-
Notifications
You must be signed in to change notification settings - Fork 0
/
reproducibility.html
1028 lines (678 loc) · 28.8 KB
/
reproducibility.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
<!DOCTYPE html>
<html>
<head>
<title>Reproducible research from project inception through publication: best practices for managing research data</title>
<meta charset="utf-8">
<meta name="date" content="2018-10-31" />
<link href="libs/remark-css/default.css" rel="stylesheet" />
<script src="libs/kePrint/kePrint.js"></script>
<link rel="stylesheet" href="reproducibility_assets/my-theme.css" type="text/css" />
<link rel="stylesheet" href="libs/remark-css/default-fonts.css" type="text/css" />
</head>
<body>
<textarea id="source">
class: center, middle, inverse, title-slide
# Reproducible research from project inception through publication: best practices for managing research data
### 2018-10-31
---
#### research data workflow: this is your world (or it will be soon)
<img src="reproducibility_assets/figure-html/workflow.png" width="100%">
.footnote[J. Bryan from http://stat545.com/]
---
* how do you keep that up-to-date?
--
* what if something changes, what if something needs to be redone - how do you manage that?
--
* why do the results in table 1 not seem to correspond to the results in figure 1?
--
* why were those particular samples omitted?
--
* where did I get these data?
--
* how did I make that figure?
---
background-image: url(https://media.giphy.com/media/MEtSuIu6qu0HC/giphy.gif)
background-position: 50% 50%
background-size: 50%
class: inverse
**basically, if the thought of redoing your analyses is terrifying 😱 then you are doing it wrong (paraphrasing Jenny Bryan)**
---
#### research data workflow: this is your world (or it will be soon) - .light-blue[now add to that publishing your data and code]
<img src="reproducibility_assets/figure-html/workflow_with_data.png" width="100%">
.footnote[J. Bryan from http://stat545.com/]
---
#### reproducibility
* Replication is the cornerstone of scientific research, with consistent findings from independent investigators the primary means by which scientific evidence accumulates for or against a hypothesis.
* The **replicability** of a study is related to the chance that an independent experiment targeting the same scientific question will produce a result consistent with the original study.
* A variation of this concept, referred to as reproducibility, has emerged as a key minimum acceptable standard, especially for heavily computational research.
* **Reproducibility** is defined as the ability to recompute data analytic results, given an observed data set and knowledge of the data analysis pipeline.
.footnote[R. Peng [The reproducibility crisis in science: A statistical counterattack](10.1111/j.1740-9713.2015.00827.x)]
---
#### reproducibility, for scientific reasons
##### given your data, someone else can reproduce your exact results
* increased trustworthiness
* more rigorous, reliable science
* learning more from one another's work
"Science should be 'show me', not 'trust me'; it should be 'help me if you can', not 'catch me if you can'."
*-- Philip B. Stark, <a href="https://www.nature.com/articles/d41586-018-05256-0" target="_blank">Nature 2018</a>*
.footnote[J. Thompson [bit.ly/jlt-rmed2018](bit.ly/jlt-rmed2018)]
---
#### reproducibility, for personal reasons
* Did I mention that subjects with IDs > 100 are actually kangaroos and should be excluded?
* I won the lottery 👏 - now my coworker is taking over
* Journal reviews back after 8 months! Time for revisions!
* How does that patient have 15 months of treatment when we only followed people for 12 months?
.footnote[J. Thompson [bit.ly/jlt-rmed2018](bit.ly/jlt-rmed2018)]
---
#### what we will cover (okay, touch on) today
* best practices
+ naming
+ organiztion
+ scripting
* spreadsheets (and other pointy, clicky stuff)
* literate programming
* version control
* data management plans
* publishing data
---
#### BP [Best Practice]
---
#### BP: naming things - principles for file names
--
* machine readable
- regular expression and globbing friendly
+ avoid spaces, punctuation, accented characters, case sensivity
- easy to compute on with deliberate use of delimiters
+ example: *2017-11-17_berneilwash_oxygen_day_1.csv*
.footnote[J. Bryan [Naming things](https://speakerdeck.com/jennybc/how-to-name-files)]
--
* human readable
- names contain info about the content
- easy to figure out what what something is based on the name
+ *2016_salmon_counts.csv* conveys a lot of information about the object, and has far more meaning than *fishData.csv*
--
* play well with default ordering
.pull-left[
- 1_file_name.csv
- 11_file_name.csv
- 2_file_name.csv
]
.pull-right[
- 01_file_name.csv
- 02_file_name.csv
- 11_file_name.csv
]
---
class: inverse
#### BP: naming - names matter in times of stress
which set of file(names)s would you prefer at 3 a.m. before a dealine?
