Home

FishFrame 4.3 User manual

1. Welght can be pulled into the table instead or together with the number This opens up for the possibility to make calculated measures based on both measures DO NOT remove Species from the axes Species Pivot table Species distribution in sea harbour distribution in map sampled catches Individual catches sampled and chart are standardized raised to 1 tonnes catches gt In of total catch Samples with validity weight code 4 is included from this report 13 CPUE weight Pivot table per hour map and chart Discard Pivot table fraction By map weight and chart Mean weight Pivot table map and chart Standardized Pivot table CANUM map Admin only and chart 14 26 January 2007 Multiple samples within same stratum are aggregated as an average 1 tonnes catch Each sample is given equeal weighting in the average Zero catch for a given species in a given stratum affects the average if 3 The species is represented in a stock living in the area ICES sub area There is sampled catch of any species within the same stratum DO NOT remove Species from the axes Catch Per Unit Effort Catch weight per hour of fishing effort Zero catches are included it is therefore crucial to select fishery and dataset with care the dataset could include stations where only cod was reported thereby indicating a false zero catch of other species However catches outside the stock
2. from a merge between a b and c by Y Q FS F A C Sp St Cc Ss and L 47 26 January 2007 5 PopulateStandardizedCANUM Gives number per 1000 tonnes landed by Y Q ES F A C Sp St Cc Ss and Age a Get number per 1000 tomnes landed as the sum of age fractions numberPer1000Tonnes by Y Q ES F A C Sp St Cc Ss and Age from a merge by length between Box7 and ALK b Delete all landing records where the corresponding discards was lost in a discard is zero because of missing ALKs Processes creating the mean weight The MeanWeight is created from CA SLD and ALK records The SLD and ALK are combined to produce a standardized distribution by age and length called WeigtedFraction SLD is weighted by CatchWeight The WelgtedFraction is combined with a matrix containing the basic meanweighs from CA resulting in PartOfMeanWeight by Y Q FS F A C Sp St Cc Ss Length and Age PartOfMeanWeightOfStrata is WeigtedFraction by Y Q FS F A C Sp St Cc Ss and Age The mean weight is then calculated by the pivot table as the sum of PartOfMeanWeight divided by the sum of PartOfMeanWeightOfStrata Steps in creating MeanWeight 1 MeanWeight a Get average MeanWeight from CA by Y Q A C Sp St Cc Ss Length and Age only where number gt 0 meanweight gt 0 and the CA record is not disabled during the outlier analysis b Get fraction from SLD and split it into age groups using ALK
3. Change password It is required to retype the password this is to avoid problems for the user in case of involuntary mistyping of passwords the password is masked as so a visual quality check 1s not possible There 1s a password policy to avoid hacking The policy does now allow the password to be equal to any part of the name or email The password should also be minimum 6 characters long and preferably contain letters numbers and special characters New user The administrator can create new users using the designated form Figure 36 3 FishFrame Microsoft Internet Explorer Ja fx File Edit View Favorites Tools Help ae Address El http ch itto3 FishFrame FishFrame bo Go Links gt Select dataset to Data browser Reports Analysis Data action Info amp Help browse First name Landing statistics Last name Aggregated E mail Commercial samplings Country Select one Sea Harbour User Role Select one Market Password Trawl surveys i Datras Password Confirmation Fields marked with are mandatory Figure 36 The form where new users are crated Activity report The activity report is a pivot table that can be used to analyse the usage of FishFrame Contact Email links to e The FishFrame staff e The editors uploading data from countries e All users Links A list of links to related online databases international organisations and the institutions using
4. rel 3 Address sy http dmz web08 dfu min dk Balticsea FishFrame v g Go Links Select dataset to Data browser Reports Analysis Data action Info amp Help Misc browse PivotTable Field List Ed Drag items to the PivotTable list LandingStatistics1 Totals Official Catch Area Country S Fishery S Fishery Set S Quarter Species El Year EAS 3 56 14 5810 Landing statistics Species y Country y Area y Fishery Set y Fishery y All All 1 Quarter y 1 JAN Al Al Official Catch Official Catch Official Catc 67589000 137596000 321384640 146393662 70262213 67044593 55330054 51637054 69312000 71999000 40967000 1097523616 319239000 911678000 639698751 1159745090 691055570 698748366 594047674 266072674 308319000 152615000 120608000 6061827127 445147000 604555000 1059747372 761259897 675307341 496079595 273266680 229416680 146733000 122690000 112471000 4930553565 hi Official Catch Official Catch 157853000 291113000 389984224 272140347 174274307 176025196 149530400 97718486 42255000 152268000 Grand Total J 992826000 1944942000 2610815167 2339547196 1618979511 1439497772 1072490896 644644696 656619000 499572000 27 4046000 1904276130 13994182438 Map N Europe E Done O Trusted sites 4 Figure 37 A pivot table displaying landing statistics More in
5. station number 1 and the erroneous value was XXX The comment describes that 1t was an illegal value for that field and gives a link to the list of valid values Figure 14 The natural key can be seen in a special sub report Figure 15 by clicking on the Natural key link in the rightmost column This is important information for finding the error if the upload format used is XML but also useful for CSV file uploading 19 26 January 2007 E frmUploadFile Microsoft Internet Explorer SEE File Edit View Favorites Tools Help Address Fa http fidm2 webOs dfu min dk BalticSea FishFrame Data UploadDownload ErrorReport aspx strErrorType PrimaryXSD alidation amp strErrorFileName PrimaryXSDValidationError amp strxmiDe Y Go Links A Record aid Station Value SIE Natural Field Record type an ies BpeciesCode BL OSL o Tacna emmeraton vales Natural Key SpeciesCode HL____Pp___ fos 999999 Acceptable enumerationvalues Natural Key SpeciesCode EL Mandatory value is missing Natural Key Kox Acceptable enumerationvalues Natural Key E Mandatory value is missing Natural Key ize Category pO s eeror Acceptable range for tis feldi beween Denda Wana Key SizeCategory HI MANN aT E T POK dAcceptable enumerationvalues Natural Key 0999099 __ycenprableenumerason values anual ey Pue o EE Range error Acceptable range for this field is between 0 and Panes a ee Range error Acceptable range for this field is between 0 an
6. c Save a times b as PartOfMeanWeight by Y Q A C Sp St Cc Ss Length and Age d Save b as PartOfMeanWeightOfStrata by Y Q A C Sp St Cc Ss Length and Age e Mean weight sum of PartOfMeanWeight divided by sum of PartOfMeanWeightOfStrata This division normalizes the part of PartOfMeanWeight that originates from b to 1 0 if PartOfMeanWeight is aggregated across ages or length then this last part 1s done by the pivot table Mean weight Note that the Stock is set by the spawning type 1f this field is empty then the stock is deduced by the species and area Discard fraction Weight The processes that create the Discard fractions analysis based on catch weights are summarized below The input to the processes 1s the database tables containing the uploaded data while the output 1s the values in the pivot tables Stations are pooled and a discard fraction of the total catch landing discard is calculated by Country Year Month Area StatisticalRectangle FisherySet 48 26 January 2007 Fishery and SpeciesCode That is the basis for the pivot report When drilling up in the pivot report grouping areas or time then a simple average 1s calculated 1 SQL view AS CS CPUE CatchWeight WithZeroObservations a Get all catch weights for landings and discards summed up across stations by Country Year Month Area StatisticalRectangle FisherySet Fishery and SpeciesCode Where
7. Processes creating the Age Length Key ALK cccccccnnnncnnnnnnoonoccccncccncnononcnnnos 46 Processes creating the Standardized CANUM stCANUM cess 47 PROCESSES Creating The mean WISE add 48 Discard TACU ONS A E 48 IV TI paca E O O 48 CPU A a a 49 A A II IP 49 ACUSAN a da 50 Calculation of global abundance estimates mean weight and mean length 50 Interpolation of global abundance estimates mean weight and mean length 50 A eee Re een ne ae ee Cnn MeO Oe Ce Meee a ee ere T 52 PD PCTCICE diia 53 APPS dd 53 PNP CII Messi 54 OVENI Woren Sens ae talks tetera eines Sectoid feet coda onde S ears eonda tin 54 PP Oy is a acetate dees eee ee A E 54 COME CK SOUS ra vos usmandSebadeevoduchatedatadansosuenanneunedoie 54 CHEESE NO soci a earned 54 Check CLCAMON e So 55 COE CS SE EXC CU OM 57 Importing check sets data set definitions and checks ooonnccccccnncnnnnnnnm 58 pecuri CW NO cando WAL nai a A 59 26 January 2007 Introduction This document describes how to use all the features in FishFrame It is also the place where users can exchange descriptions of best practice All contributions are welcome and can be mailed to the administrator This document covers all standard FishFrame clones i e FishFrame Baltic Sea FishFrame North Sea and FishFrame FantaSea even though the Baltic clone is chosen for illustrations etc A separate user manual can be found for the Fish
8. approved Green links mean approved while red indicates not approved There are two links for each combination of Species SpawningType Area and Quarter The first link is for age length relations and the second 1s for length weight relation Click on a link to get the corresponding outlier analysis OA 2D 26 January 2007 A FishFrame Microsoft Internet Explorer File Edit View Favorites Tools Help Address E http dmz web08 dfu min dk BalticSea FishFrame Select dataset to Data browser Reports Analysis Data action Info Help browse Denmark 2003 Age Length relation Length Weight relation a Clupea harengus area28 aay aa Gadus morhua area 25 o1 o2 a3 02 Pleuronectes platessa area 22 Q1 02 Pleuronectes platessa area 24 Q1 02 Pleuronectes platessa area 25 Q1 Salmo salar area25 for E Sprattus sprattus area 22 or fof Sprattus sprattus area 25 or fof sprattus sprattus area 26 or fof Sprattus sprattus area 28 oi P e Green text Approved Red text Not approved Q1 Conca Core o e erg oz ie Q1 EA aa a Trusted sites Figure 18 Outlier analysis overview table for Denmark 2003 The web browser needs a plug in installed for viewing the OA diagrams The plug in is free and details about downloading and installing 1t can be found under Info amp Help IT Support Help on
9. placements of the cells Try downloading the sheet and only copy the data into the sheet If this should not help then mail the sheet to the administrator who will be able to help It is recommended that programs to extract data from databases and format directly into XML are made nationally This section describes how to use the converter program Exchange Format Converter Excel gt XML 1 Download and install Net components v 1 1 Cif you do not have it already 2 Download and install converter program 3 Read the description of how to use the program in the Usermanual Figure 27 Download page for the exchange format converter application The program will after installation be accessible from program files like other programs on the PC Figure 28 m FishPrame rr FishFrameAcoustics J E ALS 2 SML converter Figure 28 Start the converter program under FishFrame gt FishFrameAcoustics in the program files The application only consists of one form see Figure 29 On this form the year country ship Species and stock is selected The path and name of the excel file to convert is either entered manually or selected by clicking browse The button Clear form removes all entries in the textboxes The button Create XML starts the conversion process indicated by the progress bar that shows up below the button When the process ends the result is written above the progress bar as seen on Figure 30
