn, Universit...EuroIoTa
OpenML enables truly collaborative machine learning. Scientists can post important data, inviting anyone to help analyze it. OpenML structures and organizes all results online to show the state of the art and push progress.
OpenML is being integrated in most popular machine learning environments, so you can automatically upload all your data, code, and experiments. And if you develop new tools, there's an API for that, plus people to help you.
OpenML allows you to search, compare, visualize, analyze and download all combined results online. Explore the state of the art, improve it, build on it, ask questions and start discussions
The aim of the EU FP 7 Large-Scale Integrating Project LarKC is to develop the Large Knowledge Collider (LarKC, for short, pronounced “lark”), a platform for massive distributed incomplete reasoning that will remove the scalability barriers of currently existing reasoning systems for the Semantic Web. The LarKC platform is available at larkc.sourceforge.net. This talk, is part of a tutorial for early users of the LarKC platform, and describes the data model used within LarKC.
Wi2015 - Clustering of Linked Open Data - the LODeX toolLaura Po
Presentation of the tool LODeX (http://www.dbgroup.unimore.it/lodex2/testCluster) at the 2015 IEEE/WIC/ACM International Conference on Web Intelligence, Singapore, December 6-8, 2015
We extend RDF with the ability to represent property values that exist, but are unknown or partially known, using constraints. Following ideas from the incomplete information literature, we develop a semantics for this extension of RDF, called RDFi, and study SPARQL query evaluation in this framework.
Linked geospatial data has recently received attention, as researchers and practitioners have started tapping the wealth of geospatial information available on the Web. Incomplete geospatial information, although appearing often in the applications captured by such datasets, is not represented and queried properly due to the lack of appropriate data models and query languages. We discuss our recent work on the model RDFi, an extension of RDF with the ability to represent property values that exist, but are unknown or partially known, using constraints, and an extension of the query language SPARQL with qualitative and quantitative geospatial querying capabilities. We demonstrate the usefulness of RDFi in geospatial Semantic Web applications by giving examples and comparing the modeling capabilities of RDFi with the ones of related Semantic Web systems.
Challenge@RuleML2015 Modeling Object-Relational Geolocation Knowledge in PSOA...RuleML
In recent years, many geospatial data sets have become available
on the Web. These data can be incorporated into real-world applications
to answer advanced geospatial queries. In this paper, we present
a use case to integrate a local data set with external geospatial data
sets on the Web. The data sets are modeled in different paradigms –
relational and object-centered. The integration uses Positional-Slotted
Object-Applicative (PSOA) RuleML, which combines the relational and
object-centered modeling paradigms for databases as well as knowledge
bases (KBs).
The linked open data cloud is constantly evolving as datasets are continuously updated with newer versions. As a result, representing, querying, and visualizing the temporal dimension of linked data is crucial. This is especially important for geospatial datasets that form the backbone of large scale open data publication efforts in many sectors of the economy (the public sector, the Earth observation sector). Although there has been some work on the representation and querying of linked geospatial data that change over time, to the best of our knowledge, there is currently no tool that offers spatiotemporal visualization of such data. Although the visualization of the temporal evolution of geospatial data is common practice in the GIS area, there is no tool that handles linked geospatial data and allows for the visualization of both the spatial and temporal dimensions, to the best of our knowledge. In this demo paper, we present SexTant, a Web-based system for the visualization and exploration of time-evolving linked geospatial data and the creation, sharing, and collaborative editing of "temporally-enriched" thematic maps which are produced by combining different sources of such data.
Computational Training and Data Literacy for Domain ScientistsJoshua Bloom
Presented at the National Academy of Sciences (11 April 2014, Washington, D.C.) at the workshop "Training Students to Extract Value from Big Data.” Discussion of computational and programming education at UC Berkeley. Emphasis on Python as a glue/gateway language. An advocation for the notion of first teaching "Data Literacy" to domain scientists before teaching Big Data proficiency.