.center[
<img src="reproducibility_assets/figure-html/good_bad_names.png" width="80%">
]
.footnote[J. Bryan [Naming things](https://speakerdeck.com/jennybc/how-to-name-files)]
---
#### BP: use the ISO 8601 standard for dates (YYYY-MM-DD) everwhere, always without exception
.center[
<img src="reproducibility_assets/figure-html/noniso.png" width="70%">
.small[**comprehensive map of all countries in the world that use MMDDYYYY format**]
]
.footnote[J. Bryan [Naming things](https://speakerdeck.com/jennybc/how-to-name-files)]
---
#### BP: employ sound project organization
*your closest collaborator is you six months ago, but you do not reply to emails (K. Broman paraphrasing M. Holder)*
.pull-left[
<img src="reproducibility_assets/figure-html/projectOrganizationCropped.png" width="95%">
]
.pull-right[
.small[
* segregate all materials for a project in one directory
* organize according to prevailing conventions (e.g., R package structure)
* maintain a clear separation of data, method, and output while unambiguously expressing the relationship among them
* specify the computational environment used for the original analysis
* organize such that another person can know what to expect from the plain meaning of the file and directory names
* include README files
]]
.footnote[K. Broman [Steps toward reproducible research](bit.ly/jsm2016)]
---
#### BP: keep the raw data raw
* save the raw data
.center[
<img src="reproducibility_assets/figure-html/Fleetwood-Mac-Cant-Go-Back-Love.jpg" width="80%">
]
.footnote[Wilson et al. (2017) [Good enough practices in scientific computing](https://doi.org/10.1371/journal.pcbi.1005510)]
---
#### BP: thoughtful curation
* curate your data in a way that you would like to receive it
.center[
<img src="/home/srearl/localRepos/science_mathematics_seminar/reproducibility_assets/figure-html/usgs.png" width="80%">
]
.footnote[Wilson et al. (2017) [Good enough practices in scientific computing](https://doi.org/10.1371/journal.pcbi.1005510)]
---
#### BP: open file formats
* use open file formats (e.g., csv not xlsx)
<br>
<br>
.center[
<img src="reproducibility_assets/figure-html/paperclip.jpeg" width="50%">
]
.footnote[Wilson et al. (2017) [Good enough practices in scientific computing](https://doi.org/10.1371/journal.pcbi.1005510)]
---
#### BP: analysis-friendly data
* create analysis-friendly data:
+ each column a variable
+ each row an observation
.pull-left[
<table class="table" style="font-size: 12px; width: auto !important; margin-left: auto; margin-right: auto;">
<thead>
<tr>
<th style="text-align:right;"> Sepal.Length </th>
<th style="text-align:right;"> Sepal.Width </th>
<th style="text-align:right;"> Petal.Length </th>
<th style="text-align:right;"> Petal.Width </th>
<th style="text-align:left;"> Species </th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:right;"> 5.1 </td>
<td style="text-align:right;"> 3.5 </td>
<td style="text-align:right;"> 1.4 </td>
<td style="text-align:right;"> 0.2 </td>
<td style="text-align:left;"> setosa </td>
</tr>
<tr>
<td style="text-align:right;"> 4.9 </td>
<td style="text-align:right;"> 3.0 </td>
<td style="text-align:right;"> 1.4 </td>
<td style="text-align:right;"> 0.2 </td>
<td style="text-align:left;"> setosa </td>
</tr>
<tr>
<td style="text-align:right;"> 4.7 </td>
<td style="text-align:right;"> 3.2 </td>
<td style="text-align:right;"> 1.3 </td>
<td style="text-align:right;"> 0.2 </td>
<td style="text-align:left;"> setosa </td>
</tr>
<tr>
<td style="text-align:right;"> 4.6 </td>
<td style="text-align:right;"> 3.1 </td>
<td style="text-align:right;"> 1.5 </td>
<td style="text-align:right;"> 0.2 </td>
<td style="text-align:left;"> setosa </td>
</tr>
<tr>
<td style="text-align:right;"> 5.0 </td>
<td style="text-align:right;"> 3.6 </td>
<td style="text-align:right;"> 1.4 </td>
<td style="text-align:right;"> 0.2 </td>
<td style="text-align:left;"> setosa </td>
</tr>
<tr>
<td style="text-align:right;"> 5.4 </td>
<td style="text-align:right;"> 3.9 </td>
<td style="text-align:right;"> 1.7 </td>
<td style="text-align:right;"> 0.4 </td>
<td style="text-align:left;"> setosa </td>
</tr>
</tbody>
</table>
]
.pull-right[
<table class="table" style="font-size: 12px; width: auto !important; margin-left: auto; margin-right: auto;">
<thead>
<tr>
<th style="text-align:left;"> Species </th>
<th style="text-align:left;"> metric </th>
