Software Development in Agricultural Computer Science: Status and Perspectives p. 1
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1 Software Development in Agricultural Computer Science: Status and Perspectives Eildert Groeneveld Rodica, April 15th Institute for Animal Breeding, FAL, Mariensee Software Development in Agricultural Computer Science: Status and Perspectives p. 1
2 utline 1. bjectives in Computer Science in Agriculture 2. The Framework 3. Thesis 4. the so what? projects 5. examples of dead-end developments 6. possible solutions and development paths. examples of the S development model 8. pen Source development 9. outlook Software Development in Agricultural Computer Science: Status and Perspectives p. 2
3 bjectives in Agr. Computer Science Facilitate IT solutions in Agriculture quick development and implementation of new solutions requires research and development essentiell framework: cumulative mode of development leads to accelerated development is based on original research progress resulting from the general development in SW/HW does not count Software Development in Agricultural Computer Science: Status and Perspectives p. 3
4 The Framework Information processing in Agriculture: in the scientific area: design and evaluation of experiments development of computing algorithms well defined inputs -> problem solution -> utput (IP) Software Development in Agricultural Computer Science: Status and Perspectives p. 4
5 The Framework ff on farm area: Information processing in Agriculture: solutions to local problems: optimization of feed rations (IP) area of global information: collection, management and evaluation merging data from various sources: lots of land, soil samples performance recording: milk, growth, reproduction across farms: aggregation of data from many sources (InfoSys) in animal production: BLUP genetic evaluation Software Development in Agricultural Computer Science: Status and Perspectives p. 5
6 The Framework fff Information processing in Agriculture: animal breeding, crop production, agricultural engineering, agricultural economics different kind of systems (IP InfoSys): IP: production of data -> problem solution->decision->throw data away InfoSys: integrated data utilization: breeding, milk recording, labs, AI, utilization of the WEB, networking of farms Software Development in Agricultural Computer Science: Status and Perspectives p. 6
7 IP vs InfoSys conceptual differences: IP: simple well defined inputs complex processing but usually in a simple program environment (F90, C,...) well defined outputs processing layer is disconnected from the inputs Software Development in Agricultural Computer Science: Status and Perspectives p.
8 Examples IP statistical procedures through use of packages (SAS, R...) analysis of inbreeding (SW) computation of BLUP (SW) estimation of covariance components (SW) etc. Software Development in Agricultural Computer Science: Status and Perspectives p. 8
9 IP vs InfoSys ff InfoSys: conceptual differences: many sources of data from different origin/systems as a result: different SW as a result: different operating systems includes data transfer different data structures among different problems (organizations) everything is connected with everything Software Development in Agricultural Computer Science: Status and Perspectives p. 9
10 Examples InfoSys gene banks in plants and animals e-commerce Systems query and information systems integrierted data bases: plants/animals many components: Webserver, DBMS, programming languages, S Software Development in Agricultural Computer Science: Status and Perspectives p. 10
11 Thesis IP: 1. many developments with large impact: DFREML, MTDFREML, ASREML, VCE, ABTK, PEST InfoSys: 1. many developments that solve NE problem 2. are thus irrelevant for the industry as a whole: 3. the So What? projects. Software Development in Agricultural Computer Science: Status and Perspectives p. 11
12 The Problem: An Example WCGALP Australia in Section : Computing Techniques in Animal Breeding total of 26 contributions 1 IP 4 InfoSys: NZ sheep improvement scheme QTL detection WEB Animal Recording Scheme AMNS Dairy Sheep Management all SW Software Development in Agricultural Computer Science: Status and Perspectives p. 12
13 Analysis of the Problem: own examples 190: central database for the BHZP: HP-1000 network type database electronic on-farm data recording electronic automated data transfer remote program execution Effect: solves the BHZP problem, but no other despite publication sorry to say: SW project Software Development in Agricultural Computer Science: Status and Perspectives p. 13
14 nalysis of the Problem: own examples ff End 1980: new attempt at generalization: RACLE SUN-S pig breding program Slovenia transfered to Chinese Swine Herd at U of I (USA): no transfer beyond solved a problem in Slovenia and U of I but nothing else despite Master s thesis sorry to say: SW project Software Development in Agricultural Computer Science: Status and Perspectives p. 14
15 A Key Experience meeting of developers of integrated databases different countries different external circumstances remarkable: different systems and tools (dbase, Clipper, racle...) totally different development paths every system a completely new development without reference to previous work (literature?) no way to use software across nothing worked really well Software Development in Agricultural Computer Science: Status and Perspectives p. 15
16 Critical Question How many development projects in the different areas are of the kind: So What? Software Development in Agricultural Computer Science: Status and Perspectives p. 16