Astronomical Data Processing on the LSST Scale with Apache SparkDatabricks
The next decade promises to be exciting for both astronomy and computer science with a number of large-scale astronomical surveys in preparation. One of the most important ones is Large Scale Survey Telescope, or LSST. LSST will produce the first ‘video’ of the deep sky in history by continually scanning the visible sky and taking one 3.2 giga-pixel image every 20 seconds. In this talk we will describe LSST’s unique design and how its image processing pipeline produces catalogs of astronomical objects. To process and quickly cross-match catalog data we built AXS (Astronomy Extensions for Spark), a system based on Apache Spark. We will explain its design and what is behind its great cross-matching performance.
RDF4U: RDF Graph Visualization by Interpreting Linked Data as KnowledgeRathachai Chawuthai
Presented in : JIST2015, Yichang, China
Prototype: http://rc.lodac.nii.ac.jp/rdf4u/
Video: https://www.youtube.com/watch?v=z3roA9-Cp8g
Abstract: It is known that Semantic Web and Linked Open Data (LOD) are powerful technologies for knowledge management, and explicit knowledge is expected to be presented by RDF format (Resource Description Framework), but normal users are far from RDF due to technical skills required. As we learn, a concept-map or a node-link diagram can enhance the learning ability of learners from beginner to advanced user level, so RDF graph visualization can be a suitable tool for making users be familiar with Semantic technology. However, an RDF graph generated from the whole query result is not suitable for reading, because it is highly connected like a hairball and less organized. To make a graph presenting knowledge be more proper to read, this research introduces an approach to sparsify a graph using the combination of three main functions: graph simplification, triple ranking, and property selection. These functions are mostly initiated based on the interpretation of RDF data as knowledge units together with statistical analysis in order to deliver an easily-readable graph to users. A prototype is implemented to demonstrate the suitability and feasibility of the approach. It shows that the simple and flexible graph visualization is easy to read, and it creates the impression of users. In addition, the attractive tool helps to inspire users to realize the advantageous role of linked data in knowledge management.
Geographica: A Benchmark for Geospatial RDF StoresKostis Kyzirakos
Geospatial extensions of SPARQL like GeoSPARQL and stSPARQL have recently been defined and corresponding geospatial RDF stores have been implemented. However, there is no widely used benchmark for evaluating geospatial RDF stores which takes into account recent advances to the state of the art in this area. In this paper, we develop a benchmark, called Geographica, which uses both real-world and synthetic data to test the offered functionality and the performance of some prominent geospatial RDF stores.
Discovering Alignments in Ontologies of Linked DataCraig Knoblock
Rahul Parundekar and Craig A. Knoblock and Jose Luis Ambite, Discovering Alignments in Ontologies of Linked Data, Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013
Revisiting the Representation of and Need for Raw Geometries on the Linked Da...Blake Regalia
Geospatial data on the Semantic Web historically stems from using point geometries to represent the geographic locations of places. As the practice evolved in the Semantic Web community, a demand for more complex geometries and geospatial query capabilities came about as a consequence of integrating traditional GIS and geo-data into the Linked Data cloud. However, recent projects have revealed that, in practice, these established techniques have major shortcomings that limit their storage, transmission, and query potential. In this position paper, we examine these shortcomings, propose to treat geometries similar to how other binary data are stored and referenced on the Semantic Web, namely by representing them as resources via URIs instead of RDF literals, and demonstrate the utility of precomputing topological relations rather than computing them on-demand by arguing that end users are most often interested in topology and not raw geometries.