10. Figure 49 The list of available checks sets Check set execution CreationDate 16 01 2006 14 01 2006 14 01 2006 14 01 2006 Clicking on the Execute button besides a check set Figure 49 runs the checks The results from the example can be seen on Figure 50 The results from each check can be viewed by clicking on the sign to the left of the check title 57 26 January 2007 Results of executing check set Check Set Name Cod age length relations Description Below checks did not pass validation Expanding a check will display the failed data Cod age 2 of length 200 500 mm El Cod age 3 of length 300 650 mm Below data did not pass valid Journey StationNo Area Quarter SpeciesCode CatchCategory SizeCategory Gadus Denmark 2000 691 2d 1 Landing 3 660 morhua Denmark 2000 691 24 i Gadus Landing 3 660 morhua Denmark 2000 693 A il Gadus Landing 3 670 morhua Denmark 2000 693 O al Gadus Landing 3 700 morhua Denmark 2000 694 1 22 ld Gadus Discard 0 290 morhua Denmark 2000 695 22 i Gadus Landing 2 750 morhua Denmark 2000 698 1 24 1 Sadus Discard 0 270 we gt Close Figure 50 The result report Importing check sets data set definitions and checks New check sets can be based on other check sets Some will become templates After clicking on the create new check set button Figure 44 it is possible to import either a full check set or the data
11. FishFrame 35 26 January 2007 Generic components The generic components are blocks of the user interface that are used several places in the application The functionality of the components are independent of the specific implementation and are therefore described separate from those chapters Some of the components require some kind of installation The details of this can be found under Help amp Info IT Support Pivot tables A PivotTable Figure 37 1s an interactive table that can be used to analyze data dynamically Some of the features are Filtering data Sorting data Grouping data Summing up calculating from Formatting Copy data to other programs Dump data to excel and continue dynamic work there Moving adding and removing fields Drilling down drilling up slicing and dicing data Most of theses features are accessible when right clicking an item e g a field for field working with properties or on the green header bar for table properties The functionality is described in the MS Office Pivot table component help that is being reached by pressing the icon on the upper right corner of the pivot table The help document is well structured and gives quick access to specific info through a navigation tree or a search 36 26 January 2007 2 FishFrame Microsoft Internet Explorer File Eat View Favorites Tools Help Q tec X Q x a A yo Search S 7 Favorites QU Media g B te K
12. Information on selection Area samples Water area el 2 The Kattegat ie 20937 km Figure 40 Pivot map from Figure 39 in grey scale prepared for publishing in a black and white report SVG diagrams The SVG diagrams Figure 19 and Figure 20 are used for the outlier analysis The features of a SVG diagram are e Zoom in out and to original extent Right click on the diagram and select Zoom 1n Zoom out or Original extent e Save Right click on the diagram and select Save SVG as The diagram can be saved as a SVG file which can be opened in a browser later SVG stands for Scalable Vector Graphics and is a XML format for displaying diagrams on the internet The XML data containing the actual data can be explored by right clicking the diagram and selecting view source More information about SVG can be found at http www w3 org Graphics SVG Simple tables The features of a simple table Figure 41 are 41 26 January 2007 e Show all records The table only shows the first 15 records The Show all button below the table indicates that there are more records for the current data selection Click the button to get all data e Show next previous records The two links Back and Forward below the table indicates that there are more records for the current data selection Click the links to get the next or previous 15 records e Sorting Click on a column header to sort th
13. Journey 1095 a ft ca o Show all O Trusted sites Figure 41 A simple table as 1t appears when browsing data with the tree Future versions planning and bug handling Errors and crashes Errors that occur during normal use of FishFrame are logged and the system immediately sends a mail to the administrator The administrator will then take the appropriate action which would normally be to contact the affected user correct the error or add the bug to the task list so it can be fixed as soon as possible It is OK for users to contact the administrator themselves for help and questions 1f they experience a system error 42 26 January 2007 Version planning The development process is incremental so that new features and bug fixes are added in releases This is to ensure that a proper system test is performed on each release Some minor changes that can not introduce bugs e g documentation are added on a more ad hoc basis The selection of developments in a given release 1s picked from the prioritized task list and module list which can be downloaded from the documentation page under Info amp Help in the menu The prioritization is made on the basis of user feedback System testing Some of the testing 1s documented in the test documentation which can be downloaded from the documentation page under Info amp Help in the menu Technical stuff This is documented in the developer s manua
14. Sele File Edit View Favorites Tools Help ae Links irst 2001 Bo i Ji Landing 2 Done Trusted sites Figure 15 Natural key report from the data check error report 2 Second check This is a mandatory step The second check is the check where the last requirements described in the exchange document is performed These requirements are dependencies between fields e g the field VesselLength is mandatory but Optional if gear is fixed gear On the first page Figure 16 the data set is selected A Check button appears after year and country had been selected Quarter and area are optional Care should be taken when selecting data set because the checker will stamp the data with data status 2 as last step even if some of the data has already been released and thereby has the data status 6 This especially applies to countries where different labs upload data from different areas or if data are uploaded quarter by quarter When clicking on Check the data checking routine is executed and the result is displayed as seen on Figure 17 passed or Figure 18 not passed If the data does not pass the checks then the input data should be corrected in the national database a new upload file should be generated and uploaded Data status is kept on 1 if the data does not pass the check Second check C Select data to check Year county Quarter Figure 16 Sele
15. The two newly created XML files is places in the same folder as the excel sheet Their names are concatenations of Country ship code year file type e g Denmark DAN2 2005 AB xml The XML files are then ready for upload Manual editing in the files can be done with a normal text editor like notepad or a special XML editor like XML spy 31 26 January 2007 FishFrameAcoustics Excel to AML converter select year 2005 select country DEN Select ship DANZ DAN Select species Clupea harengus Select stock het 47d3 and her 3322 Select excel sheet Browse Clear form Create xml Close Figure 29 The user interface in the conversion application Generating ml files COMPLETE TT TTT TTT TE Figure 30 Conversion ended successfully Info amp Help All documentation tutorials and help on how to use Info amp Help FishFrame interpret data or format upload files 1s found Tutorials under Info amp Help Figure 31 Documentation Tutorials Exchange spec s The tutorials are small film clips that can be downloaded IT support Figure 32 They come wrapped in a player so they do not require any special software to be viewed Click on the link to open or download the tutorials Notice that they are quite large for a thin internet connection up to 7 MB Figure 31 Selection of info amp help a2 26 January 2007 2 FishFrame Micro
16. Year Q Quarter C Country J Journey St Station FS Fishery stratification F Fishery A Area Sp Species St Stock Cc Catch category Ss Size sorting and L Length 45 26 January 2007 Processes creating Standardized length distribution SLD The SLD 1s created from data from HH and HL records The processes used here are mainly filtering weighting and standardizing the data The SLD is stored as weighted numbers from stations by Y Q FS F A C Sp St Cc Ss and L The weighted number is in itself no real measure It only gives sense as fraction of the total for all lengths in the stratum Steps in creating SLD 1 MergeHHWithHL Merges HH with HL Only uses records where HLNoAtLength gt 0 HL CatchWeight gt 0 HL SampleWeight gt 0 and HL ValidityCode 1 2 GetFishery Sets the fishery field according to the fishery set and the definition hereof 3 PopulateSLD a Sum up total number by Year Journey Station Species Catch category and size sorting from MergeHH WithHL b Merge this with the output from MergeHH WithHL by Year Journey Station Species Catch category and size sorting Get numbers weighted by catch weight as number catch weight total number by Y Q J St FS F A C Sp St Cc Ss and L where fishery is output from GetFishery Only uses records where fishery has a value c Sum up weighted numbers from stations by Y Q FS F A C Sp St Cc Ss and L Note that the Stock is
17. above Effort statistics 1 Upload first check Same as for Commercial samplings disaggregated step 1 please refer to that chapter above 6 Release Same as for Commercial samplings disaggregated step 6 please refer to that chapter above Acoustic survey data detailed stage 1 1 Upload first check Same as for Commercial samplings disaggregated step 1 please refer to that chapter above 6 Release Same as for Commercial samplings disaggregated step 6 please refer to that chapter above Acoustic survey data compiled stage 3 1 Upload first check Same as for Commercial samplings disaggregated step 1 please refer to that chapter above 6 Release Same as for Commercial samplings disaggregated step 6 please refer to that chapter above Data action Data integration All the work steps in the data flow concerning rasing aggregation and estimation of data 1s found under Data Action gt Data integration 29 26 January 2007 Commercial fisheries This 1s a mandatory step lt To be written gt Acoustic surveys National raising gt Calculate national estimates stage 2 This step 1s under development International compilation gt Calculate global estimates First select the year and Species The system then calculates number weight mean weight and mean length at age maturity stock stat rect etc Calculating global stock estimates fro
