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Peter Fox
Data Science - CSCI-6961-01
Week 13, November 30, 2010
Webs of Data and Data on the Web, the Deep Web, Data
Discovery, Data Integration
Contents• Review of reading assignment
• Webs of data and semantic web
• Data on the web, linked data
• Deep web
• Data discovery
• Data integration
• Summary
• Next week
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Reading• Introduction to Data Management
• Changing software, hardware a nightmare for tracking scientific data
• Overview of Scientific Workflow Systems, Gil (AAAI08 Tutorial)
• Comparison of workflow software products, Krasimira Stoilova ,Todor Stoilov
• Scientific Workflow Systems for 21st Century, New Bottle or New Wine? Yong Zhao, Ioan Raicu, Ian Foster 3
Webs of data• Early Web - Web of pages
• http://www.ted.com/index.php/talks/tim_berners_lee_on_the_next_web.html
• Semantic web started as a way to facilitate “machine accessible content”– Initially was available only to those with familiarity
with the languages and tools, e.g. your parents could not use it
• Webs of data grew out of this– One specific example is W3C’s Linked Open
Data 4
Semantic Web• http://www.w3.org/2001/sw/
• “The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. It is a collaborative effort led by W3C with participation from a large number of researchers and industrial partners. It is based on the Resource Description Framework (RDF). See also the separate FAQ for further information.”
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Terminology• Semantic Web
– An extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation, www.semanticweb.org
– Primer: http://www.ics.forth.gr/isl/swprimer/ • Semantic Grid
– Semantic services to use the resources of many computers connected by a network to solve large scale computational/ data problems
• Provenance– origin or source from which something comes, intention for use, who/what
generated for, manner of manufacture, history of subsequent owners, sense of place and time of manufacture, production or discovery, documented in detail sufficient to allow reproducibility.
• Ontology (n.d.). The Free On-line Dictionary of Computing. http://dictionary.reference.com/browse/ontology– An explicitformal specification of how to represent the objects, conceptsand
other entities that are assumed to exist in some area ofinterest and the relationships that hold among them.
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Semantic Web Layers
http://www.w3.org/2003/Talks/1023-iswc-tbl/slide26-0.html, http://flickr.com/photos/pshab/291147522/
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Application Areas for SW• Smart search• Annotation (even simple forms), smart tagging• Geospatial• Implementing logic (rules), e.g. in workflows• Data integration• Verification …. and the list goes on• Web services• Web content mining with natural language parsing• User interface development (portals)• Semantic desktop• Wikis - OntoWiki, SemanticMediaWiki• Sensor Web• Software engineering• Explanation
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Semantic Web Basics• The triple: {subject-predicate-object}
Interferometer is-a optical instrumentOptical instrument has focal length
• W3C is the primary (but not sole) governing org.– RDF– OWL 1.0 and 2.0 - Ontology Web Language
• RDF – programming environment for 14+ languages, including C, C++,
Python, Java, Javascript, Ruby, PHP,...(no Cobol or Ada yet ;-( )
• OWL programming for Java
• Closed World - where complete knowledge is known (encoded), AI relied on this
• Open World - where knowledge is incomplete/ evolving, SW promotes this
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Ontology Spectrum
Catalog/ID
SelectedLogical
Constraints(disjointness,
inverse, …)
Terms/glossary
Thesauri“narrower
term”relation
Formalis-a
Frames(properties)
Informalis-a
Formalinstance
Value Restrs.
GeneralLogical
constraints
Originally from AAAI 1999- Ontologies Panel by Gruninger, Lehmann, McGuinness, Uschold, Welty; – updated by McGuinness.Description in: www.ksl.stanford.edu/people/dlm/papers/ontologies-come-of-age-abstract.html
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SW != ontologies on the web (!)• Ontologies are important, but use them only when necessary as
identified by use cases• The Semantic Web is about integrating data on the Web; ontologies
(and/or rules) are tools to achieve that when necessary• SW ontologies != some big (central) ontology
– The ethos of the Semantic Web is on sharing, ie, sharing possibly many small ontologies
– A huge, central ontology could be difficult to manage in terms of maintenance.