Presentation of the spatiotemporal RDF store Strabon at the Linked Data Europe Workshop, co-located with the European Data Forum in Athens, Greece (21 March 2014)
While much of the recent literature in spatial statistics has evolved around addressing the big data issue, practical implementations of these methods on high performance computing systems for truly large data are still rare. We discuss our explorations in this area at the National Center for Atmospheric Research for a range of applications, which can benefit from large scale computing infrastructure. These applications include extreme value analysis, approximate spatial methods, spatial localization methods and statistically-based data compression and are implemented in different programming languages. We will focus on timing results and practical considerations, such as speed vs. memory trade-offs, limits of scaling and ease of use.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
1. Querying Incomplete Geospatial
Information in RDF
Charalampos Nikolaou and Manolis Koubarakis
Department of Informatics and Telecommunications
National and Kapodistrian University of Athens
International Symposium on Spatial and Temporal Databases (SSTD) 2013
August 23, 2013
2. Motivation
• Increased interest in publishing geospatial datasets
as linked data (i.e., encoded in RDF and with
semantic links to other datasets)
• Geospatial information might be:
o Quantitative (e.g., exact geometric information)
o Qualitative (e.g., topological relations)
... and express knowledge that is
o Complete
o Incomplete (or indefinite)
6. Linked Geospatial Data
DB
Tropes
Hellenic
FBD
Hellenic
PD
Crime
Reports
UK
NHS
(EnAKTing)
Open
Election
Data
Project
EU
Institutions
CO2
Emission
(EnAKTing)
Energy
(EnAKTing)
EEA
Mortality
(EnAKTing)
Ordnance
Survey
legislation
data.gov.uk
UK Postcodes
ESD
standards
ISTAT
Immigration
Lichfield
Spending
Scotland
Pupils &
Exams
Traffic
Scotland
Data
Gov.ie
reference
data.gov.
uk
TWC LOGD
transport
data.gov.
uk
Eurostat
Eurostat
(FUB)
(RKB
Explorer)
Linked
EDGAR
(Ontology
Central)
EURES
(Ontology
Central)
GovTrack
Finnish
Municipalities
New
York
Times
World
Factbook
Geo
Species
Italian
public
schools
Project
Gutenberg
UMBEL
riese
dbpedia
lite
dataopenac-uk
TCM
Gene
DIT
Daily
Med
YAGO
Open
Cyc
data
dcs
Diseasome
Enipedia
Lexvo
DBLP
(L3S)
Twarql
LinkedCT
EUNIS
Cornetto
SMC
Journals
Ocean
Drilling
Codices
Turismo
de
Zaragoza
Janus
AMP
Linked
GeoData
WordNet
(W3C)
Alpine
Ski
Austria
AEMET
Metoffice
Weather
Forecasts
PDB
Weather
Stations
Yahoo!
Geo
Planet
National
Radioactivity
JP
ChEMBL
Open
Data
Thesaurus
Sears
GESIS
Pisa
RESEX
Scholarometer
ACM
NVD
IBM
DEPLOY
Newcastle
RAE2001
LOCAH
Roma
CiteSeer
Courseware
dotAC
ePrints
IEEE
RISKS
PROSITE
Affymetrix
SISVU
GEMET
Airports
STW
Budapest
IRIT
VIVO
Indiana
(Bio2RDF)
PubMed
ProDom
VIVO
Cornell
STITCH
LAAS
NSF
KISTI
Linked
Open
Colors
SGD
Gene
Ontology
AGROV
OC
Product
DB
DBLP
(RKB
Explorer)
Swedish
Open
Cultural
Heritage
JISC
WordNet
(RKB
Explorer)
EARTh
lobid
Organisations
ECS
(RKB
Explorer)
HGNC
LODE
Climbing
NSZL
Catalog
Wiki
ECS
Southampton
ECS
Southampton
EPrints
Eurécom
UniProt
Taxono
my
lobid
Resources
Pfam
UniProt
WordNet
(VUA)
Ulm
P20
UN/
LOCODE
SIDER
Drug
Bank
Europeana
OAI
DBLP
(FU
Berlin)
ERA
lingvoj
VIAF
Deutsche
Biographie
~ 62 billion
triples
BibBase
Uberblic
Norwegian
MeSH
UB
Mannheim
Calames
BNB
Freebase
Rådata
nå!
