The Computational Materials Repository

More documents

Recommendations

Info

12 Introductionis an integral part in daily routine of biologist researchers.Other biological databases are Ensemble[2], which stores information aboutthe genome, or the Protein Data Bank (PDB)[3] - which contain published3D structures of proteins; a good example of collaborate efforts is the HumanGenome Project[4] that was initiated in 1990 and aimed at sequencing thewhole human genome. Many institutes around the world were participating insequencing, analyzing, annotating and submitting data.The electronic structure calculation community is not there yet. Especiallywe are far from a cross-linked freely available database where researchers canupload their data and put it in context with already available data in order toderive new results - however partial solutions exist: The Virtual Materials DesignFramework (VMDF)[5], a tool to filter and analyze aggregated sets of electronicstructure data introduces a first step towards user-friendly analysis of data, theCAMd database[6] or AFlowLib[7] that present a selection of aggregated dataon the Internet and make it available through a web interface - or ICSD, theInorganic Crystal Structure Database[8, 9] that collects validated experimentallydetermined data, and provides a software tool and a web interface to performsearches - unfortunately not for free. During the last eight months more elaboratetools and databases have seen the light of day: ESTEST[10] aims at validationand verification of electronic structure calculations of different codes; MaterialsGenome[11, 12] has a high-throughput infrastructure to perform screenings andpresents results through toolboxes that are accessible on the Internet - andthe Quixote[13, 14] project that focuses on quantum chemistry data presents acollaborative open source framework to collect and process data from differentsources.The reasons why we are not there is that it is hard to find a commonapplicable scheme that is able to cover most aspects. The electronic structuredata is for instance more heterogeneous - there are numerous file formats - andthe the analysis depends greatly on the perused goal. The challenges of handlingdata in an efficient and reusable way can be divided in a few mature tasks asrepresented in Fig. 1.1.
13Figure 1.1: Major tasks when aggregating data - the arrows represent the work flow.Calculating produces results that need to be collected in a commonly readableformat. These results could then be stored in a database for further analysis. Thepresentation can be done in a web-interface or any other tool that is able to retrievedata from the storage. Important is to notice that analysis can produce derived datathat should be added to the storage as well.With the Computational Materials Repository (CMR) that is presentedin this document, we provide a modular open source system that addressesthe challenges of collecting, storing, making data available through interfacesand propose and implement basic ideas how to perform analysis. The focusis in particular on DFT codes because they represent a favorable trade-offbetween speed and accuracy for the treatment of “few-hundred-atom” systemshighly relevant for understanding physical and chemical properties of materials.We propose a file-format (db-files) that holds extracted data syntactically andsemantically as close as possible to the original output file - and introduce groupsto indicate connections between data. The Python user interface allows to searchand query data which then can be analysed. In order to cope with differentassumptions on names and units, CMR implements mappings. A mappingenables to rename and convert for example the field CartesianPositions inBohr units, to positions in Angstrom.To get a user-friendly way of looking at the data, the PHP/HTML interfacepresents the data with the help of a MySQL database and a webserver as shownin Fig. 1.2. When the data is published it is possible to create a custom view asshown in Fig. 1.3 to make the results easier accessible for public.
Page 3: Document HistoryThis document bases
Page 8 and 9: 8 Contents
Page 10 and 11: 10 CONTENTS3.3.2.3 CMR Database . .
Page 14 and 15: 14 IntroductionFigure 1.2: The PHP/
Page 16 and 17: 16 Introduction
Page 18 and 19: 18 Introduction and usage of CMRAll
Page 20 and 21: 20 Introduction and usage of CMR•
Page 22 and 23: 22 Introduction and usage of CMRimp
Page 24 and 25: 24 Introduction and usage of CMRFig
Page 26 and 27: 26 Introduction and usage of CMRAt
Page 34 and 35: 34 Introduction and usage of CMR1 T
Page 36 and 37: 36 Introduction and usage of CMRloo
Page 38 and 39: 38 Introduction and usage of CMRto
Page 40 and 41: 40 Introduction and usage of CMRAAf
Page 42 and 43: 42 Introduction and usage of CMRTo
Page 44 and 45: 44 Introduction and usage of CMRmem
Page 46 and 47: 46 Introduction and usage of CMRato
Page 54 and 55: 54 Introduction and usage of CMR
Page 56 and 57: 56 Computational Materials Reposito
Page 62 and 63:
62 Computational Materials Reposito
Page 64 and 65:
Page 66 and 67:
Page 68 and 69:
Page 70 and 71:
Page 72 and 73:
Page 74 and 75:
Page 76 and 77:
Page 78 and 79:
Page 80 and 81:
80 Appendixputer system, Date, HF,
Page 82 and 83:
82 Appendix4.2 PHPUI script to cont
Page 84 and 85:
84 Appendix4.3 Deployment Examples
Page 86 and 87:
86 Appendix4.4 Inside a db-fileA mi
Page 88 and 89:
88 Bibliography
Page 90 and 91:
90 BIBLIOGRAPHY[11] Anubhav Jain, G
Page 92 and 93:
92 BIBLIOGRAPHY[35] XML Technology.
show all

The Computational Materials Repository

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?