A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information...
-
Upload
maryann-martone -
Category
Technology
-
view
561 -
download
3
description
Transcript of A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information...
![Page 1: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/1.jpg)
A Deep Survey of the Digital Resource Landscape:
Perspectives from the Neuroscience Information Framework
Maryann E. Martone, Ph. D.University of California, San Diego
![Page 2: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/2.jpg)
• NIF is an initiative of the NIH Blueprint consortium of institutes– What types of resources (data, tools, materials, services) are available to the
neuroscience community?– How many are there?– What domains do they cover? What domains do they not cover?– Where are they?
• Web sites• Databases• Literature• Supplementary material
– Who uses them?– Who creates them?– How can we find them?– How can we make them better in the future?
http://neuinfo.org
• PDF files
• Desk drawers
![Page 3: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/3.jpg)
The Neuroscience Information Framework
• NIF has developed a production technology platform for researchers to:– Discover– Share– Analyze– Integrate neuroscience-relevant
information• Since 2008, NIF has assembled
the largest searchable catalog of neuroscience data and resources on the web
• Cost-effective and innovative strategy for managing data assets
“This unique data depository serves as a model for other Web sites to provide research data. “ - Choice Reviews Online
NIF is poised to capitalize on the new tools and emphasis on big data and open science
![Page 4: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/4.jpg)
http://neuinfo.orgJune10, 2013 dkCOIN Investigator's Retreat 4
The Neuroscience Information Framework: Discovery and utilization of web-based resources for neuroscience
• A portal for finding and using neuroscience resources
A consistent framework for describing resources
Provides simultaneous search of multiple types of information, organized by category
Supported by an expansive ontology for neuroscience
Utilizes advanced technologies to search the “hidden web”
UCSD, Yale, Cal Tech, George Mason, Washington Univ
Literature
Database Federation
Registry
![Page 5: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/5.jpg)
Part 1: Surveying the resource landscape
•NIF Registry: A catalog of neuroscience-relevant resources• > 6000 currently
listed• > 2200 databases
•And we are finding more every day
![Page 6: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/6.jpg)
dkCOIN Investigator's Retreat
How do resources get added to the NIF Registry?
June10, 2013 6
•NIF curators•Nomination by the community•Semi-automated text mining pipelines
NIF RegistryRequires no special skillsSite map available for
local hosting
•NIF Data Federation• DISCO interop• Requires some
programming skill
Bandrowski et al., 2012
![Page 7: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/7.jpg)
NIF Registry
• Extended over time– Parent resource– Supporting agency– Grant numbers– Accessibility– Related to– Organism– Disease or condition– Last updated
First catalog: SFN Neuroscience Database Gateway NIF 0.5 NIF 1.0+
Simple metadata model
Name, description, type, URL, other names, keywords, unique identifier
~2003 2006 2008
![Page 8: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/8.jpg)
dkCOIN Investigator's Retreat 8
Resource Curation
June10, 2013
• NIF Registry is hosted on Semantic Media Wiki platform Neurolex– Community can add,
review, edit without special privileges
– Searchable by Google– Integrated with NIF
ontologies– Graph structure
http://neurolex.org
![Page 9: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/9.jpg)
The resource graph
NIF is creating the linked data graph of resources
![Page 10: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/10.jpg)
Keeping the Registry Current
– NIF employs an automated link checker – Last analysis: 478/6100 invalid URL’s (~8%)– 199 can’t locate at another university or location out of service (~3%)– Bigger issue: Many resources are no longer updated or maintained
1996 1998 2000 2002 2004 2006 2008 2010 2012 20140
20
40
60
80
100
120
140
160
180
200
0
500
1000
1500
2000
2500
3000
3500
Resources addedLast
upd
ated
![Page 11: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/11.jpg)
• Automated text mining is used to look for “web page last updated” or copyright dates– Identified for 570 resources; manual review suggested that the results
were accurate although we can’t guarantee that the date itself is accurate
– 373 were not updated within the last 2 years (65%)•Manual review of ~200 resources identified by 3DVC for their
catalog– 38 not updated within the past 2 years (~20%)– 8 migrated to new addresses or institutions– 7 are no longer in service (~3%)– 3 were deemed no longer appropriate
Tracking the fate of digital resources
Yuling Li, Paul Sternberg, Cal Tech
![Page 12: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/12.jpg)
Keeping content up to date
Connectome
Tractography
Epigenetics
•New tags come into existence•New resource types come into existence, e.g., Mobile apps•Resources add new types of content • Change name• Change scope
•> 7000 updates to the registry last year
It’s a challenge to keep the registry up to date; sitemaps, curation, ontologies, community review
![Page 13: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/13.jpg)
dkCOIN Investigator's Retreat 13
Ontology provides a human-centric model for search and data integration
June10, 2013
![Page 14: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/14.jpg)
Last updated...