18. all data the user can move on to step 4 Since step 3 is an optional step it can be skipped if the time plan makes it impossible 4 Advanced check This is an optional step The user guide for this module is extensive and has therefore been placed separately in Appendix II A set of default checks exists in the system and will typically be the starting point for the user Users can then add delete and modify checks in their own copy of the set run it and save it for later use A filter can be added so the user runs the checks on a subset of the data A user can have several sets of checks The types of checks are e Simple value comparisons e Range max min and enumeration checks depending on other fields e g Age is between 0 and 25 if species is cod e Formula based dependency checks like Weight k Length where k is dependent on the species and maybe Quarter and area too The two prior checks are actually just simple checks of this type 5 Confirm raising settings This is an optional step 27 26 January 2007 Check the settings for the country year stovk and catch category that are worked on Move on to step 6 1f they are correct otherwise get the administrator to change them an editor page 1s under development Stock CatchCategory Data sampling source o me coman fisheries Sea and harbour sampling RyLanding WeightOtaAllspecies Figure 24 Country year stock CatchCategory specific settings for the
19. files El and E2 added as new recordtypes in new file ES effort statistics Definition of Journey added O Trusted sites Figure 8 The upload page Lower part of the page presents a list of recent changes in the exchange format The system then runs through the following steps 1 Uploads the file to the server 2 Key value consistency check not for XML upload Checks 1f parent and child records are matching e g that HH country field 1s the same as all the HL s country fields 3 Conversion to XML not for XML upload 4 Duplicate record check This ensures that lines that are required to be unique with respect to the key parameters e g HH and HL records in CS files do not exist as duplicates This step is skipped and then performed during saving for large LS and AA files 5 Data check a All the range and enumeration checks specified in the exchange document Enumeration checks are checks where valid values are given in a list 16 26 January 2007 b Checks 1f mandatory fields has a value c Check on the XML structure If all steps are passed without errors like in Figure 9 then the data can be inserted into the system Click on the link Yes to insert the data otherwise just navigate away from the page using the menu A successful saving will be reported in the addition of two lines stating FishFrame successfully updated gt The upload of you data completed successfully When the data a
20. from version 4 3 in December 2006 Details on installing and setting up software can be found online under Info amp Help IT Support Project notes It is very important for the FishFrame team that all effort is made as a bottom up process E g close cooperation between developers architects and end users It is in our view the most effective method to add true value to end users The project has so far been managed by DIFRES and all software has been written by software developers in DIFRES We would like to widen the management design group and formalize it Furthermore we welcome any non DIFRES software developers The existing software architecture modules provides the basis for a distributed development Hosting of the FishFrame servers has so far been done by DIFRES This could continue as long as the participating labs are satisfied Hosting could also be handled by any other lab User interface The screen is split into three areas Figure 1 1 The left frame contains the logon page from start and a data tree after the user has logged on 2 The green menu in the upper part of the right frame The menu is expanded when the mouse is moved over a part of the menu Item are selected by single clicking A black triangle indicates that the menu can be expanded further 3 The main screen in the rest of the right frame 26 January 2007 All the functionality is covered menu point by menu point in the designate
21. observed values The age length relationship is described by the von Bertalanfy s growth equation L t L eH 23 26 January 2007 The constants lo and k should be estimated by a non linear regression but is in the current version estimated by a Beverton Holt plot which gives a rather poor fit with few data and outliers are identified if they exceed 2 standard error of the observed values 3 FishFrame Microsoft Internet Explorer SEE ay File Edit View Favorites Tools Help Address E http dmz web08 dfu min dk Balticsea FishFrame Y Go Links A Select dataset to Data browser Reports Analysis Data action Info amp Help Misc browse Outlier analysis for Country Denmark Year 2003 Quarter 1 Species Gadus morhua Area 21 Landing statistics Aggregated Yellow line is regression Green points are inliers Red points are outliers and Grey points are disabled data Commercial samplings lick here to approve this straturi or click on data points on chart to disable enable Sea Harbour Market Length weight relation on catchcategory Discard and sizecategory 0 Trawl surveys Datras Pp ot oh 2 100 Length mm No charts could be provided for CatchCategory Landing SizeCategory 1 there were propably too few data to perform regression Check data through the data tree Length weight relation on catchcategory Landing and sizecategory 2 Trusted sites Figu
22. only set if the stock can be deduced by the species and area If some kind of stock split is needed because more stocks are present for the given species in the given area then stock is not set Processes creating the Age Length Key ALK The ALK is created from data from CA records The ALK is stored as numbers and fraction of total numbers by Y Q A C Sp St St L and Age After the initial population another process estimates ALK s where length exists in SLD but no corresponding ALK could be extracted from the CA records Note This deviates slightly from old cod practice in the Baltic Sea because it used also to be by CatchCategory Steps in creating ALK 1 PopulateALK a Get numbers by Y Q A C Sp St L Age b Get total numbers by Y Q A C Sp St L c Only from CA records that have a number a length and that is not disabled in the data action step 3 outlier analysis d Merge a and b Save a as numbers and a b as fraction 2 CalculateAndInsertALKRegressions middle tier function therefore not in figure a Get up to four data records from ALK Two closest shorter lengths and two closest longer lengths 46 b 26 January 2007 Estimate missing ALK using linear regression if at least two data records are available Note that the Stock is set by the spawning type 1f this field is empty then the stock is deduced by the species and area Processes creating the Standardized CANUM stCANUM The st
23. range between floor and ceilimg OHH OHL Oca Field LengthClass Y Floor 200 Type Value B Ceiling 600 Add selection Figure 47 Setting check criteria In step 3 we enter the title Cod age 2 of length 200 500 mm and clicks Save Back in step 2 of the check set wizard the new check is now visible in the list of checks Figure 48 More can be added In our example Cod age 3 of length 300 650 mm 1s also added S6 Step 1 Step 2 Step 3 Target Dataset Checks Information 26 January 2007 Check Set Creation Module Define checks Available Checks Name Description Cod age 2 of length 200 500 mm Cod age 3 of length 300 650 mm New Check Import full check set Import check Figure 48 The list of added checks Cancel amp Exit Step 3 in the check set wizard is to add a title and a description of the check set In our example the title entered 1s Cod age length relations Clicking Save amp Exit leads back to the list of available check sets Our new check set is now visible in the list Figure 49 Advanced Validation Module Show All Check Sets O Show Your Check Sets Available Check Sets Description CreatedBy Edit Execute Cod age length relations Teunis Jansen Edit Execute Herring stock checks Teunis Jansen Edit Execute Marked samplings checks Teunis Jansen Edit Execute North sea cod checks Teunis Jansen Create Mew Check Set
24. the password now and then Levels of access roles The level of access role is one of the following four 1 Reader 2 Editor 3 Stock coordinator 4 Administrator 26 January 2007 Stock coordinator will be added to the system in the next release The functionality available to each role 1s listed in Table 1 UI BJVP MITA JUQUuISSISSE IO 49035 I3SBI9 S13SN pP Y PPV re O AS a eh e O e y 391 YSNOIY BIVP MIAA SIS 8U8 pue syoda gep peoyumop peojdya BLP ISLIP PUE IJBPITLA SUISSIUW 338UISI A dd y yjunoJ3e I SN UMO JPA Reader 9 1 2 gt 12 pe pe pete Cara ee ee a Administrator PT e e Table 1 Available actions by role only from own country from all countries Functionality The functionality will be presented here in the same order as it is found in the menu Notice that the content of the menu is role dependant so the choice of functionality will always match what your security level permits you to access The menu Figure 2 contains five top items that can be expanded Data browser Analysis Data action Info amp Help Figure 2 The main menu The submenus under each item are explained below Data browser Data browser Reports The type of data to be explored using the data Commercial samplings tree in the left pane can be selected Lenii SELES OTE The tree in the left frame in the tree base
25. 07 Commercial samplings disaggregated 1 Upload amp first check Consult the exchange format specification for information about the content of the data file The exchange format specification can be found on the documentation page under Info amp Help The overwrite rules are described below The upload file is selected in the dialog window that pops up after pressing the browse button on the upload page Figure 8 23 FishFrame Microsoft Internet Explorer File Edit View Favorites Tools Help Address V4 http ich pcb tej01 FishFrame FishFrame Default aspx Select dataset to browse Data browser Reports Analysis Data action Info amp Help die ii samplings Select Zip or ASCU file to upload 568 Harbour Market Landing statistics Browse High resolution Low resolution Effort statistics e High resolution Submit file Low resolution Trawl surveys Datras Exchange format change log ANEW Version 4 0 15 January 2006 e HH Three new fields Mesh size in selection device optional Claimed fishing activity mandatory and Vessel Identifier optional HH Change of field 28 from Number of stations aggregated to Number of hauls sets on Journey CS file structure CAs can now follow HLs on each station when station number is known HH Field 9 VesselLength valid range has been increased to 160 m L1 New field Landings multiplier optional L2 added as new record type in LS
26. 2 OA diagram from Figure 20 after disabling a data point The age length OA Figure 23 consists of a single diagram No diagram is presented if less that three data records are present The regression procedure in the current version is rather poor and will be changed as soon as possible However the plot 1s still of great value to spot data points that sticks out 26 26 January 2007 23 FishFrame Microsoft Internet Explorer File Edit View Favorites Tools Help Address E http fdmz web08 dfu min ck BalticSea FishFramej Select dataset to Data browser Reports Analysis Data action Info Help browse Outlier analysis for Country Denmark Year 2003 Quarter 2 Species Sprattus sprattus Landing statistics Area 21 Aggregated Yellow line is regression Green points are inlers Red points are outliers and Grey points are disabled data Commercial lick here to approve this stratum or click on data points on chart to disable enable samplings Sea Harbour Age Length relation Market Trawl surveys Datras H a ond Age years Trusted sites Figure 23 Age Length outlier analysis diagram with two outliers If larger errors than just a single strange data point are detected the workflow 1s to go back to the raw data in the national database correct the error make a new upload file and start with step 1 again When all links has been changed to green by checking and approving
