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The Materials Project
Validation, Provenance and Sandboxes
Goals
• Validation
– constantly guard against bugs in core data
and imported data
• Provenance
– know how data came to be
• Sandboxes
– Combine public and non-public data; "good
fences make good neighbors"
Validation
(Internal)
Database ID
External ID What we expected
What we got
Validation runs all the time
• Rules with "constraints" for every database (and sandbox)
• Test constraints against entire DB every night  email reports
• Validation engine, etc. all open-source software in pymatgen-db
Remote
server
Validation
engine
Rules
MP Databases
Reports
(email, web pages, ..)
Rules have a simple syntax
_aliases:
- snl_id = mps_id
- energy = analysis.e_above_hull
materials:
-
filter:
constraints:
- final_energy_per_atom <= 0
- initial_structure.lattice.volume > 0
- initial_structure.lattice.a > 0
- initial_structure.lattice.b > 0
- initial_structure.lattice.c > 0
- initial_structure.lattice.matrix size 3
- formation_energy_per_atom <= 5
- formation_energy_per_atom > -5
- cpu_time > 5
- e_above_hull > -0.000001
- final_energy < 0
- reduced_cell_formula size$
nelements
# Check num. ICSD sources for
selected compounds
-
filter:
- task_id = "mp-540081"
constraints:
- icsd_id size> 10
-
filter:
- task_id = "mp-20379"
constraints:
- icsd_id size 1
-
filter:
- task_id = "mp-13634"
constraints:
- icsd_id size> 0
-
filter:
- task_id = "mp-600022"
constraints:
- icsd_id size 0
# NiO2 phases should never become
stable
-
filter:
- e_above_hull = 0
constraints:
- pretty_formula != 'NiO2'
tasks:
-
filter:
- state = "successful"
constraints:
- output.final_energy_per_atom <= 0
Validation summary
Easy-to-use, integrated, efficient tools to
report errors
Next steps
– Record all check results in DB
– More sophisticated checks (Map/Reduce)
– Make it easier to add new checks internally
– Make it easier to add new check for anyone
• per-sandbox or even per-user ("MP Alerts")
Provenance: How do I know that
the data is correct?
Types of provenance in the system
1) Calculation workflows
– FireWorks records calculation inputs, .. results in great detail
2) External datasets
– Structure Notation Language standardizes the naming of data
sources and publications
3) Post-calculation data transformations
– New "builders" provides framework for tracking creation of final
database products
(1) (2)
(3)
Provenance is available
for every material
Provenance in DB
Structure Notation Language
"snl_final": {
"about": {
"created_at": {
"string": "2014-02-22
19:07:00.383869",
"@class": "datetime",
"@module": "datetime"
},
"_materialsproject": {
"submission_id":
52621,
"snl_id": 398676,
"spacegroup": {
"lattice_type":
"tetragonal",
"symbol":
"P4_2/mmc",
"number": 131,
"point_group":
"4/mmm",
"crystal_system":
"tetragonal",
"hall": "-P 4c 2"
}
},
"_cedergroup": {
"BURP_sids": [
409544,
409545,
409546
],
"icsd_ids": [
],
"e_above_hull":
0.075125350000000423734
},
"references": "",
"authors": [
{
"name": "Geoffroy
Hautier",
"email":
"geoffroy.hautier@uclouvain
.be"
},
{
"name": "Bo Xu",
"email":
"boxu14@mit.edu"
}
],
"remarks": [
"supplementary
compounds from MIT
matgen database"
],
"projects": [
"MIT matgen"
],
"history": [
{
"url": "http://www.fiz-
karlsruhe.de/icsd_home.htm
l",
"name": "Inorganic
Crystal Structure Database",
"description": {
"Collection code":
24692
}
},
{
"url": "",
"name": "",
"description": {
"source": null,
"orig_name": "Basic
substitution code.",
"formula": "O1 Pd1"
}
},
{
"url":
"http://ceder.mit.edu/",
"name": "MIT Ceder
group research database",
"description": {
"source": 105986,
"orig_name": "",
"formula": "FeO"
}
},
{
"url":
"http://www.materialsproject.
org",
"name": "Materials
Project structure
optimization",
"description": {
"fw_id": 820305,
"task_type": "GGA
optimize structure (2x)",
"task_id": "mp-
753682"
}
},
{
"url":
"http://www.materialsproject.
org",
"name": "Materials
Project structure
optimization",
"description": {
"fw_id": 820308,
"task_type":
"GGA+U optimize structure
(2x)",
"task_id": "mp-
776678"
}
}
]
},
Metadata
Crystal
DB sources
References History of
structure
optimizations
Future work: unified view of
provenance
VASP
result
ICSD
VASP
result
VASP
result
Post-
processing
Material
properties
Computation
Data import
processing
e.g., Defects
Sandbox example: Multivalent
JCESR
users
Non-
JCESR
users
Multivalent app
Sandboxes = Database + Apps
Core data Core data
+
multivalent
materials
Non-
JCESR
users
JCESR
users
Technical challenges
• Pre-process data for real-time search
• Interfaces for per-user access control
– https://materialsproject.org/materials/1234?san
dbox=jcesr
– Web UI elements
and
Future: dynamic sandbox creation
Current:
– Large & significant
additional data / apps
• e.g., JCESR
– Longer-term
connections to MP data
• e.g. porous materials
– Companies
• e.g. VW/Stanford
Future
small collab.
per-user?
CoD?
Summary
• Validation
– guard against bugs by checking all data daily
and at data import/creation time
• Provenance
– universal standard for annotating data
provenance
• Sandboxes
– unified view of distinct databases
– onramp for new collaborations and data