GND
ndlna
data
bnf.fr
OS
DBpedia
GeoWord
Net
El
Viajero
Tourism
IdRef
Sudoc
iServe
Geo
Names
LCSH
Sudoc
RDF
Book
Mashup
LIBRIS
PSH
DDC
Open
Calais
Greek
DBpedia
ntnusc
MARC
Codes
List
totl.net
US Census
(rdfabout)
Piedmont
Accomodations
URI
Burner
LEM
Thesaurus W
SW
Dog
Food
Portuguese
DBpedia
t4gm
info
RAMEAU
SH
LinkedL
CCN
theses.
fr
my
Experiment
flickr
wrappr
NDL
subjects
Open
Library
(Talis)
Plymouth
Reading
Lists
Revyu
Fishes
of Texas
(rdfabout)
Scotland
Geography
Linked
MDB
Event
Media
US SEC
Semantic
XBRL
FTS
Chronicling
America
Telegraphis
Linked
Sensor Data
(Kno.e.sis)
Eurostat
Goodwin
Family
NTU
Resource
Lists
Open
Library
SSW
Thesaur
us
semantic
web.org
BBC
Music
Geo
Linked
Data
Source Code
Ecosystem
Linked Data
Didactal
ia
Pokedex
St.
Andrews
Resource
Lists
Manchester
Reading
Lists
gnoss
Poképédia
Classical
(DB
Tune)
BBC
Wildlife
Finder
NASA
(Data
Incubator)
Ontos
News
Portal
Sussex
Reading
Lists
Bricklink
yovisto
Semantic
Tweet
Linked
Crunchbase
Jamendo
(DBtune)
Music
Brainz
(DBTune)
Last.FM
(rdfize)
Taxon
Concept
LOIUS
CORDIS
CORDIS
(FUB)
(Data
Incubator)
BBC
Program
mes
Rechtspraak.
nl
Openly
Local
data.gov.uk
intervals
London
Gazette
Discogs
(DBTune)
OpenEI
statistics
data.gov.
uk
GovWILD
Brazilian
Politicians
educatio
n.data.g
ov.uk
Music
Brainz
(zitgist)
RDF
ohloh
FanHubz
patents
data.go
v.uk
research
data.gov.
uk
Klappstuhlclub
Lotico
(Data
Incubator)
Last.FM
artists
Population (EnAKTing)
reegle
Ren.
Energy
Generators
(DBTune)
Surge
Radio
tags2con
delicious
Slideshare
2RDF
(DBTune)
Music
Brainz
John
Peel
EUTC
Productions
business
data.gov.
uk
Crime
(EnAKTing)
Ox
Points
GTAA
Magnatune
Linked
User
Feedback
LOV
Audio
Scrobbler
Moseley
Folk
OMIM
MGI
InterPro
Smart
Link
Product
Types
Ontology
Open
Corporates
Italian
Museums
Amsterdam
Museum
UniParc
UniRef
UniSTS
Linked
Open
Numbers
Reactome
OGOLOD
Pub
Chem
GeneID
KEGG
Pathway
Medi
Care
Google
Art
wrapper
meducator
KEGG
Drug
UniPath
way
Chem2
Bio2RDF
Homolo
Gene
VIVO UF
ECCOTCP
bible
ontology
KEGG
Enzyme
PBAC
KEGG
Reaction
KEGG
Compound
KEGG
Glycan
Media
Geographic
Publications
User-generated content
Government
Cross-domain
Life sciences
As of September 2011
7. Question
How do we manage (represent, store,
query) this data efficiently?
8. Challenges: Theory
① RDF extensions for representing and querying incomplete
qualitative and quantitative geospatial information
•
GeoSPARQL
•
We proposed RDFi
•
No published algorithm for query processing when considering
RCC-8 and constants
o Standard OGC query language for RDF data with geospatial information
o Topological relations can be expressed/queried, but no reasoning is
offered.
o Can work with any topological/temporal constraint language
with/without constant symbols (e.g., RCC-5, RCC-8, IA)
o Formal semantics and algorithm for computing certain answers
o Preliminary complexity results for various constraint languages
10. i
RDF
by example (cont’d)
Query: Find fires inside the
region of West Greece.
West
Greece
GeoSPARQL query:
Olympia
CERTAIN SELECT ?f
WHERE {
?f rdf:type noa:Fire.
gag:WestGreece geo:sfContains ?f.