27. CANUM is created from data from HH HL SLD and ALK records stCANUM is stored as numbers per 1000 tonnes landed by Y Q A C Sp St Cc Ss and Age Steps in creating stCANUM 1 Box0 ByStation d 2 Boxl C 3 Box2 Get catch weight sample weight and total numbers by Sampling type Y Q A C Sp St FS F Cc Ss only where catch weight sample weight and total numbers are present and gt 0 Sum up catch weight for landings by Y Q FS F A C Sp St Excluding markedsamplings Sum up catch weight for discards by Y Q FS F A C Sp St Excluding markedsamplings Merge a and b Gives number and total number by Y Q FS F A C Sp St Cc Ss and L a b 4 Box 7 Sum up number from SLD across lengths by Y Q FS F A C Sp St Cc Ss Merge SLD Gives number per 1000 tonnes landed by Y Q FS F A C Sp St Cc Ss and L a Get overall mean weight as the sum of sample weights the sum of numbers from Box0_ByStation by Y Q FS F A C Sp St Cc Ss excluding markedsamplings for discard records The stations are weighted by samplesize in this meanweight Ratio as Discarded weight landed weight from Box by Y Q FS F A C Sp St Cs set as discard Ratio as Number total number by Y Q FS F A C Sp St Cc Ss and L from Box 2 Get NumberPer1000T as 1000 Ratio from b for discards or 1 for landings OverAll MeanWeight from a Ratio from c
28. FishFrame 4 3 User manual By T Jansen H Degel amp Users of FishFrame Danish Institute for Fisheries Research Charlottenlund castle Charlottenlund Denmark E mail tey dfu min dk amp hd dfu min dk FishFrame Mozilla Firefox File Edit View History Bookmarks Tools Help gt Ee a L http tidma webos fu min l NorthSea Fishrramej al gt Gl coca Data browser Data action Select dataset to browse Commercial samplings Hibene FishFrame 4 3 North Sea Market Landing statisti Han pie Re Fisheries amp Stock Assessment Data Framework Low resolution Effort statistics High resolution Low resolution Acoustic surveys Detailed acoustics Detailed fishing Compiled Trawl surveys Datras 26 January 2007 Table of content A 4 A do 4 Dit dar 4 O 5 is oeaiceudsinded EE E E N N 5 Dato ie y en E E E N 5 Software and hardware requirements e etna eeaaies 6 i 2 61 WS 80 r E E E A E EA 6 UT O ea r dante Gitta eet deoat hie 6 OS UE LY sae tear escent cetacean A nah canta Gath ne aan hice E E E T 7 TOS OM rd did 7 Levels ol ACCESS TONES annor oin aen AE a eee 7 F nciona hi A OOO RR TE On o 8 Dat DONGE ae a o es lhe O elias os 8 REDO erae adidas 9 AnaS iS eao a A A E S 12 Data actiom Data Mamen A A 15 Commercial samplings disaggregated ccccccccccccccceeeeeeeeeeeessesseeeeeeeeeeeeeeees 16 LAndiRS S asc 29 A E a E E 29 Acoustic survey dat
29. FrameAcoustics clones Other documentation can be found on the documentation page under Info amp Help or 1t can be requested from the FishFrame staff The versioning of this document follows the date stamp in the upper right corner on all pages except the front page The latest version 1s always available from the FishFrameAcoustics website The system FishFrame 1s an existing web based datawarehouse application that can be accessed on www FishFrame org FishFrame is the link between stored nationally raw data and the aggregated data used in the assessment process The main workflow in FishFrame brings data through data checking raising extrapolation and export to assessment tools The data status is tracked along this path and relevant information is available to the user in interactive reports and analysis The data confidentiality and access to data manipulation tools is handled under a tight role based security system FishFrame is an open source project The free licensing policy is described in the FishFrame License document found on the documentation page A full set of source code for the latest version can be obtained by contacting the FishFrame team Data FishFrame contains all fisheries assessment relevant data except data for establishing commercial tunings fleets The assessment relevant data include e Biological information of the landings obtained by sampling from market e Biological information of the cat
30. Haul validity is valid and sampling type 1s Harbour or sea Note that the area 1s converted from the uploaded area to grand parent area E g area 5b1 would be converted to 5 Discard fraction discard weight discard weight landing weight by Country Year Month Area StatisticalRectangle FisherySet Fishery and SpeciesCode 2 Cube and pivot table CS DiscardFraction Weight Simple average when pooling fractions from multiple strata e g several areas or fisheries CPUE Weight The processes that create the Discard fractions analysis based on catch weights are summarized below The input to the processes 1s the database tables containing the uploaded data while the output is the values in the pivot tables Stations are pooled and a CPUE is calculated by Country Year Month Area StatisticalRectangle FisherySet Fishery and Species That is the basis for the pivot report When drilling up in the pivot report grouping areas or time then a simple average 1s calculated 1 SQL view AS CS CPUE CatchWeight WithZeroObservations d Get catch weight effort hours for each station and with zeros for zero catches by Journey Station Country Year Month StatisticalRectangle FisherySet Fishery and SpeciesCode Where Haul validity is valid sampling type is Harbour or sea and Statistical rectangle has a value Get CPUE as Sum of Catch divided by sum of eff
31. TsT Grand Total Year Samples Samples Samples Samples Samples Samples Samples Samples Samples Samples Samples 1995 120 1996 586 and mm E Done Trusted sites Figure 38 A pivot chart displaying number of stations by year and country More information about pivot charts can be found at http msdn microsoft com office understanding owc Pivot maps A pivot map Figure 39 is a map based on the content of a pivot table To create a map Make sure that there are no fields on the column axis Make sure that there 1s only a geographical field area or statistical rectangle on the row axis 3 Press the Create map button NO m The pivot map features are e Zoom in 1 Select the gt button in the row of buttons upper right area 2 Move the cursor over the map the cursor is now appears as a 3 Click on the corner of the area that should be zoomed to 4 Hold the mouse button down while dragging to the opposite corner of the area the area is now marked by a black box 38 26 January 2007 5 Release the mouse button Zoom out 1 Select the El button in the row of buttons upper right area 2 Click on the position that is wanted as mid point for the new extension Zoom out to full extension 1 Select the El button in the row of buttons upper right area Pan 1 Select the button in the row of buttons upper right area 2 Click on the position that 1s wanted as mid point fo
32. a detailed stage 1 ooccccccnnnccoooononananccnnnnnnnnnnncnnnonononos 29 Acoustic survey data compiled stage 3 coccccccccnnnnnnnnononnoononcnnnnnnnnnnnnnnnnnnnnnos 29 Data action Data tie Sr atom 3555 end A T T S 29 Commercial nenes odiada 30 PECOUSTIC D o E itt OE e 30 Data UI e a eee 30 VFO HE o POPE OO N SEA 32 AROE EA A E E S O EE E E E 32 Ernie PE E AT T 33 E N 34 PP EE AE ee ee ee ee E E E 34 A A e II varleiddcadl cosnabatuscte 34 SECUN OY caret eiesarecie th tethal ene aaah A 34 G0 01 6 fe Serene mee note e ne penn Neer een A 35 A ss occ cee cinta EA E AOT A AE E dso casei ore 35 Generne compone mS seeni neen actos tice ob dad Gecise stu otleeacoicinveatdlak emote etteaes 36 Pivot Fa DCS Sion 36 PAC A E toto iene ceric was eee re oic tee eee 37 POEMAS a 38 AE E 41 SPIE fe E OPERA OA Pa een o ei eee Aen seen Ne me ced ane Mee ae nen Nan re ner 4 Future versions planning and bug handlINg cccccconoononoooonoonnccncnnnonononononononononanons 42 Errors ANA CLAS NCS iii 42 NELSON PADNIE cc 43 SA IEA E IN 43 Technical Stats 43 Recommended timing of workflow for assessment WG S d ooooonnccccccccnononcnnnnnnnnnonnnnanos 43 26 January 2007 Documentation of aggregation and calculation procedures oocccccccccnnnnnnnnnnnnnnnnnnnnnnos 43 CANUM Mean weight Age length Standardized length distribution 43 Processes creating Standardized length distribution SLD eee 46
33. aggregation procedures 6 Release This 1s a mandatory step After quality assuring the data they are released to further international work The data status is changed indicating that these data are now ready to be used in international work CS data The data 1s now included in the analysis Standardized length distribution Age length key Mean weight and Standardized CANUM 23 FishFrame Microsoft Internet Explorer File Edit view Favorites Tools Help Address amp http dmz web08 dfu min dk BalticSea FishFrame Select dataset to Data browser Reports Analysis Data action Info amp Help browse Releasing national data to use in assessment WG This may take up to 20 minutes Data successfully raised Landing statistics Aggregated AEE ER samplings gt Setting data status please wait Harbour Data status successfully updated Market gt The release of you data completed successfully Trawl surveys Trusted sites Figure 25 Test data from 2001 was released successfully 28 26 January 2007 Landing statistics 1 Upload first check Same as for Commercial samplings disaggregated step 1 please refer to that chapter above 2 Advanced check Same as for Commercial samplings disaggregated step 2 please refer to that chapter above 6 Release Same as for Commercial samplings disaggregated step 6 please refer to that chapter
34. ch discard as well as retained part compiled separately obtained by observers participating in regular fishery e Biological information of the catch discard as well as retained part compiled separately collected by the fishermen themselves e Official landings statistics by two different aggregation levels e Effort statistics by two different aggregation levels e Data from Acoustic surveys integrated scrutinized NASCs biological information from the catch e Scientific demersal trawl survey data on exchange format 26 January 2007 All biological information 1s basically on disaggregated form haul set for sea and harbour sampling and single sample level for marked samples Results from scientific demersal trawl surveys not acoustic surveys are copies of the data uploaded to the ICES database DATRAS The variables included in FishFrame should satisfy all data needs for most assessment models including fishery based assessment models For a complete list of variables included please consult the exchange format specifications found under Info amp Help gt Documentation Coverage It is the aimed that all countries having interests in the Baltic Sea and or the North EC member states and non member states ICES member states and non member states will upload data to FishFrame The more complete the data are the better use can be made of FishFrame For an updated overview of the data in the database please use the re