– Semantic web languages such as OWL contain primitives for equivalence and disjointness of terms and meta primitives for versioning info
• The practice: – SW applications using ontologies mix large number of ontologies and
vocabularies (FOAF, DC, and others) – the real advantage comes from this mix: that is also how new relationships
may be discovered• One readable background article from the metadata world is available at:
http://www.metamodel.com/article.php?story=20030115211223271
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Semantic Web Myths• ‘the Semantic Web is a reincarnation of Artificial Intelligence
on the Web’ (closed world versus open world)• ‘it relies on giant, centrally controlled ontologies for
"meaning" (as opposed to a democratic, bottom-up control of terms)’
• ‘one has to add metadata to all Web pages, convert all relational databases, and XML data to use the Semantic Web’
• ‘one has to learn formal logic, knowledge representation techniques, description logic, etc, to use it’
• ‘it is, essentially, an academic project, of no interest for industry’
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Integrating Multiple Data Sources
• The Semantic Web lets us merge statements from different sources
• The RDF Graph Model allows programs to use data uniformly regardless of the source
• Figuring out where to find such data is a motivator for Semantic Web Services
#Ionosphere #magnetic
“100”“TerrestrialIonosphere”
name
hasCoordinates
hasLowerBoundaryValue
Different line & text colors represent different data sources
hasLowerBoundaryUnit
“km”
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Drill Down /Focused Perusal• The Semantic Web uses Uniform
Resource Identifiers (URIs) to name things
• These can typically be resolved to get more information about the resource
• This essentially creates a web of data analogous to the web of text created by the World Wide Web
• Ontologies are represented using the same structure as content– We can resolve class and
property URIs to learn about the ontology
InternetInternet
…#NeutralTemperature
...#ISR
…#Norway
…#EISCAT
measuredby
type
locatedIn
...#FPI
...#MilllstoneHill
operatedby
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Statements about Statements• The Semantic Web allows us to
make statements about statements– Timestamps
– Provenance / Lineage
– Authoritativeness / Probability / Uncertainty
– Security classification
– …
• This is an unsung virtue of the Semantic Web
#Aurora
Red
#Danny’s
20031031
hascolor
hasSource
hasDateTime
Ontologies Workshop, APL May 26, 2006
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‘Collecting’ the ‘data’
• Part of the (meta)data information is present in tools ... but thrown away at output e.g., a business chart can be generated by a tool: it ‘knows’ the structure, the classification, etc. of the chart, but, usually, this information is lost storing it in web data would be easy!
• SW-aware tools are around (even if you do not know it...), though more would be good: – Photoshop CS stores metadata in RDF in, say, jpg files
(using XMP)– RSS 1.0 feeds are generated by (almost) all blogging
systems (a huge amount of RDF data!)
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‘Collecting’ the ‘data’• Scraping - different tools, services, etc, come
around every day: – get RDF data associated with images, for
example: service to get RDF from flickr images– service to get RDF from XMP– XSLT scripts to retrieve microformat data from
XHTML files– RSS scraping in use in VO projects in Japan– scripts to convert spreadsheets to RDF
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‘Collecting’ the ‘data’• SQL - A huge amount of data in Relational
Databases– Although tools exist, it is not feasible to convert that data
into RDF – Instead: SQL ⇋ RDF ‘bridges’ are being developed: a
query to RDF data is transformed into SQL on-the-fly– Reading for this week, article by Berners Lee and Sahoo
et al.– RDB2RDF W3 working group -
http://www.w3.org/2001/sw/rdb2rdf/– D2RQ/ D2RServer
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More Collecting• RDFa (formerly known as RDF/A) extends XHTML
by: – extending the link and meta to include child elements– add metadata to any elements (a bit like the class in
microformats, but via dedicated properties)
• It is very similar to microformats, but with more rigor: – it is a general framework (instead of an ‘agreement’ on
the meaning of, say, a class attribute value)– terminologies can be mixed more easily
• GRDDL - Gleaning Resource Descriptions from Dialects of Languages
• ATOM (follow on to RSS)
Linked open data• http://linkeddata.org/guides-and-tutorials
• http://tomheath.com/slides/2009-02-austin-linkeddata-tutorial.pdf (we will look at some of these slides now, #1-25 and 30-37)
• And of course:– http://logd.tw.rpi.edu/ – http://data-gov.tw.rpi.edu/wiki
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(Class 2) Management• Creation of logical collections
• Physical data handling
• Interoperability support
• Security support
• Data ownership
• Metadata collection, management and access.
• Persistence
• Knowledge and information discovery
• Data dissemination and publication 22
Data Management and WOD• Is this the grand solution?
• How is the data managed?