• Some neglected resources are still valuable– Complete data sets– Rare data
• Software may still be usable
• Some databases, however, may only be of historical interest– “all metalloproteins
found in PDB”
Are all databases and data sets equally valuable?
![Page 15: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/15.jpg)
• The NIF Registry has created a linked data graph of web-accessible resources•Maintained on a community wiki
platform• Provides data on the fluidity of the
resource landscape– New resources continue to be created and
found– Relatively few disappear altogether– Many more grow stale, although their value
may still be significant– Maintaining up to date curation requires
frequent updating
Summary
NIF Registry provides insight into the state of digital resources on the web
![Page 16: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/16.jpg)
Part 2: Surveying the data landscape
•The NIF data federation performs deep search over the content of over 200 databases•New databases are added at a rate of 25-40 per year• Latest update: Open Source Brain; ingest
completed in 2 hours•Databases chosen on a variety of criteria:• Early: testing different types of resources• Thematic areas• Volunteers
![Page 17: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/17.jpg)
dkCOIN Investigator's Retreat 17Jun-08 Dec-08 Jul-09 Jan-10 Aug-10 Feb-11 Sep-11 Apr-12 Oct-12 May-1310000
100000
1000000
10000000
100000000
1000000000
0
50
100
150
200
250
Num
ber o
f Fed
erat
ed R
ecor
ds (M
illio
ns)
Num
ber o
f Fed
erat
ed D
atab
ases
Data Federation GrowthNIF searches the largest collation of neuroscience-relevant data on the web
DISCO
June10, 2013
![Page 18: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/18.jpg)
dkCOIN Investigator's Retreat 18
Data Ingestion Architecture
CurrentPlanned
DISCO Dashboard Functions• Ingest Script Manager• Public Script Repository• Data & Event Tracker• Versioning System• Curator Tool • Data Transformer Manager
June10, 2013 Luis Marenco, Rixin Wang, Perrry Miller, Gordon ShepherdYale University
![Page 19: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/19.jpg)
dkCOIN Investigator's Retreat 19
DISCO Dashboard
June10, 2013
• Management of registry resources through a single administrative dashboard
• Associated discovery pipeline
• Tools to manage data updates
• Change tracking
• Globally unique identifier creation
Luis Marenco, Rixin Wang, Perrry Miller, Gordon ShepherdYale University
![Page 20: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/20.jpg)
NIF data federation
NIF was designed to be populated rapidly with progressive refinement
![Page 21: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/21.jpg)
What are the connections of the hippocampus?
Hippocampus OR “Cornu Ammonis” OR “Ammon’s horn” Query expansion: Synonyms
and related conceptsBoolean queries
Data sources categorized by
“data type” and level of nervous
system
Common views across multiple
sources
Tutorials for using full resource when getting there from
NIF
Link back to record in
original source
![Page 22: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/22.jpg)
Results are organized within a common framework
Connects to
Synapsed with
Synapsed by
Input regioninnervates
Axon innervatesProjects toCellular contact
Subcellular contact
Source site
Target site
Each resource implements a different, though related model; systems are complex and difficult to learn, in many cases
![Page 23: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/23.jpg)
NIF Semantic Framework: NIFSTD ontology
• NIF covers multiple structural scales and domains of relevance to neuroscience• Aggregate of community ontologies with some extensions for neuroscience, e.g., Gene
Ontology, Chebi, Protein Ontology
NIFSTD
Organism
NS FunctionMolecule InvestigationSubcellular structure
Macromolecule Gene
Molecule Descriptors
Techniques
Reagent Protocols
Cell
Resource Instrument
Dysfunction QualityAnatomical Structure
![Page 24: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/24.jpg)
dkCOIN Investigator's Retreat 24
Use of Ontologies• Controlled vocabulary for describing type of resource and
content– Database, Image, Diabetes
• Entity-mapping of database and data content• Data integration across sources• Search: Mixture of mapped content and string-based
search– Different parts of the infrastructure use the vocabularies in
different ways– Utilize synonyms, parents, children to refine search– Increasing use of other relationships and logical inferencing
• Generation of semantic content (i.e. RDF, Linked Data)
June10, 2013
![Page 25: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/25.jpg)
25
NIF Concept Mapper
June10, 2013
Aligns sources to the NIF semantic framework
![Page 26: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/26.jpg)
Column level mapping: Reducing false positives
![Page 27: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/27.jpg)
The scourge of neuroanatomical nomenclature: Importance of NIF semantic framework
•NIF Connectivity: 7 databases containing connectivity primary data or claims from literature on connectivity between brain regions• Brain Architecture Management System (rodent)• Temporal lobe.com (rodent)• Connectome Wiki (human)• Brain Maps (various)• CoCoMac (primate cortex)• UCLA Multimodal database (Human fMRI)• Avian Brain Connectivity Database (Bird)
•Total: 1800 unique brain terms (excluding Avian)
•Number of exact terms used in > 1 database: 42•Number of synonym matches: 99•Number of 1st order partonomy matches: 385
![Page 28: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/28.jpg)
dkCOIN Investigator's Retreat 28
Content Annotation – Google Refine
June10, 2013
![Page 29: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/29.jpg)
dkCOIN Investigator's Retreat 29
Resource Provider Services - Linkout
June10, 2013
![Page 30: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/30.jpg)
What have we learned: Grabbing the long tail of small data
• NIF can be used to survey the data landscape
• Analysis of NIF shows multiple databases with similar scope and content
• Many contain partially overlapping data
• Data “flows” from one resource to the next– Data is reinterpreted, reanalyzed or
added to
• Is duplication good or bad?