17 What to do? the basic problem: solution of NE problem thus: not transferable because solution of one problems includes all side conditions: operating system RDBMS system tools and software this is hardly ever an issue in NE problem but strong restriction on transfer software is generally not available Software Development in Agricultural Computer Science: Status and Perspectives p. 1
18 What to do? ff solution can only lie in: generalization: find the Poodle s core also: never develop for NE case, but always for many parallel implementation implement a layered system which allows replacing components (non monolithic) release software Software Development in Agricultural Computer Science: Status and Perspectives p. 18
19 A New Development Path started as Integrated Database of Performance Records in Pig Populations any animal identification system any data structure installation free of licencing costs scales from on-farm to national development of procedures for development and migration development of software toolbox development of general evaluation software Software Development in Agricultural Computer Science: Status and Perspectives p. 19
20 A New Development Path ff avoid proprietary software use standards (SQL-99) use pen source developer group implementation in at least two environments Software Development in Agricultural Computer Science: Status and Perspectives p. 20
21 Development Strategy/Procedure can be used independently from software migration steps of an information system Software for the implementation of the procedures generic solution for BR Software Development in Agricultural Computer Science: Status and Perspectives p. 21
22 Closed or pen Development? IP can work without program modification InfoSys: different data structures require software modification System without source code not conceivable closed development: few people have the knowledge restricted pool for future development need to create development capacity pensource Software Development in Agricultural Computer Science: Status and Perspectives p. 22
23 pen Source Development The Cathedral & the Bazaar (Eric S. Raymond) given enough eyeballs, all bugs are shallow big project: EMACS, LINUX, FETCHMAIL KDE, GNME requires infrastructure: Internet connection Software management system (CVS) Software Development in Agricultural Computer Science: Status and Perspectives p. 23
24 pen Source: Advantages get help with debugging expand developers base enhances future system safety through expanded knowledge base help during conceptual development cost effective developer and test capacity via the Internet the world is the limit (cooperation space) Software Development in Agricultural Computer Science: Status and Perspectives p. 24
25 Implementers Institute of Animal Production, Irene, South Africa Landesanstalt für Tierzucht, Köllitsch University of Ljubljana, Slovenia Research Institute Nitra, Slovakia University Debrecen, Hungary Veterinary Academy Kaunas, Lithuania University Stara Zagora, Bulgaria FA University Göttingen TZ, Mariensee Software Development in Agricultural Computer Science: Status and Perspectives p. 25
26 Current Projects PISSA South Africa, Pigs, Cheetah Beef South Africa, Cattle PIS Lithuania, Pigs CryoDB Netherlands, Germany, Genebank MINIPIGS Göttingen, pigs MLABIS Germany, DNA Material SCHAF-T Germany, Sheep Saxonian Pig System, Germany EFABIS (FA, F, PL, D), Biodiversity Database a number in Slovenia: Rabbits, Horses, Cattle, Pigs,.. Software Development in Agricultural Computer Science: Status and Perspectives p. 26
27 Platforms create Utility many developers in CC, Research Inst. but SW generally not usable in InfoSys on generic platforms software can be used: Population report ZWISSS... cumulative development model Software Development in Agricultural Computer Science: Status and Perspectives p. 2
28 ( $ ' % 9 8 Population Report 1 & $ # $! 001/./ *+, %- ) 300 /% 6 % 2354 = << :; 9 B?C A? >@? Software Development in Agricultural Computer Science: Status and Perspectives p. 28
29 & % $!# - # 3-2$! $ 0 # + % / ' %$! 5 > 9= G 8 9 9= < 9 9 B I 9 B F B 9= 9 > < 9 I I > 9 B I > 9= ; 9 F= G A B A 6 = > 9= ; 9 8 9F > ; < 9 NL M Q Q PNL M Q P M P Q P NNL M N Q L Q N Q L LL N Q M N Q LL MQ MN P MM N N L P Q QLL L M Population Report 1 ff!,* ) 1 1 % # 0 /! $.*/ - $,! + (*) 6 6: 9 = < 9 ; : ? > > 9 ; 6 : 6 8 A 6 : : 6 < E 8 6 D : C : 6 A 9 C 8 6 B ; : 9 6F 6 A >B :<9 : 9= 6 J I 8 : F I 6 A 9= > 9 DHG > 9= 6 6 *K FA E 6 A E > 9 ; : F < 9 6 A A = A 6 I F E < 9 >IB F > I 6 FA F > F 8 D@ C B B > > ; < 9 ; G :: > ; < 9 ; : J 98 : FA : J 98 : FA ML L NL NL N Q NL M NL L NL LL N P N L LL Q LL N P PLL P P MLL N NLL Software Development in Agricultural Computer Science: Status and Perspectives p. 29
30 ,! * & & ( &!! /- /.- > =< ;9 :9 89 F Population Report 2 +& $ % ')( $ % # 1 & &! BE ACBD <?@@ Software Development in Agricultural Computer Science: Status and Perspectives p. 30
31 + & %* ) ) ) ($ ' & ( % & / 2 ( % ( % 25 & / ( % Population Report 2 ff. - & %! &,, ) ($ % ' %(& (! $ % #!! $ % ' (% ( &! $ % % 0 (* % ( +( 0 (* % ( +( Software Development in Agricultural Computer Science: Status and Perspectives p. 31
32 Publications is SW development in InfoSys or IP research? I think it is. Need to change attitudes. general problem with S projects may be: we are part of the problem? Software Development in Agricultural Computer Science: Status and Perspectives p. 32
33 Summing Up Commercial Development: solve NE problem Research in CS: develop generic solutions research in this area is not uncontested clean definition of layers pen Source avoid proprietary solutions push for a cumulative development model Software Development in Agricultural Computer Science: Status and Perspectives p. 33
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