35. charts The diagrams have some functionality like zooming See the description of SVG diagrams in the chapter Generic components below The data in the OA diagrams Figure 19 are indicated by green points except for the outliers which are red and disabled data which are grey The yellow line is the regression Any point in the chart can be explored by single clicking it If the points are in a cluster then zooming in will make it easier to select the right one When selecting a point all its information pops up in a table in a new window Figure 21 The data point can then be disabled or enabled and a proper reason can be entered for documentation purposes If a data point is disabled it is not used in any further analysis If the data are satisfactory for further analysis then the button Click here to approve this stratum is pressed and the user is redirected to the overview table Figure 18 Outlier criteria Based on the data submitted to the database an outlier analysis is made to identify data points that could be erroneous Regressions are made on length weight and age length relationship The data are stratified by year country species area and quarter The length weight relationship is described by Weight a length The constants a and b are estimated by regression on the linear zed equation and the theoretical length weight curve are drawn Outliers are identified 1f they exceed 2 standard error of the
36. ct data set for second check 21 26 January 2007 Results of executing second check Selected data to check Year 2001 County Li Quarter 1 Area 24 The selected data did not pass the second check and is therefore not ready for further checks steps usage or processing Please correct your data nationally and upload a new corrected file Below is a list of the checks that the data did not pass Please refer to the documentation or look in Advanced check for more details Description gt Checksets second check CS General System checks in data action step 2 Description E Mandatory vessel information for mobile gear Vessel length Vessel power and Vessel size are mandato El Mandatory Mesh size for other gear than long lines Area Gear ClaimedFisheryActivityCategoryID Test data 7001 805 1 d OTB 076 DEF 105 1 110 Test data 7001 507 1 d OTB 0TB_DEF_ 105 1 110 Test data 2001 5085 1 d ETA TRE alla shall E E Aggregation level is Journey StationNo 999 Number of hauls gt 1 Figure 17 Result of the second data check The data did not pass all the checks Exact information is given so the input data can be corrected de iw 3 Approve Outlier analysis This is an optional step After selecting the country and year in the first dialog form then a table like Figure 18 appears The table gives overview over which strata that already have been
37. ctangles are summarized below The input to the 50 26 January 2007 processes 1s the database tables containing the stock estimates while the output 1s the values in the pivot tables In SQL stored procedure AS InterpolateMissingRectanglesBy Y earSpeciesStatisticalRectangle following happens l 1 Sum of numbers times inverse distance 11 the simple mean of total weights of all specimens times inverse distance 11 and the simple mean of total lengths of all specimens times inverse distance 2 1 11 111 1s divided by the total of the inverse distances completing the weightening This is then saved in the stock estimate database table 3 For the last step between the database table and the pivot table See step 4 in the documentation of Calculation of global abundance estimates mean weight and mean length above Note that this method equal weights data from different ship instead of weightening by milage The milage weightening is still intact within single ship data 51 26 January 2007 References Anon 2006 Report of the Ad Hoc Meeting of independent experts on Fleet Fishery based sampling EU report Commission Staff Working Paper 12 16 June 2006 52 26 January 2007 Appendices Appendix I Data request form The undersigned requests hereby permission to get a copy of the data specified below The undersigned 1s aware of and understand that data only are to be used as specified below and tha
38. d Catch W eight 10000000000000 099999999 atural Ke andatory value is missing Natural Key Range error Acceptable range for this field is between 0 and HL l eee eae A ps Range error Acceptable range for this field is between 0 and 10000000000000 0999999999 atural Ke Ex ange eos Aceeptable range for this feld is benween O andadas Natal ey 99999999 Range error Acceptable range for this field is between O and 9999 Natural Key E eT PRE VIT 99999999 Acceptable enumerationvalues Natural Key OX y enee emos Acceptable range fr this feld iz between Cand 999 atual Key 99999999 Range error Acceptable range for this field is between O and 9999 Natural Key o RT TA 99999999 Range error Acceptable range for this field is between 0 and 999 Natural Key 1 Trusted sites ca o e ca ea ca an ca nA ca o an ca r in co o nn cay xa ollo e e ca o les ca nn ca o a Sample Weight HI co eMe HI ngth co oao o nA ca o an 09 an co o nn ca o les 0 E O O O A eye AIET Wh S 00 Eh O 09 o pe ca o a co a Figure 13 The data check error report Values 154521 155054 155156 155470 155453 155666 155594 156074 156515 156565 156571 156572 Figure 14 Acceptable enumeration values report from the data check error report 20 26 January 2007 3 frmUploadFile Microsoft Internet Explorer
39. d chapter below 3 FishFrame Mozilla Firefox File Edit View History Bookmarks Tools Help lt a el y e ah http fidmz web0s dfu min dk NorthSea FishFrame Info amp Help FishFrame Security User name Password a aE FishFrame 4 3 North Sea Fisheries amp Stock Assessment Data Framework NB Your user account will be locked if you enter your password incorrectly 3 times If you wish a reminder of your password enter your user name and press Mail password and it will be emailed to you Mail password Figure 1 FishFrame web application before logging on Security FishFrame contains confidential data therefore only valid users with a secure set of logon credentials can access the data Information about changing user details like email and password can be found in the designated chapter under Functionality below Logon Log on using the username email and password given by the administrator It 1s possible to get a mail with the password if it has been lost Enter the email in the user name field and press the mail password button found in the lower part of the left frame Figure 1 If a wrong password 1s entered two times then a warning is issued and on the third attempt the account will be locked Only the administrator can unlock the account Every time the log on attempt is successfully the counter is reset so there is no risk for account lockout by mistyping
40. d data dd browser Figure 4 are used to navigate through the data while the actual data are presented in a table in the right frame A node in the tree is expanded by clicking the and collapsed by clicking the When clicking on the label text the node is toggled expanded or collapsed and the data represented by the node is shown in the table The table is a simple table The functionality of a simple table is described in the designated chapter below Acoustic surveys Trawl surveys Figure 3 Selection of data browser 26 January 2007 FishFrame Microsoft Internet Explorer File Edit View Favorites Tools Help Commercial Sea Data browser Reports Analysis Data action Info amp Help Sampling Y 5 S Z gt Gear Validity CatchWeight SampleWeight NoMeasured Length Meas Number 2000 raso e ommen ft Denmark Estonia discar 080050 8088000 Finland Germany 2004 2003 1999 E 1996 E Journey 4 E Stations Station 1 E Station 2 E discard landing Station 3 Station 4 1995 Latvia Lithauania Poland Russia Sweden Test data 900 f0 e fesom 2 a20 12 500 e esomfen f2 o0 i2s00 J6 oomme ja Telele 2 a lor RIEJA ejejeje fe E 2 000 12000 esoo fe aiomme gt 12000 fi2soo fas omae y 12000 esoo fe 330mmfem p 12000 raso fas O mon fio asooo farso faao 350amlem 2 z300 475 000 fao asome 2 azoo 475 000 faao aomen 3 a300 farag
41. d fraction pivot charts pivot maps or simple tables Mean Weight Standardized CANUM The functionality in these reports is Figure 6 Selection of analysis 12 26 January 2007 described in the designated chapter below Commercial Age Length Special See description in designated chapter samplings Weight below outlier analysis Age Length Pivot table Age length key Fractions for each relations and chart age for a given length Row totals are always 1 Includes age regressions per default but this can be altered and explored by modifying the regression dimension For aggregation and regression details see designated chapter below Standard Pivot table Standard length distribution length distr and chart The normalized length distribution For aggregation details see designated chapter below Species Pivot table Species distribution in sea harbour distribution in map sampled catches Individual catches sampled and chart are standardized raised to 1 tonnes catches gt In of total catch Samples with validity numbers code 4 1s excluded from this report Multiple samples within same stratum are aggregated as an average 1 tonnes catch Each sample is given equeal weighting in the average Zero catch for a given species in a given stratum affects the average 1f 1 The species is represented in a stock living in the area ICES sub area 2 There is sampled catch of any species within the same Stratum
42. e data by that field Clicking more that once on the same field reverses the sorting direction e Dump data into MS excel Right click on the table and select Export to MS Excel e Copy to other programs Select manually the data in the table and copy or drag drop them into another application A FishFrame Microsoft Internet Explorer File Edit View Favorites Tools Help Address http dmz web08 dFu min dk BalticSea FishFramejdefault aspx Lin Commercial Sea Data browser Reports Analysis Data action Info amp Help Sampling Category Size Month Day Gear Validity CatchWeight SampleWeight NoMeasured Length Meas Number 2 Danmark Dewa o i p omh pao po h Pomm awumey 1084 cara ofr p Jorsh ozo oao j faomea Ji Seena Laos o h fe foh faeo fisso 7 _ 4sommlen Jr sstetion2 mae o i fo Jorsh 194000 haoo E forom P Sm Landng o 1 fomejr haoo haoo 37 feom 1 avid Emane Jo fi gt one r 194000 fiac a7 Sooma Jr ehippoaioss Tandag Jo 1 fo omh 194000 hao gt i eMicrostom adne 0 1 9 forhi fisa 164000 Scophthalr ea H o Ala A ol o Solea vulgi OTB 1 a Journey 1085 Journey 1087 orh orhi orhi J w o o A ca o El Journey 1088 194 000 164 000 El Journey 1089 El Journey 1090 194 000 164 000 194 000 164 000 p o 37 37 OF 3y S EX ae 37 mm mm mm mm mm mm mm mm E Journey 1091 E Journey 1092 Journey 1093 Back Forwarc El Journey 1094 E
43. for LS data 0 1 ma Historic Help Document on version 2 0 0 2 MB ICES WGBFAS Paper 2003 0 6 MB Poster at color of the oceans conference Bruxelles 2002 0 9 MB Poster at ICES ASC Tallinn 2003 0 9 mB FAO Paper on Analysis server in FishFrame 2003 2 9 MB FAO paper on XML in FishFrame 2003 0 1 MB Figure 33 The documentation page 33 26 January 2007 IT Support In this section there are three pages with guidelines for setting up the computer to use different features in FishFrame e Help on reports This is the pivot based reports and analysis e Help on charts This is the charts used in the outlier analysis Misc Info amp Help Misc All security features and contact Refresh information is found under Misc Figure Moe ee Security 3 4 Change password Contact New user Links Refresh Activity report This navigates all parts of FishFrame to the ii beginning as 1f the user had just logged on Use this if the menu item that is needed is hiding under an element on the screen the menu goes underneath elements such as drop down boxed buttons and pivot tables Figure 34 Selection of miscellaneous functionality Security Update user details The name and email address can be changed on the form depicted in Figure 35 Administrators can also change the country and role User First name E mail User Role Country Figure 35 Update user details form 34 26 January 2007