• Found?
• Curated?
• What about the metadata?
• What problems are introduced?
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Data on the Web, Internet• Data behind web services
• Data files on web sites
• We have covered data as service approaches
• Thinking you have found data when you have really only found information and metadata
• The real difference between this topic and the next one is:– Access and dissemination– Level of curation (and often description)
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Data on the internet• http://www.dataspaceweb.org/
• Data files on other protocols– FTP– RFTP– GridFTP– SABUL– XMPP/AMQP– Others…
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Deep web• Data behind web services
• Data behind query interfaces (databases or files)
• Introduces a different curation problem
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The loose definition• Something that a crawler cannot find and/or
index– Creates the other definition of shallow web
• Has many implications for discovery, access and use
• Curation is more complex to satisfy this definition, i.e. not a matter of just putting files ‘on the web’
• 50, 100, 1000 times the ‘shallow web’?
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Managing (in) the deep web• Sometimes, the deep web aspect of a data
source can be due to extreme obscurity, language peculiarities, NO metadata, NO documentation
• There are no known studies of how effective data management (what you are learning) could change the percentage of deep/ shallow
• Semantics are often put forward as a solution http://www.mkbergman.com/458/new-currents-in-the-deep-web/ 28
Internet impacts on management
• Management of data that is..
• Web – ‘stateless’
• Curation, Preservation – highly stateful (by definition)
• You will hear terms such as digital curation and digital preservation (search on these) but what about internet curation and internet preservation (Internet Archive?)
• What others??29
(Class 2) Management• Creation of logical collections
• Physical data handling
• Interoperability support
• Security support
• Data ownership
• Metadata collection, management and access.
• Persistence
• Knowledge and information discovery
• Data dissemination and publication 30
Thus data frameworks are appearing
• Many – meaning they go beyond web sites, they incorporate many of the data management functions
• Initially syntactic – e.g. OPeNDAP, ADDE,
• Application oriented – e.g. virtual observatories
• Semantic – e.g. Virtual Solar-Terrestrial Observatory
• ALL of these are changing the nature of data management and role of data ‘providers’ cf. ? 31
BOM, Melbourne, VIC 20071015 (Fox)
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Some DefinitionsDAP = Data Access Protocol
Model used to describe the data; Request syntax and semantics; and Response syntax and semantics.
OPeNDAP The software; Numerous reference implementations; Core/libraries and services (servers and clients).
OPeNDAP Inc. OPeNDAP is a 501.c(3) non-profit corporation; Formed to maintain, evolve and promote the
discipline neutral DAP that was the DODS core infrastructure.
BOM, Melbourne, VIC 20071015 (Fox)
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Considerations with regard to the development of DAP and OPeNDAP
Many data providers
Many data formats
Many different semantic representations of the data
Many different security requirements
Many different client types
BOM, Melbourne, VIC 20071015 (Fox)
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Broad Vision
A world in which a single data access protocol is used for the exchange of data between network based applications regardless of discipline.
A layer above TCP/IP providing for syntactic and semantic consistency not available in existing protocols such as FTP.
BOM, Melbourne, VIC 20071015 (Fox)
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Practical Practical Considerations
The broad vision:
Is syntactically achievable, but
Is not semantically achievable, at least not in the near term.
BOM, Melbourne, VIC 20071015 (Fox)
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OPeNDAP Inc. Mission Statement
To maintain, evolve and promote a data access protocol (DAP) and reference implementation software (OPeNDAP) for the syntactically consistent exchange of data over the network.
The DAP should provide syntactic interoperability across disciplines and allow for semantic interoperability within disciplines.
BOM, Melbourne, VIC 20071015 (Fox)
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The DAP has been designed to be as general as possible without being constrained to a particular discipline or world view.
The Data Access Protocol (DAP)
The DAP is a discipline neutral data access protocol; it is being used in astronomy, medicine, earth science,…
Provides data format and location, and data organization transparency
Is metadata neutral
BOM, Melbourne, VIC 20071015 (Fox)
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DAP comparisons• File-based
– GridFTP/FTP– HTTP– SRB
• Service-based– Open-Geospatial Consortium, WCS, WMS, WFS, …– Virtual Observatory (Astronomy), SIAP, SSAP, STAP,…
BOM, Melbourne, VIC 20071015 (Fox)
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Who is using DAP/ OPeNDAP?