}
11. i
RDF
by example (cont’d)
Query: Find fires inside the
region of West Greece.
contains
contains
West
Greece
Olympia
GeoSPARQL query:
CERTAIN SELECT ?f
WHERE {
?f rdf:type noa:Fire.
gag:WestGreece geo:sfContains ?f.
}
12. Challenges: Theory
② Efficient computation of the entailment relation
Φ⊨Θ
• where Φ and Θ are quantifier-free first-order
formulas of a constraint language expressing the
topological relations of various frameworks (RCC-8,
DE-9IM, etc.)
13. Challenges: Theory
③ Computing entailment is equivalent to checking
consistency of formulas with constraint networks
• Constraint networks:
o Spatial relations among regions
o Regions might be constant ones (exact geometric
information) or identified by a URI
• Most recent results considered basic and complete
RCC-5 networks with polygonal regions
• For RCC-8, deciding consistency is NP-complete
• No published algorithm for checking consistency
• Are there tractable cases?
14. Challenges: Practice
④ Scale to billions of triples
• Reasoners from QSR scale only up to hundreds of regions
with complex spatial relations
How do they perform in our case?
• Setting:
o
o
o
o
Real linked geospatial datasets
No constants
Only base RCC-8 relations
Evaluation of consistency checking using the well-known
path-consistency algorithm
15. Experimental evaluation
after one day
•
Computation of
the complete
constraint
network
•
Running time:
O(n3)
•
Memory
requirements:
O(n2)
n ≈ thousands to
millions
hundreds of
regions
thousands of
regions
thousands of
regions
thousands of
regions
Setup: Intel Xeon E5620, 2.4 GHz, 12MB L3, 48GB RAM, RAID 5, Ubuntu 12.04
16. Network structure
• We have started working on algorithms taking into
account the structure of these networks:
o Node degrees fit a power-law distribution
o Network is sparse
17. Network structure (cont’d)
• Edges of three kinds:
non-tangential proper part
externally connected
equals
• Reflect networks composed of components with
hierarchical structure
o R-tree extensions (Papadias, Kalnis, Mamoulis, AAAI’99)
• Parallel algorithms combined with backward-chaining
techniques for lazy query processing
o Graph partitioning
o Path compression data structures and indexes
18. Related work: Spatial
• Qualitative spatial reasoning
- Efficient algorithms for consistency checking of constraint
networks (complex spatial relations, few number of regions)
- Does not consider query processing
• Description logic reasoners
- PelletSpatial: RCC-8 reasoning (cannot handle disjunctions)
- RacerPro: RCC-8 reasoning
19. Related work: Temporal
• Chaudhuri (VLDB’88)
• The knowledge representation language Telos (TOIS’90)
• Foundations of temporal constraint databases (Koubarakis,
PhD thesis, ‘94)
• Qualitative temporal reasoning community (since 80s)
• SQL+i system (BNCOD‘96)
• Later system (IEEE’97)
• Hurtado and Vaisman (2006)
20. Conclusions
• What’s the CHALLENGE?
Implementing an efficient query processing system
for incomplete geospatial information in RDFi
• The desired system should:
o reason about qualitative and quantitative spatial
information that might be incomplete
o be scalable to billions of triples in the most useful cases
Ordnance Survey is Great Britain's national mapping authority. It offers digital and paper map products for a wide range of business and outdoor uses.
GADM is a spatial database of the location of the world's administrative areas for use in GIS and similar software.
NUTS is a hierarchical system defined by the Eurostat office of the European Union for dividing the economic territory of EU in 4 levels.
Chaudhuri (VLDB’88)Framework for temporal relationships in a database employing a graph model (limited to definite information) The knowledge representation language Telos (1991)Preliminary Prolog implementation by M. Koubarakis and T. Topaloglou. The most efficient implementation of Telos (ConceptBase) does not consider incomplete information.Foundations of temporal constraint databases (Koubarakis, PhD thesis 1994)Database models for (indefinite) temporal constraint databasesSQL+i (1996)Temporal RDBMS for modeling and querying indeterminate temporal factsRepresentation and reasoning employing constraint networksLater system (1997)Querying of temporal knowledge basesLimited query language (no disjunctive expressions)