44. formation about pivot tables can be found at http msdn microsoft com office understanding owc Pivot charts A pivot chart Figure 38 1s a chart that is driven dynamically by the data in an accompanying pivot table It shares all the features of a pivot table The functionality is described in the MS Office chart component help that 1s being reached by pressing the icon on the upper right corner of the chart The help document is well structured and gives quick access to specific info through a navigation tree or a search 37 26 January 2007 A FishFrame Microsoft Internet Explorer AE ar Fie Edit view Favorites Tools Help Address E http dmz web08 dfu min dk Balticsea FishFramej v Go Links A Select dataset to Date browser Analysis Data action Info amp Help Misc browse Stations PivotTable Field List Drag items to the PivotTable list CS_Samples Totals Samples Aggregation Level A Area Area Quarter Sampling Type Fishery Set Y Fishery Y Gear Country All All All All All All Day Series Fishery 3 Fishery Set Fishing Time 3 Gear 3 Haul Validity Main Fishing Depth Main Water Depth 5 Mesh Size Month UA A Rowarea MB Ba 2h 4l el a OE 0 214 88 Area y Quarter y Sampling Type Fishery Set Fishery Gear y All All All All All All Country y DEN EST_ FIN GFR LAT uT PoL RUS SwE
45. hat only gives the option Enumeration while Year is a numerical which gives the options Value and Range Select the operator This can be Equal to Not equal to Is null or Is not null Null means nothing or missing Select the values to compare with In our example Denmark is clicked in the list and 2000 is entered in the field Click on the Add selection button Step 1 Step 2 Step 3 Target Dataset checks Information Edit target dataset Dataset name Danish market 2000 Specify target data All Countries A Belgiurn Denmark England Estonia Finland France Values Germany Ireland Latvia Lithauania Netherlands Norway Poland Russia HH Onl Oca ES O Is Null O Is Not Null Field Country Type Enumeration lt Add selection List of added restrictions tecor Comparator Value s CA r 2000 t Country Denmark Eat Beet cs Esa Dette e SamplingType Market Figure 45 Defining the dataset The name of the dataset can be entered in the filed at the top of the page Finally the dataset definition can be saved by clicking on the Save dataset button Step 2 in the wizard is to define the checks and step 3 is to give the check set a title and a description optional Check creation Clicking on the New check button opens the check c
46. he exchange format converter reads the cell contents as it appears in the formatted form Do not add rows columns or calculated cells or do it in a separate copy that will not be fed into the converter program Exchange format converter 30 26 January 2007 A program that can convert data in excel sheet version 27 September 2005 to data in XML upload format can be downloaded and installed here Figure 27 It 1s important not to change anything else than the values in the cells containing abundance milage fraction mean weight and mean length The format of these cells should remain untouched as numbers with the preset decimal places If the format is changes it will affect the precision and rounding in the conversion To avoid this it is recommended that all data are copied into the sheets using Edit gt Insert special gt Values from the excel menu Notice that XML is the primary exchange format not the excel sheet The description of the XML exchange format is in a separate document that can be downloaded from the documentation page under Info amp Help The converter program has been developed mainly to convert old data files so they can be uploaded The program does not handle all sorts of incorrect excel sheets in a very user friendly way it will crash if the file is wrong If it should crash then make sure that it is the right version of the excel sheet and that there has not been any changes to the
47. he form in appendix I giving detailed descriptions of the data needs and the use of data Data can normally only be used by the scientific community for scientific purposes Only national editors and administrators can do such download While most of the data are visible for all users in FishFrame some are confidential The confidential data are masked by for users from other countries Data considered confidential in FishFrame are e Longitude and latitude of stations of commercial samples sea sampling 26 January 2007 e Length frequency data from commercial data The exact number at length and catch weight is masked rest 1s visible e Unallocated and area misreported landing statistics Software and hardware requirements The client side requirements are listed below while the server side setup is documented in the developer s manual See also the FishFrame Tech note on the documentation page e Web browser tested on MS Internet explorer 7 0 Mozilla Firefox 2 0 and Opera e Pop up windows enabled e MS Office XP Web Components part of full office XP installation This 1s to be able to use the pivot tables and charts e Adobe SVG viewer free software This used in the outlier analysis e Adobe reader free software or similar to read documentation in PDF format e Internet access 30 Kb is sufficient except for tutorials more is nice Pivot tables and outlier analysis will only work in Firefox
48. here year ship and species match as well as BiolSubArea StatRect 1f it is present 3 An average weighted by milage of 1 Total number calculated as abundance fraction milage TotalMilage to get it per age stock and maturity 11 Total weight calculated as mean weight multiplied abundance fraction milage TotalMilage 11 Total length of all specimens calculated as mean length abundance fraction milage TotalMilage is then saved for all ships except where ship TST test data Measures zeros are not stored All relevant rectangles are presumed to be covered in the survey if holes exist then they will be interpolated later in the interpolation step 4 The aggregation level is selected in the pivot 1 Abundance is then calculated as a simple sum of the total number 11 Mean weight is then calculated as the sum of total weights divided by the sum of the total weights Note that the outcome is weighted by the numbers when aggregating rectangles and ships etc in contrast to a simple average i Mean weight is then calculated as the sum of total weights divided by the sum of the total weights Note that the outcome is weighted by the numbers when aggregating rectangles and ships etc in contrast to a simple average Interpolation of global abundance estimates mean weight and mean length The process that estimates missing total stock estimates by interpolation of available measured data neighbouring 8 re
49. l Recommended timing of workflow for assessment WG s It is recommended to set two deadlines one well before the WG meeting and the other just prior to the WG meeting Deadline 1 All data should have passed step 6 They are released and can therefore be used by other countries to apply estimate strata without data 2 All data should have passed step 8 All data are complete and the countries have evaluated the apply estimation methods and the results hereof The data set is then ready for the stock coordinator to make a first exploratory run in the assessment model software on the first day of the WG meeting or even in the days before The stock coordinator can also start the assessment with a sub group meeting where the countries present and discuss their choices for apply estimation methods in plenary Documentation of aggregation and calculation procedures CANUM Mean weight Age length amp Standardized length distribution The processes that create CANUM and mean weights are summarized in Figure 42 and Figure 43 The input to the processes on Figure 42 is the database tables containing the uploaded data while the output is the input to the processes on Figure 43 26 January 2007 43 Data can be explored in several steps see the Analysis chapter under Functionality above Tbl StandardizedCANUM Tbl MWML sp oP PopulateMVWML PopulateStandardizedCANUM FOP UDF MeanWeight UDF MeanLe
50. m acoustic survey Estimates successfully calculated Data status successfully updated gt The process completed successfully Figure 26 Global estimates for Herring in the 2006 HERAS survey was calculated successfully Note that measures zeros are not stored All relevant rectangles are presumed to be covered in the survey if holes exist then they will be interpolated later in the interpolation step International compilation gt Interpolate missing rectangles Select the year species and rectangle that should be estimated by interpolating the values from available data from the neighbouring 8 rectangles Data action Tools All the available tools and test data that can be used to assist the work done under Data maintenance and Data integration can be found under Data Action gt Tools Test data This section contains all the data used in the structured acceptance test The tests and usage of the test data is described in the test document that can be found on the documentation page Excel exchange format This is the excel sheet previously used to submit data to the coordinator John Simmonds The sheet has existed in several versions through the years The version that can be downloaded here is the version from 27 September 2005 Notice that 1t is important to keep the formatting since this reflects the formatting in the upload format e g abundance as numeric with 4 decimal places and t
51. ngles overlap two areas but in the calculations they are being treated as belonging to a specific area Area gt Area Simple table The relational hierarchical structure to area of the areas Area gt Simple table The definitions of which areas that is Adjacent areas Simple table List of codes that can be used for adjacent to which 11 26 January 2007 Biological Biological areas in acoustic data subareas Area gt Sub Simple table List of sub statistical rectangle Statistical quarters of a rectangle Rectangle Species Simple table List of species codes Acoustic Simple table List of acoustic species groups species codes to be used in acoustic data Species groups Stocks Simple table Definitions of stocks and pivot table and map Simple table Sub stock codes and their definition Simple table Maturity scale codes scale Table 2 Descriptions of reports A Analysis Data action nalysis Commercial samplings 2 Age Length Weight Outlier E r A E analysis All output that require analytical processing Data integration ELA e i Age Length Relations is found under Analysis this includes Standard Length Distr input to stock assessment models made Species distribution in during data action step 10 WG stock sampled catches release These reports are described in CPUE Table 3 Most of the reports are pivot tables Discar
52. ngth Tbl Fact_ALK Tbl pon IAS PopulateRegression SP PopulateALK Tbl SLD SP PopulateSLD UDF MergeHHWithHL Box0 ByStation UDF k strGetFishery Tbh Tbl Tbl SMALK Station LF Tbl L_Species Tbl L Species Tbl L Statistical Rectangle Figure 42 Overview of processes that calculate standardized CANUM mean weight standardized length distribution and age length keys The labels refer to database objects like SQL code or data 44 26 January 2007 tables The labels are prefixed with a legend Tbl Table UDF and no label User defined function and SP Stored procedure Tbl CANUM SP PopulateCANUM Tbl StandardizedCANUM SP PopulateAl1StandizedCANUM EstimationSourcesUsing SP GetWeightedM eanNumberPe ri000T Tbl StandardizedCANUM EstimationSource eo SP PopulateAllStandizedCANUM EstimationTargets SP InsertStandardized CANUMEstimate Tbl 4 StandardizedCANUM EstimationTarget Figure 43 Overview of processes that calculate CANUM The labels refer to database objects like SQL code or data tables The labels are prefixed with a legend Tbl Table UDF and no label User defined function and SP Stored procedure The processes called user defined functions and stored procedures are where the aggregation and calculations occur They are documented process by process below Following abbreviations are used Y