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Materials Project Validation, Provenance, and Sandboxes by Dan Gunter

  • 1. The Materials Project Validation, Provenance and Sandboxes
  • 2. Goals • Validation – constantly guard against bugs in core data and imported data • Provenance – know how data came to be • Sandboxes – Combine public and non-public data; "good fences make good neighbors"
  • 3. Validation (Internal) Database ID External ID What we expected What we got
  • 4. Validation runs all the time • Rules with "constraints" for every database (and sandbox) • Test constraints against entire DB every night  email reports • Validation engine, etc. all open-source software in pymatgen-db Remote server Validation engine Rules MP Databases Reports (email, web pages, ..)
  • 5. Rules have a simple syntax _aliases: - snl_id = mps_id - energy = analysis.e_above_hull materials: - filter: constraints: - final_energy_per_atom <= 0 - initial_structure.lattice.volume > 0 - initial_structure.lattice.a > 0 - initial_structure.lattice.b > 0 - initial_structure.lattice.c > 0 - initial_structure.lattice.matrix size 3 - formation_energy_per_atom <= 5 - formation_energy_per_atom > -5 - cpu_time > 5 - e_above_hull > -0.000001 - final_energy < 0 - reduced_cell_formula size$ nelements # Check num. ICSD sources for selected compounds - filter: - task_id = "mp-540081" constraints: - icsd_id size> 10 - filter: - task_id = "mp-20379" constraints: - icsd_id size 1 - filter: - task_id = "mp-13634" constraints: - icsd_id size> 0 - filter: - task_id = "mp-600022" constraints: - icsd_id size 0 # NiO2 phases should never become stable - filter: - e_above_hull = 0 constraints: - pretty_formula != 'NiO2' tasks: - filter: - state = "successful" constraints: - output.final_energy_per_atom <= 0
  • 6. Validation summary Easy-to-use, integrated, efficient tools to report errors Next steps – Record all check results in DB – More sophisticated checks (Map/Reduce) – Make it easier to add new checks internally – Make it easier to add new check for anyone • per-sandbox or even per-user ("MP Alerts")
  • 7. Provenance: How do I know that the data is correct?
  • 8. Types of provenance in the system 1) Calculation workflows – FireWorks records calculation inputs, .. results in great detail 2) External datasets – Structure Notation Language standardizes the naming of data sources and publications 3) Post-calculation data transformations – New "builders" provides framework for tracking creation of final database products (1) (2) (3)
  • 10. Provenance in DB Structure Notation Language "snl_final": { "about": { "created_at": { "string": "2014-02-22 19:07:00.383869", "@class": "datetime", "@module": "datetime" }, "_materialsproject": { "submission_id": 52621, "snl_id": 398676, "spacegroup": { "lattice_type": "tetragonal", "symbol": "P4_2/mmc", "number": 131, "point_group": "4/mmm", "crystal_system": "tetragonal", "hall": "-P 4c 2" } }, "_cedergroup": { "BURP_sids": [ 409544, 409545, 409546 ], "icsd_ids": [ ], "e_above_hull": 0.075125350000000423734 }, "references": "", "authors": [ { "name": "Geoffroy Hautier", "email": "geoffroy.hautier@uclouvain .be" }, { "name": "Bo Xu", "email": "boxu14@mit.edu" } ], "remarks": [ "supplementary compounds from MIT matgen database" ], "projects": [ "MIT matgen" ], "history": [ { "url": "http://www.fiz- karlsruhe.de/icsd_home.htm l", "name": "Inorganic Crystal Structure Database", "description": { "Collection code": 24692 } }, { "url": "", "name": "", "description": { "source": null, "orig_name": "Basic substitution code.", "formula": "O1 Pd1" } }, { "url": "http://ceder.mit.edu/", "name": "MIT Ceder group research database", "description": { "source": 105986, "orig_name": "", "formula": "FeO" } }, { "url": "http://www.materialsproject. org", "name": "Materials Project structure optimization", "description": { "fw_id": 820305, "task_type": "GGA optimize structure (2x)", "task_id": "mp- 753682" } }, { "url": "http://www.materialsproject. org", "name": "Materials Project structure optimization", "description": { "fw_id": 820308, "task_type": "GGA+U optimize structure (2x)", "task_id": "mp- 776678" } } ] }, Metadata Crystal DB sources References History of structure optimizations
  • 11. Future work: unified view of provenance VASP result ICSD VASP result VASP result Post- processing Material properties Computation Data import processing e.g., Defects
  • 14. Sandboxes = Database + Apps Core data Core data + multivalent materials Non- JCESR users JCESR users
  • 15. Technical challenges • Pre-process data for real-time search • Interfaces for per-user access control – https://materialsproject.org/materials/1234?san dbox=jcesr – Web UI elements and
  • 16. Future: dynamic sandbox creation Current: – Large & significant additional data / apps • e.g., JCESR – Longer-term connections to MP data • e.g. porous materials – Companies • e.g. VW/Stanford Future small collab. per-user? CoD?
  • 17. Summary • Validation – guard against bugs by checking all data daily and at data import/creation time • Provenance – universal standard for annotating data provenance • Sandboxes – unified view of distinct databases – onramp for new collaborations and data

Editor's Notes

  1. Picture of 1915 Heinrich Campendonk painting, "Landscape with horses". Steve Martin paid $850K for a forged version of the painting, from a reputable art house in Paris, in 2004. He sold it at a loss of $250K before discovering it was a forgery. The forgery was performed by Wolfgang Beltracchi.
  2. Sandboxes are a way to share preliminary data in the context of MP data and tools.