Transcript Slide 1
Fluvial Architecture Knowledge Transfer System (FAKTS): querying the database from the FRG website Luca Colombera, Nigel P. Mountney, Marco Patacci Fluvial & Eolian Research Group – University of Leeds Querying FAKTS Two alternative ways to interrogate FAKTS: - WEB-BASED FRONT-END hosted on FRG website. Easy to use, but of limited capability. Queries can be run on the website without requiring download of software or data. - SQL QUERIES on MySQL. More difficult to use, but it enables full database interrogation. Queries are run locally, requiring download of software (MySQL and HeidiSQL) and database. Web-accessible front end Easy to use, limited capability of query: - depositional and architectural elements currently included; - dimension and transition data made available; - limited number of filters. Further developments will follow. Web-accessible front end Go to: http://frg.leeds.ac.uk/ Web-accessible front end Log in to ‘Sponsors’ Pages’ Web-accessible front end Select ‘FAKTS Database’ from left-hand panel Web-accessible front end Excel spreadsheets containing example output retrieved from the fully-searchable version of FAKTS are available for download. Web-accessible front end Excel spreadsheets containing example output retrieved from the fully-searchable version of FAKTS are available for download. Web-accessible front end Excel spreadsheets containing example output retrieved from the fully-searchable version of FAKTS are available for download. Web-accessible front end The menu-driven front-end can be accessed from the same page. Web-accessible front end Queries can be formulated and run from this page. Web-accessible front end (1) the scale of observation (scale of genetic unit) should be chosen from the right-hand panel. Web-accessible front end Let’s say we are interested in large-scale depositional elements. Web-accessible front end The number in brackets under the genetic-unit type tells us that 46 studies contain information at the depositional-element scale. Web-accessible front end (2) the type of output (i.e. geometry or transition data) we are interested in should be selected next. Web-accessible front end Let’s say we are interested in obtaining dimensional parameters. Web-accessible front end Now we can filter the database on the parameters on which the depositional systems are classified (lower right-hand panel). Web-accessible front end (3) Let’s say we are interested only in data from convergent tectonic settings. Web-accessible front end (3) let’s say we are interested only in data from convergent tectonic settings: we get 22 case studies now. Web-accessible front end (4) now, we want to further filter the database by selecting only systems from subhumid basins. Web-accessible front end (4) now, we want to further filter the database by selecting only systems from subhumid basins. Web-accessible front end 11 case studies are now left. Web-accessible front end 11 case studies are now left: here you see them listed. Web-accessible front end (5) let’s say that we want to exclude modern-river data from the South Saskatchewan: just click on (Remove) in its box. Web-accessible front end The South Saskatchewan data has now been removed. Web-accessible front end A summary of the filters applied and case studies considered is presented at the top of the central panel. Web-accessible front end (6) now we can select the type of depositional element (channelcomplex or floodplain) for which we want dimensional data. Web-accessible front end (6) now we can select the type of depositional element (channelcomplex or floodplain) for which we want dimensional data. Web-accessible front end (7) now we only need to click on ‘download’ to obtain the Excel spreadsheet with the filtered channel-complex output. Web-accessible front end The Excel spreadsheet with FAKTS output can now be opened or downloaded for analysis of channel-complex geometries. Web-accessible front end The Excel spreadsheet contains both architectural data, listed separately for each individual channel complex, and metadata. Web-accessible front end If we want to run a new query, we can reset the filters applied by clicking on ‘Reset Filters’, at the top of the right-hand panel. Web-accessible front end The screen will appear as above, as a confirmation that the filters have been reset. Web-accessible front end Let’s see another example: we want to derive lateral transitions statistics of CH architectural elements in braided systems. Web-accessible front end (1) therefore we select the scale of genetic unit of interest, which is now ‘Architectural Elements’. Web-accessible front end Now we need to select again the type of output: unit transitions. Web-accessible front end (2) we therefore click on ‘Unit Transitions’. Web-accessible front end Now we want to filter the database on river pattern, so that only braided systems are included in the query. Web-accessible front end (3) we therefore click on ‘Braided’ under the ‘River Pattern’ filter. Web-accessible front end Now, let’s say we only want to derive output from the highestquality case studies: we can filter on case data quality index. Web-accessible front end (4) we therefore click on ‘A’ under the ‘Dataset DQI’ filter. Web-accessible front end (5) now we can select the direction of transition in which we are interested from the drop-down menu in the central panel. Web-accessible front end (5) finally, we need to select the type of architectural element for which we want to derive transition statistics. Web-accessible front end (6) now, we can download the Excel spreadsheet with the relevant output by clicking on ‘Down. Excel’. Web-accessible front end The Excel spreadsheet with FAKTS output can now be opened or downloaded for analysis of CH lateral-transition data. Web-accessible front end Again, the Excel spreadsheet contains the raw architectural data, each row represents a lateral transition to an individual element. Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies. Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies. Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies. Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies. Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies. Conclusions FAKTS interrogation MySQL queries FRG website - HeidiSQL front-end requires basic SQL knowledge; - user-friendly menu-driven frontend; - output referring to any type of genetic unit can be generated; - depositional and architectural elements currently included; - any type of output can be queried (including proportions, grain size, etc.); - dimension and transition data currently made available; - all available filters can be applied; - limited number of filters; - it is possible to tailor the query so that output does not require further data analysis. - output is given in the form of raw data, which may require further analysis. Further developments will follow.