53. nis Jansen 14 01 2006 Marked samplings checks Teunis Jansen 14 01 2006 North sea cod checks Teunis Jansen 14 01 2006 Figure 44 Entry point to the advanced data check module The list of available check sets Check set creation Clicking on the Create new check set button opens the check set creation wizard Step 1 in the wizard is to define a filter The filter defines the target data set 1 e the dataset that all the checks will be executed upon Clicking on the New dataset button opens Define new target dataset page On this page several criteria can be added one by one In our example Figure 45 Country Denmark has been added 54 26 January 2007 and Y ear 2000 is about to be added by clicking on the Add selection button This type of page is typical and appears on all pages where some sorts of criteria are to be created The functionality is described here so please refer to this text later on in the guide To add criterions go through following steps refers to middle part of Figure 45 l Select record type HH HL or CA HHs can be combined with HLs and CAs while Criteria concerning HLs and CAs cannot be combined in the same check set Select field in dropdown listbox Select type of comparison This can be Value Range Enumeration a list of predefined values or Formula depending on the type of field selected In our example Country is a code and t
54. oo faao asoman a azoo 475000 fao fomaem 9 fan ng fo ji fa omy ECO CO CE EC E M fining 0 1 Jer lomai _ 3103 000 475000 CC CC 22 Back Forward amp 5 oO D R ala E o R a B E M B d H UUDEN 3 8 3 8 3 8 8 8 8 8 8 3 8 on pal E o am o om os on EM e o 5 lla 3 Trusted sites Figure 4 The tree based data browser Reports Reports Commercial samplings All output related to overview of the content Analysis of the database and reports that do not require much analytical processing is found under Reports The reports are described in Table 2 Most of the reports are pivot tables pivot charts pivot maps or simple tables The functionality in these reports is described in Samples Landing statistics Length measures Effort statistics Otolith measures Trawl surveys Datras Length freq data gt Strata definitions gt Data status Country data status in prep Country speciffic settings Figure 5 Selection of report 26 January 2007 the designated chapter below Commercial Samples Pivot table The number of stations samplings map Remember to select a fisheries set and chart otherwise the number will be multiplied by the number of fishery sets Length Pivot table The number of length measured measures map individuals and chart Remember to select a fisheries set otherwise the number will be multiplied by the number of fishery sets Otoli
55. ors were found View error report The error report 1s specific for each check An example of a key value consistency error report can be seen in Figure 17 26 January 2007 10 a duplicate record error report in Figure 11 and a data check error report in Figure 13 The error reports are explained here Key value consistency error report Figure 10 The given example is from a data file with a HH record with two erroneously HL records The country field in the HH record is set to TST while the first HL has XXX and the second has an empty field Both errors are visible on the error report The error report states in the header row that the first error is from a record type HL It also gives the location in the file ASCII line parent is 1 so this is the HH record in line 1 and the ASCII line child 1s 2 so this 1s the HL record in line 2 Below the header row there is a table with all the parameters that should be alike in the HH and HL The error in the country field in HL is easily spotted in the table A frmUploadFile Microsoft Internet Explorer Sele T Fie Edit view Favorites Tools Help sack Qj x E fl ye Search Address El http l idmz web0 dfu min dkiBalticses Go Links Y Record Type ASCI line parent ASCI line child Record Type HH HL ST pox station 4 Trusted sites Figure 10 The key value consistency error report Duplicate record error repor
56. ort by Country Year Month Area StatisticalRectangle FisherySet Fishery and Species Where Area 1s derived from StatisticalRectangle Note that the area 1s converted from the uploaded area to grand parent area E g area 5b1 would be converted to 5 2 Cube and pivot table CS CPUE WeightPerHour Simple average when pooling fractions from multiple strata e g several areas or fisheries 49 26 January 2007 Acoustic survey data Calculation of global abundance estimates mean weight and mean length The processes that create the total stock analysis based on stage 3 data abundance data AB and stock detail data SD are summarized below The input to the processes 1s the database tables containing the data that 1s either uploaded or calculated from stage 1 data AA and AF while the output is the values in the pivot tables 1 3 happens in the SQL stored procedure database server PopulateStockEstimateB y Y earSpecies following happens while step 4 happens in the pivot table analysis server client pivot component l a Abundance and milage are pooled from all SubStatisticalRectangles by Year ShipCode SpeciesCode StatisticalRectangle and BiologicalSubArea b Fraction mean weight and mean length are averaged from all Year ShipCode SpeciesCode StatisticalRectangle BiologicalSubArea Stock Age AgePlusGroup Maturity MaturityDetermination 2 Data from 1 a and 1 b is combined joined w
57. porting facilities available in FishFrame Stratification The national data collection schemes are to a wide extent stratified on common definitions These definitions include strata based on e Time periods month or quarter e Areas division sub division statistical rectangle e Fishing Activity Category The Fishing Activities are based on the definitions finalized during the Nantes Work Shop in June 2006 anon 2006 The activity stratification 1s hieratic constructed The Fishing activities resemble the so called Regional Level level 6 which is based on gear type mesh size and regulation constrains For a detailed description of the Fishing Activity system see anon 2006 and for a list of criteria defining the different Fishing activities please see Reports Stratifications Fisheries in the FishFrame menu Data policy The national data in FishFrame is owned by the national institutes Each national institute updates their own data when changes are made in the data source the national database containing the raw data FishFrame is a datawarehouse that only contain copies derived outputs from the national databases Access to viewing and analyzing other countries data in FishFrame does not entail permission to download copy or publish dis aggregated not own country data outside FishFrame Such permissions can only be granted by each national institute The request can be put forward by using t
58. r the new extension Identification 1 Select the R button in the row of buttons upper right area 2 Click on an area 3 The information about the selected area is then displayed below the map Change colour on land areas 1 Select the wanted colour in the Country drop down box Change colour scale on sea areas 1 Select the wanted colour in the Values drop down box Save or copy map as image 39 26 January 2007 e Right click on the image and select save picture as colour in the Values drop down box e Drag and drop the image into e g word F PolygonMap Microsoft Internet Explorer Sres File Edit View Favorites Tools Help qe Address E http fdmz web08 dfu min dk BalticSea FishFrame Data GI5 PolygonMap asp strMapType EJ so Links Samples by Area qa R Legend 36 454 454 872 Mera 1230 1290 1708 M i703 2126 2126 2544 Ml 2544 2964 Values Red Country Figure 39 Pivot map as it comes from the pivot table Commercial samples where area has been placed on the row axis default 40 26 January 2007 3 PolygonMap Microsoft Internet Explorer AE File Edit View Favorites Tools Help Qe Address E http fdmz web0s dfu min dk Balticsea FishFrame Data GI5 PolygonMap aspx striapType Bed Go Links Samples by Area aAA Legend 36 454 454 872 872 1290 Ml 1290 1708 Mos 2126 2126 2544 Moss 2964 Values County
59. re 19 Length weight outlier analysis for Denmark 2003 Q1 Cod and area 21 The length weight OA Figure 19 consists of up to 8 diagrams one for discard and one for each size sorting of the landings No diagram is presented if less that three data records are present e g for landings and size sorting 1 in Figure 19 An example of outliers can be seen in Figure 20 the three outliers are easily noticed due to their red colour Disabling one the 460 g 57 cm cod on Figure 21 makes the OA to be rerun without this point Figure 22 Since this decreases the standard distribution 1t makes more points turn into outliers The disabled point is greyed out 24 26 January 2007 Lengih welght relation on catchcategory Landing and sizecategory 5 2000 Ca Weight 1 c L 200 300 400 500 500 Length mm Figure 20 Length Weight outlier analysis diagram with three outliers 2 ManageDataPoint Microsoft Internet Explorer Eto fx Denmark 2003 Gadus morhua Journey StationNo 9 Quarter IO II Se E a Grident NN y Number O l o IndividualMeanWeight 460 Disabled No _ DisableReason Disable data Figure 21 Pop up window with a single data point CA record from OA and the functionality to manage it 25 26 January 2007 Length weight relation on catchcategory Landing and sizecalegory 5 2000 Weight 2 i ia HKI 300 400 SC 600 Length mm Figure 2
60. re inserted they might overwrite old data for the same stratum The overwrite rules are Commercial sampling By Year Country Journey Landing statistics By Year Quarter Country and Species Effort statistics By Year Quarter Country and Species Acoustic data aggregated stage 3 By Survey Year Ship and species Acoustic data dis aggregated stage 1 o Fishing By Survey Year and Ship o Acoustics By Survey Year and Ship 3 FishFrame Microsoft Internet Explorer File Edit View Favorites Tools Help Address El http dmz web08 dfu min ck BalticSea FishFrame Select dataset to Data browser Reports Analysis Data action Info amp Help Misc browse File upload completed Key value consistency check complete No errors were found Data successfully converted to XML format Bal Doublicate record check complete No errors were found samplings Data check complete No errors were found Sea E gt Data from Test data 2001 can now be inserted into FishFrame do you Market wish to proceed Yes Landing statistics Aggregated Trawl surveys Datras Trusted sites Figure 9 All checks have been passed without errors If errors are detected in the file in any of the checks then the process will stop immediately and the feedback line will state the number of errors found which check that found them and provide a link to a detailed error report e g Data check complete 78 Err