• Science examples– PMEL with their Tsunami inundation modeling– Ocean regional modelers to extract open
boundary conditions– Visualization of data sets using MATLAB/IDL/…
• Service examples– Live Access Server– Mapserver – OGC services and OPeNDAP data
access (future)– Digital Library Service - metadata and catalogue
info
BOM, Melbourne, VIC 20071015 (Fox)
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Data Access Protocol (DAP2) - Current
DAP2 currently a NASA/ESE ‘Standard’
Current servers implement DAP2
DAP 2 + XML responses (implemented)
DAP3
BOM, Melbourne, VIC 20071015 (Fox)
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DAP4 DAP4 improvements over DAP3:
Additional datatypesSwathBlob - GIF, MPEG,…
Additional functionality Check sumModulo
The additional datatypes will enable the DAP to be used in a wider variety of circumstances and are a direct response to users’ requests.
BOM, Melbourne, VIC 20071015 (Fox)
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What DAP means to me
• Data access and transport• Response types: DAP objects versus file type
– A DAP URL is essentially an HTTP URL with additional restrictions placed on the abs-path component.
– DAP2-URL = "http://" host [ ":" port ] [ abs-path]• abs-path = server-path data-source-id [ "." ext[ "?" query ] ] • server-path = [ "/" token ] • data-source-id = [ "/" token ] • ext = "das" | "dds" | "dods"
– The server-path is the pathname to the server, whereas data-source-id is the pathname to the data.
BOM, Melbourne, VIC 20071015 (Fox)
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OPeNDAP V3 Architecture
Cgi style access
CGI-style access Uses web server HTTP protocol Several request and response types Reads data files, Databases, et c., returns info May return DAP2 objects or other data Client can be application, web browser or
specialized server/service
DataClient
BOM, Melbourne, VIC 20071015 (Fox)
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OPeNDAP V4 (Hyrax) Architecture
OLFS BES
OPeNDAP Lightweight Front end Server (OLFS) Receives requests and asks the BES to fill them Uses Java Servlets Does not directly ‘touch’ data Multi-protocol
Data
Back End Server (BES) Reads data files, Databases, et c., returns info May return DAP2 objects or other data Does not require web server
Client
BOM, Melbourne, VIC 20071015 (Fox)
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Binaries Generated
There are approximately 80 binaries built on a nightly basis. They are built for the following platforms/operating systems:
Linux FC4 FC5
MacOS-X (universal binaries when possible)
Windows XP, win32
Java 1.5 (Tomcat 5.5)
IRIX (in four variants), Solaris, AIX, OSF
BOM, Melbourne, VIC 20071015 (Fox)
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Clients Browser Interfaces Data System Integrators (ODC) Servers Processing Servers Aggregating Servers - OPeNDAP chains Ancillary Information Services
The OPeNDAP data access protocol is used by a variety of system elements.
OPeNDAP System Elements
BOM, Melbourne, VIC 20071015 (Fox)
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Clients
Clients make requests and receive responses via the DAP.
Clients convert data from the OPeNDAP data model to the form required in the client application.
BOM, Melbourne, VIC 20071015 (Fox)
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netCDF C
Ferret GrADS
netCDF Java
IDV VisAD ncBrowse
Matlab
MatlabClient
Access ExcelIDL
IDLClient
ArcGIS
pyDAP
OPeNDAP Clients
ArcGIS
pyDAP
NCL
NCLClient
Internet
WebBrowser OPeNDAP
DataConnector
BOM, Melbourne, VIC 20071015 (Fox)
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OCAPI -> OC in 2009 A pure OPeNDAP C API (OCAPI) for the
client-side
Applications:DAP-aware ‘commands’ for commercial analysis
programs (e.g., IDL)Scripting tools (e.g., Perl)
BOM, Melbourne, VIC 20071015 (Fox)
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Clients Browser Interfaces Data System Integrators (ODC) Servers Processing Servers Aggregating Servers - OPeNDAP chains Ancillary Information Services
The OPeNDAP data access protocol is used by a variety of system elements.
OPeNDAP System Elements
BOM, Melbourne, VIC 20071015 (Fox)
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Clients Browser Interfaces Data System Integrators (ODC) Servers Processing Servers Aggregating Servers - OPeNDAP chains Ancillary Information Services
The OPeNDAP data access protocol is used by a variety of system elements.
OPeNDAP System Elements
BOM, Melbourne, VIC 20071015 (Fox)
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Servers
Servers receive requests and provide responses via the DAP.