![Page 31: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/31.jpg)
What do you mean by data?Databases come in many shapes and sizes
• Primary data:– Data available for reanalysis, e.g.,
microarray data sets from GEO; brain images from XNAT; microscopic images (CCDB/CIL)
• Secondary data– Data features extracted through
data processing and sometimes normalization, e.g, brain structure volumes (IBVD), gene expression levels (Allen Brain Atlas); brain connectivity statements (BAMS)
• Tertiary data– Claims and assertions about the
meaning of data• E.g., gene
upregulation/downregulation, brain activation as a function of task
• Registries:– Metadata– Pointers to data sets or materials
stored elsewhere
• Data aggregators– Aggregate data of the same type
from multiple sources, e.g., Cell Image Library ,SUMSdb, Brede
• Single source– Data acquired within a single
context , e.g., Allen Brain Atlas
Researchers are producing a variety of information artifacts using a multitude of technologies
![Page 32: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/32.jpg)
NIF Analytics: The Neuroscience Landscape
NIF is in a unique position to answer questions about the neuroscience landscape
Where are the data?
StriatumHypothalamusOlfactory bulb
Cerebral cortex
Brain
Brai
n re
gion
Data source
Vadim Astakhov, Kepler Workflow Engine
![Page 33: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/33.jpg)
Whither neuroscience information?
∞
What is easily machine processable and accessible
What is potentially knowable
What is known:Literature, images, human
knowledge
Unstructured; Natural language processing, entity recognition, image
processing and analysis;
communication
![Page 34: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/34.jpg)
Open world meets closed world
We know a lot about some things and less about others; some of NIF’s sources are comprehensive; others are highly biased
But...NIF has > 900,000 antibodies, 250,000 model organisms, and 3 million microarray records
![Page 35: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/35.jpg)
Diseases of nervous system
What drives discovery?
The combination of ontologies, diverse data and analytics lets us look at the current landscape in interesting ways
Neurodegenerative
Seizure disorders
Neoplastic disease of nervous system NIH
ReporterNIF
dat
a fe
dera
ted
sour
ces
![Page 36: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/36.jpg)
Embracing duplication: Data Mash ups
•NIF queries across 3 of approximately 10 fMRI databases•Two resources, Brede and SUMSdb curated activation foci from the literature•~300 PMID’s were common between Brede and SUMSdb• PMID serves as a unique identifier for an article
•Same information; value addedData is additive
![Page 37: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/37.jpg)
Same data: different analysis
•Gemma: Gene ID + Gene Symbol•DRG: Gene name + Probe ID
•Gemma presented results relative to baseline chronic morphine; DRG with respect to saline, so direction of change is opposite in the 2 databases
Chronic vs acute morphine in striatum
• Analysis:• 1370 statements from Gemma regarding gene expression as a function of chronic
morphine• 617 were consistent with DRG; over half of the claims of the paper were not
confirmed in this analysis• Results for 1 gene were opposite in DRG and Gemma• 45 did not have enough information provided in the paper to make a judgment
Relatively simple standards would make life easier
![Page 38: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/38.jpg)
Phases of NIF• 2006-2008: A survey of what was out there• 2008-2009: Strategy for resource discovery
– NIF Registry vs NIF data federation– Ingestion of data contained within different technology platforms, e.g., XML vs relational
vs RDF– Effective search across semantically diverse sources
• NIFSTD ontologies
• 2009-2011: Strategy for data integration– Unified views across common sources– Mapping of content to NIF vocabularies
• 2011-present: Data analytics– Uniform external data references
• 2012-present: SciCrunch: unified biomedical resource services
NIF provides a strategy and set of tools applicable to all biomedical science
![Page 39: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/39.jpg)
dkCOIN Investigator's Retreat 39