61. reation wizard Step in the wizard is to define a filter The filter defines the subset of the target data set that this 55 26 January 2007 check will operate on On this page several criteria can be added one by one In our example Figure 46 SpeciesCode Gadus morhua and Age 2 has been added Step 1 Step 2 Step 3 Target Dataset Checks Information Check input Step 1 Step 2 Step 3 Define subset of target dataset Define data check Check information Which subset of data do you want to check OHH OHL Oca Equal To O Not Equal To Field Age v value a O Is Null Type Value O Is Not Null Add selection List of added restrictions teco Comparator Value s CA SpeciesCode Gadus morhua Figure 46 Defining subset of dataset Step 2 in the wizard is to define the criteria for the check Add the criteria for what regarded as being correct the system will then pick out and show the records that do not fulfil these criteria In our example we want to check that the length of 2 year old cod is within reasonable limits We therefore add the criterion LengthClass within range 200 500 mm Figure 47 Step Step 2 Step 3 Target Dataset Checks Information Check input Step 1 Step 2 Step 3 Define subset of target dataset Define data check Check information Set up conditions for new check Specify a
62. s distribution area are excluded Marked sampling data are excluded as well The fraction of the catch that was discarded Calculated as a simple mean discard weight fraction of the catch weight Zero landings and zero discards are included it is therefore crucial to select fishery and dataset with care the dataset could include stations where only cod was reported thereby indicating a false zero catch of other species Mean weight in grams by age group Includes weight regressions per default For aggregation and regression details see designated chapter below The mean weight can also be calculated by lengthclass if this field is dragged onto one of the axes If length class and age are on the axes then the report displays the basic mean weight based on CA records not weighted by catches Standardized catch in numbers by age group Standardized so that it is in 1000 specimens per 1000 tonnes Data integration Pivot table map and chart Acoustic Pivot table surveys gt map Total Stock and chart Estimate abundance Acoustic Pivot table surveys gt map Total Stock and chart Estimate weight Acoustic Pivot table Surveys gt map Total Stock and chart Estimate mean weight Acoustic Pivot table surveys gt map Total Stock and chart Estimate mean length Table 3 Descriptions of analysis Data action Data mainenance 26 January 2007 landings This table can be
63. set definition from another check set Figure 51 The import dialog screen Figure 52 displays all the check sets available for import Single checks can also be picked out and imported from other check sets This is done by clicking on the Import check button on the step 2 page Figure 48 The import dialog screen will then display all the checks available for import Data browser i i Data action Info amp Hel Step 1 Step Z Step 3 Target Dataset Checks Information PARRES i J Check Set Creation Module Define target dataset Avallable dataset definitions Wo datasets defined New Dataset Import full check set Import dataset definition Figure 51 Check set creation page 58 26 January 2007 Show All Check Sets Show Your Check Sets Awallable Check Sets Teunis Cod age length relations 16 01 2006 CS Jansen Second check CS General system checks in data Teunis 23 03 2006 cs action step 2 Jansen Second check CS Market sampling System checks in data second 26 03 2006 CS action step 2 check Second check CS Sea and Harbour System checks in data Second ee ome sampling CA action step 2 check eee s Second check CS Sea and Harbour System checks in data Teunis Pe E sampling HH HL action step 2 Jansen eee Figure 52 Select check set for import Security Who can do what A check set is owned by the creator Other users can view and run the check set but only the creator can edit i
64. soft Internet Explorer SEE a File Edit View Favorites Tools Help gt Address http dmz web08 dfu min dk BalticSea FishFrame v Go Links Commercial Data browser Reports Analysis Data action Info amp Help Misc Market Sampling HD k On Tutorials E Test data E 2001 T z SampleTrip 804 reeview dataview 3 0 mB E SampleTrip 805 Upload amp validation not available yet Samples E SMALKs Approval outlier analysis disabling of data amp use of charts s s me Clupea harer Release 1 9 ma n Smi Platichthys fi Download 2 6x me El 2000 Analysis Reports 6 7 ma 1995 Creating Maps not available yet security not available yet lt gt E Trusted sites Figure 32 The tutorials page where film clips can be downloaded Documentation The documentation is in pdf format which can be viewed in the free adobe reader Click in the link to open or download the document File Edit view Favorites Tools Help 3 FishFrame Microsoft Internet Explorer Sees af Address 4 http ch itto3 FishFrame FishFrame v Go Links Select dataset to Data browser Reports Analysis Data action Info amp Help Misc browse Landing statistics Docu mentation Aggregated Commercial Updated samplings gt AS User maual 1 0 ms Harbour Exchange format specification 0 1 me Market 3 Test documentation 0 1 me Trawl surveys XSD schema file for CS data 0 1 me OS xSD schema file
65. t Figure 11 The given example is from a data file where the two first lines are L1 aggregated landings that are identical in all the key parameters As it can be seen in the report by looking at the two columns named ASCII line number the errors were found by comparing line 1 and 2 The identical natural key can be seen in a special sub report Figure 12 by clicking on the Natural key link in the rightmost column This is 18 26 January 2007 important information for finding the error if the upload format used is XML but also useful for CSV file uploading frmUploadFile Microsoft Internet Explorer File Edit View Favorites Tools Help Address Record Type ASCII line number ASCI line number Compared Against Natural key PA Trusted sites Figure 11 The duplicate record error report 3 frmUploadFile Micro Sel File Edit View Favorites T Qe Address E http dr Eco Links gt e oo NENE OTE MO Figure 12 The natural key report from the duplicate record error report Data check error report Figure 13 The given example is from a file with 24 errors of various kinds They are all of the types out of range invalid value or missing mandatory field See the first line in the report here it 1s stated reading columns from left to right that the error 1s 1n the field SpeciesCode the record type HL record number 1 this is the first HL record Journey number 806
66. t Other users can import the checks into their own editable check set 59
67. t data must be deleted within a year after the date of submission of this application The administrator of BaltCom must be informed when data are deleted The data must never be handed over to a third party What data are requested Country Y ear s Sub division s Species What information are requested Aggregation level Raw data or Aggregated on Journey Statistical rectangle Sub division Fish stock Other What shall the data be used for Who are requesting the data Date Signature 53 26 January 2007 Appendix II The guide to the advanced data checker module Overview With this module it is possible to assess the data quality by defining data checks and running them on subsets of the data This guide will introduce the functionality by creating an example check set step by step The example will set up checks on Danish market samplings from year 2000 and check if cod age 2 and 3 has proper lengths Terminology A Check set consists of 1 Target dataset definitions a filter 2 Checks 3 A title and a description A Check consists of 1 Subset of target dataset definition a filter 2 Check definition some criteria 3 A title and a description Check sets The first page that meets the user is the list of check sets Figure 44 Advanced Validation Module Show All Check Sets O Show Your Check Sets Awallable Check Sets SE a a ESE TISSN Herring stock checks Teu
68. tatistics 10 26 January 2007 number of trips These are the efforts uploaded as El and E2 format Data status Pivot table The average of the last successfully and map completed step Acoustic survey Detailed data Pivot table The Abundance and milage stage 3 gt map Abundance and chart Detailed data Pivot table The fractions mean weight and stage 3 gt map mean length at age maturity stock Stock detail and chart fractions Samples Pivot table The number of stations map and chart Length Pivot table The number of length measured measures map individuals in the representative Trawl survey and chart subsamples Otolith Pivot table The number of age determined measures map individuals and chart ICES tools amp Various Various web based reporting and info mapping services available from ICES and sister institutes All presents the same trawl survey data found in FishFrame and DATRAS Strata definitions Simple table List of country codes Acoustic Simple table List of acoustic survey codes surveys Fisheries Simple table List and definition of the fishery codes Fishing Activity Categories Simple table List of Gear codes Survey gear Simple table List of gear codes for gear used by survey ships Area gt Stat Simple table The relations between statistical rect To area rectangles and areas Some statistical recta
69. th Pivot table The number of age determined measures map individuals in the representative and chart subsamples Remember to select a fisheries set otherwise the number will be multiplied by the number of fishery sets Length freq List of length groups without data without corresponding individual age corresponding Simple table distribution age Country year and quarter are selected before the report is created Length freq List of length groups without data without corresponding individual weight corresponding Simple table Country year and quarter are weight selected before the report is created Data status Pivot table The average of the last successfully and map completed step Raising Simple table The settings to be used when compiling data These settings will be country stock and year specific options Notice these settings are currently under evaluation and are therefore not implemented in the compilation procedures Pivot table The sum of official landing statistics map not including the information about and chart misreporting These are the landings uploaded as L1 and L2 format and map completed step Effort statistics Effort Pivot table The sum of number of trips Statistics map Sum of Number of sets hauls Fishing and chart time soaking time and kW days can be pulled into the table instead of Landing statistics Landing s
70. used to get the discard by landings Remember to select a fisheries set otherwise the number will be the sum of the values for all fishery sets For aggregation and regression details see designated chapter below Catch in numbers by age group landings as well as discards raised data as well as apply estimated data Remember to select a fisheries set For aggregation and regression details see designated chapter below Number of specimens in the total stock estimate All zero values measured and unmeasured are not shown in this report or they appear as empty cells Weight tonnes of specimens in the total stock estimate All zero values measured and unmeasured are not shown in this report or they appear as empty cells A zero in this report indicated a weight rounded off to O tonnes 1 e less than 500 Kg but more that 0 Kg In Grams Mean weight of specimens in the total stock estimate In mm Mean length of specimens in the total stock estimate All the work steps in the data flow from uploading raw data data screening and data handling 1s found under Data action gt Data maintenance Data action Info Help Misc Data maintenance gt Commercial samplings 1 Upload amp first check Data integration Landing statistics 2 Second check Tools gt Effort statistics 3 Approve Acoustic surveys 4 Advanced check 5 Confirm raising options Release 26 January 20

FishFrame 4.3 User manual

Contents

Download Pdf Manuals

Related Search

Related Contents