Servers convert the data from the form in which they are stored to the DAP.
Servers provide for subsetting of the data and more.
BOM, Melbourne, VIC 20071015 (Fox)
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Data Data Data Data Data Data Data
HDF5
HDF4 JDBC
FreeFormFITS
CDF CEDAR
Data
netCDF
netCDF HDF4 HDF5
Data
DSP
DSP
Data
JGOFS
Tables SQL FITS CDFFlat
Binary CEDAR
Data
General
ESML
OPeNDAP Servers
CDM
Internet
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Data
GRIBBUFR
OPeNDAP
GDS
Data
CODAR
CODAR
Data
FDS
netCDFOPeNDAP
Data
General
pyDAP
Data
DAPPER
netCDFOPeNDAP
Data
netCDFOPeNDAP
TDS
Data
General
pyDAP
Data
netCDFOPeNDAP
TDS
OPeNDAP Servers (specialized processing)
Data
ESG
netCDFOPeNDAP
Internet
BOM, Melbourne, VIC 20071015 (Fox)
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Servers
Servers may also provide other services
Directory traversal.
Browser-based form to build URL.
Ascii or other representations of data.
Metadata associated with the data.
Server side functions.
BOM, Melbourne, VIC 20071015 (Fox)
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Data
General
pyDAP
OPeNDAP Aggregation Servers
Data
GRIBBUFR
OPeNDAP
GDS
Data
CODAR
CODAR
Data
FDS
netCDFOPeNDAP
Data
DAPPER
netCDFOPeNDAP
Data
TDS
netCDFOPeNDAP
Data
General
JGOFS
Data
ESG
netCDFOPeNDAP
Internet
BOM, Melbourne, VIC 20071015 (Fox)
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The Aggregation Server: An Example
AggregationAggregationServerServer
File
DSP Data Set
FileFileFile
netCDF Data Set
File File
Matlab
Local
OPeNDAP
HTML, GIFMatlabClient
DSP
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OPeNDAP’s Hyrax (‘Server4’)
• Uses a modular architecture to support different application-level protocols– Data access using DAP2 (DAP3)– Catalogs using THREDDS– Browsing using HTML and ASCII
• Modules for data access– Different file types– Potential for database and scripting
• Modules for commands– Commands provide varying operations for different
protocols
BOM, Melbourne, VIC 20071015 (Fox)
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OPeNDAP V4 (Hyrax) Architecture
OLFS BES
OPeNDAP Lightweight Front end Server (OLFS) Receives requests and asks the BES to fill them Uses Java Servlets Does not directly ‘touch’ data Multi-protocol
Data
Back End Server (BES) Reads data files, Databases, et c., returns info May return DAP2 objects or other data Does not require web server
Client
BOM, Melbourne, VIC 20071015 (Fox)
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GridFTPDAP2
GridFTPDAP2
HTTPDAP2HTTPDAP2
ASCII outputASCII output
HTML formHTML form
Info outputInfo output
OPeNDAP Lightweight Front end ServerOPeNDAP Lightweight Front end Server
THREDDSTHREDDS
Request Formulation**Request Formulation**
Req
uest
fro
m c
lient
Res
pons
e to
clie
ntB
ESSOAP-DAP (HTTP)
DAP2 (GridFTP, HTTP)
BOM, Melbourne, VIC 20071015 (Fox)
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BES
Network Protocol andProcess start/stopactivities
Data Store Interfaces
BES Framework
PPT*Initialization/Termination
DAP2Access
NetCDF3 HDF4 FreeForm…
DataCatalogs
Commands**BES Commands/ XML Documents
*PPT is built in (other protocols)**Some commands are built inData DataData
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Ancillary Information Service• Current capability: Attributes only• Client-side only• Local and remote resources• Local resource databases
The AIS enables users to augment the metadata for a data source in a controlled way without requiring write access to the original data. By using the DAP, users are also isolated from data format issues.
BOM, Melbourne, VIC 20071015 (Fox)
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AIS Server
Client linkedw/DAP
Software
DataSource
AISServer
AISResource
1
2
0
3
0. Client requests metadata from the AIS server (which appears no different from any other DAP server).
1. The AIS server gets metadata from data source2. The AIS server gets matching the AIS resource using the AIS database and
merges it into the metadata.3. The AIS server returns resulting the metadata object.