Where is the Neuroscience in NIF?• Search semantics• Ranking• Resources supported by NIH Blueprint Institutes are
more thoroughly covered• Data types, e.g., Brain activation foci
June10, 2013
![Page 40: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/40.jpg)
40
Building a Uniform Resource Layer
Discoverability
Accessibility
Web of Data
Data specified via simple semanticsData in a usable formSemantically-enabled search
Enhanced semanticsStandardized representationLinked Open Data - RDF
Data resources simply describedAutomated data harvesting technologies Common resource registry
A production data (resource) catalog and underlying technology platform for researchers to discover, share, access, analyze, and integrate biomedical information
June10, 2013
![Page 41: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/41.jpg)
Community Built Uniform Resource Layer
June10, 2013 41
SciCrunch
NIF
Neuroscience
MONARCH
Animal Models
CommunityServices dkCOIN
SharedResources
Undiagnosed Disease Program
Phenotype RCN
3D Virtual Cell
National Institute on Aging
One Mind for Research
BIRN
International Neuroinformatics
Coordinating Facility
Model Organism Databases
Community Outreach
DELSA
Varied
(not just a data catalog)
![Page 42: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/42.jpg)
Each project shares resources and adds unique value to the resource layer
42
•3dVC: Focus on models and simulation•Gene Ontology: Focus on bioinformatics tools•National Institute on aging: Aging-related data sets•Monarch: Phenotype-Genotype; deep semantic data integration•One Mind for Research: Biospecimen repositories•NeuroGateway: Computational resources•FORCE11: Tools for next-gen publishing and e-scholarship
SciCrunch
SciCrunch is actively supporting multiple communities; multiple communities are enriching and improving SciCrunch
![Page 43: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/43.jpg)
dkCOIN Investigator's Retreat
Customized portals and rankings
June10, 2013 43
SciCrunch
NIF
Neuroscience
MONARCH
Animal Models
CommunityServices dkCOIN
SharedResources
Undiagnosed Disease Program
Phenotype RCN
3D Virtual Cell
National Institute on Aging
One Mind for Research
BIRN
International Neuroinformatics
Coordinating Facility
Model Organism Databases
Community Outreach
DELSA
Varied
dkCOINOntology
SciCrunchShared
Resources
![Page 44: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/44.jpg)
Community database: beginning
Community database:
End
Register your resource to NIF!
“How do I share my data/tool?”
“There is no database for my data”
1
2
3
4
Institutional repositories
Cloud
INCF: Global infrastructure
Government
Education
Industry
NIF is designed to leverage existing investments in resources and infrastructure
Tool repositories
![Page 45: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/45.jpg)
dkCOIN Investigator's Retreat 45
Collaboration, competition, coordination, cooperation
•The diversity and dynamism of biomedical data will make data integration challenging always
•The overall data space is vast: No one group or individual can do everything– Cooperation and coordination is essential
•Creating a core resource registry and data catalog allows the entire community to track resources, work together to keep it updated, promote cross-fertilization, and build better resources
June10, 2013
![Page 46: A Deep Survey of the Digital Resource Landscape:Perspectives from the Neuroscience Information Framework](https://reader038.fdocuments.us/reader038/viewer/2022110302/5478ec31b4af9ff4528b4700/html5/thumbnails/46.jpg)
NIF team (past and present)
Jeff Grethe, UCSD, Co Investigator, Interim PIAmarnath Gupta, UCSD, Co InvestigatorAnita Bandrowski, NIF Project LeaderGordon Shepherd, Yale UniversityPerry MillerLuis MarencoRixin WangDavid Van Essen, Washington UniversityErin ReidPaul Sternberg, Cal TechArun RangarajanHans Michael MullerYuling LiGiorgio Ascoli, George Mason UniversitySridevi Polavarum
Fahim ImamLarry LuiAndrea Arnaud StaggJonathan CachatJennifer LawrenceSvetlana SulimaDavis BanksVadim AstakhovXufei QianChris ConditMark EllismanStephen LarsonWillie WongTim Clark, Harvard UniversityPaolo CiccareseKaren Skinner, NIH, Program Officer (retired)Jonathan Pollock, NIH, Program Officer
And my colleagues in Monarch, dkNet, 3DVC, Force 11