04/19/23 Bureau of Meteorology, Melbourne Australia
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Lessons (Re)Learned Lessons (Re)Learned
1. Modularity provides for flexibility
The more modular the underlying infrastructure the more flexible the system. This is particularly important for network based systems for which the technology, software and hardware, are changing rapidly.
04/19/23 Bureau of Meteorology, Melbourne Australia
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Lessons (Re)LearnedLessons (Re)Learned
2. Data of interest will be stored in a variety of formats.
Regardless of how much one might want to define the format to be used by system participants, in the end the data will be stored in a variety of formats.
2a. The same is true of use metadata!
04/19/23 Bureau of Meteorology, Melbourne Australia
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Lessons LearnedLessons Learned
3. Structural representation of sequence data sets is a major obstacle to interoperability
Care must be given to the organizational structure (as opposed to the format) of the data.
04/19/23 Bureau of Meteorology, Melbourne Australia
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Lessons LearnedLessons Learned
7. The lack of a consistent structure for data inventories is a major obstacle to the use of distributed systems.
04/19/23 Bureau of Meteorology, Melbourne Australia
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Lesser Lessons Learned Lesser Lessons Learned
9. Some surprises/observations encountered in the OPeNDAP effort
Metadata focus in the past has been on data discovery not on data use, but metadata for use is where it’s at.
Number of variables increases almost linearly with the number of data sets.
Users will take advantage of all of the flexibility offered by a system sometimes to the disadvantage of all.
Incredible variability in the structural organization of data.
04/19/23 Bureau of Meteorology, Melbourne Australia
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Lessons LearnedLessons Learned
10. Time to maturity is order 10 years not 3
Developing new infrastructure takes time, particularly to iron out all of the %^*% little details.
Data discovery• Free text search on the internet/ web
• Data portals
• What makes discovery work?
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Three level ‘metadata’ solution
Level 1:
Data Registration at the Discovery Level,
e.g. Volcanolocation and activity
Level 2:
Data Registration at the Inventory Level,
e.g. list of datasets,times, products
Level 3:
Data Registration at the Item Detail
Level, e.g. access toindividual quantities
Ontology basedData IntegrationUsing scientific
workflows
Earth Sciences Virtual DatabaseA Data Warehouse where
Schema heterogeneity problem is Solved; schema based integration
Data Discovery Data Integration
A.K.Sinha, Virginia Tech, 2006
Data discovery• What makes discovery work?
– Metadata– Logical organization– Attention to the fact that someone would want to
discover it– It turns out that file types are a key enabler or
inhibitor to discovery
• What does not work?– Result ranking using *any* conventional
algorithms74
Smart search• Semantically aware search, e.g.
http://noesis.itsc.uah.edu
• Faceted search, e.g. mspace (http://mspace.fm ), Earth System Grid (http://esg.prototype.ucar.edu )
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Faceted search• Semantically aware search, e.g.
http://noesis.itsc.uah.edu
• Faceted search, e.g. mspace (http://mspace.fm ), Earth System Grid (http://esg.prototype.ucar.edu )
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Federated search• “is the simultaneous search of multiple online
databases or web resources and is an emerging feature of automated, web-based library and information retrieval systems. It is also often referred to as a portal or a federated search engine.” wikipedia
• Libraries have been doing this for a long time (Z39.50, ISO23950)
• Key is consistent search metadata fields (keywords)• E.g. Geospatial One Stop http://www.geodata.gov
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Data integration• “involves combining data residing in different sources and
providing users with a unified view of these data. This process becomes significant in a variety of situations both commercial (when two similar companies need to merge their databases) and scientific (combining research results from different bioinformatics repositories, for example). “
• “Data integration appears with increasing frequency as the volume and the need to share existing data explodes. It has become the focus of extensive theoretical work, and numerous open problems remain unsolved. In management circles, people frequently refer to data integration as "Enterprise Information Integration" (EII)” wikipedia
• Is this a data science/ management challenge (rhetorical question) 79
Aiding data integration• Standards – formats for sure but also
• Metadata
• Semantics
• As such any integration capability is HIGHLY curated or left entirely to the end user
• If left to the user, results in a new data product which is rarely managed or shared
• What would you do?80
Summary• Theme of data management in the chaotic
and enabling environment of the web, internet
• Emergence of frameworks that encompass some aspects of data management
• Unlocking data in a preservable way is an immense challenge
• Anything/ everything you can do will help
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