<th style="text-align:right;"> value </th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Length </td>
<td style="text-align:right;"> 5.1 </td>
</tr>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Length </td>
<td style="text-align:right;"> 4.9 </td>
</tr>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Length </td>
<td style="text-align:right;"> 4.7 </td>
</tr>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Length </td>
<td style="text-align:right;"> 4.6 </td>
</tr>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Length </td>
<td style="text-align:right;"> 5.0 </td>
</tr>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Length </td>
<td style="text-align:right;"> 5.4 </td>
</tr>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Width </td>
<td style="text-align:right;"> 3.5 </td>
</tr>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Width </td>
<td style="text-align:right;"> 3.0 </td>
</tr>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Width </td>
<td style="text-align:right;"> 3.2 </td>
</tr>
<tr>
<td style="text-align:left;"> setosa </td>
<td style="text-align:left;"> Sepal.Width </td>
<td style="text-align:right;"> 3.1 </td>
</tr>
</tbody>
</table>
]
.footnote[Wilson et al. (2017) [Good enough practices in scientific computing](https://doi.org/10.1371/journal.pcbi.1005510)]
---
background-image: url(https://media.giphy.com/media/3orif8zlUQh32KTURy/giphy.gif)
background-position: 50% 50%
background-size: 50%
class: inverse
#### BP: record everything
* record all the steps of the data process
---
#### BP: everything in a script
.light-blue[The most basic principle for reproducible research is: **do everything via code**]
* downloading data from the web
* converting an Excel file to CSV
* renaming columns or variables
* omitting bad samples or data points
* *...do all of these with programatically*
You will be tempted to open up a data file and hand-edit. But if you get a revised version of that file, you will need to do it again, and it will be harder to figure out what it was that you did.
Some things are more cumbersome via code but you will save time in the long run.
.footnote[K. Broman [Steps toward reproducible research](bit.ly/jsm2016)]
---
#### BP: learn a language. any language, just do it
.pull-left[
<img src="reproducibility_assets/figure-html/rlogo.jpg" width="100%">
]
.pull-right[
<img src="reproducibility_assets/figure-html/python-logo.png" width="70%">
]
---
#### spreadsheets: the dark side
.center[
<img src="reproducibility_assets/figure-html/excel_errors_wash_post.png" width="80%">
]
---
#### spreadsheets: the 2nd best tool for everything
.pull-left[
<img src="reproducibility_assets/figure-html/spreadsheet_hidden_data.png" width="100%">
]
.pull-right[
the beauty and the travesty of spreadsheets is that they allow you to do just about anything
* data in merged cells
* data in formatting
* small multiples
* data in formulas
]
--
**BP: use open file formats (e.g., CSV, not XLSX)**
.footnote[J. Bryan [Spreadsheets](https://speakerdeck.com/jennybc/spreadsheets)]
---
#### spreadsheets versus scripting
consider, we want to remove samples that we feel may have been contaminated...
.pull-left[
**in a R script**
<hr>
```r
some work...
```
.small[*comment code:*
.light-blue[remove samples 4 and 5 that may have been compromised due to wading upstream during sampling]]
```r
chemistry_data %>%
filter(!sampleID %in% c(4,5))
```
```r
...more work
```
]
.pull-right[
**in a spreadsheet**
<hr>
<img src="reproducibility_assets/figure-html/spreadsheet_remove_samples.png" width="105%">
]
---
#### literate programming
a common approach
<img src="reproducibility_assets/figure-html/literateProgramming.png">
.footnote[K. Healy [The Plain Person's Guide to Plain Text Social Science](https://kieranhealy.org/files/papers/plain-person-text.pdf)]
---
#### literate programming
* the problem is that the gaps are particularly prone to errors
* literate programming is essentially the integration of code and text
<small>Knuth, D. E. (1992), Literate programming, CSLI Lecture Notes, Stanford, CA: Center for the Study of Language and Information (CSLI), 1992</small>
<img src="reproducibility_assets/figure-html/literateProgramming.png" >
.footnote[K. Healy [The Plain Person's Guide to Plain Text Social Science](https://kieranhealy.org/files/papers/plain-person-text.pdf)]
---
#### literate programming
.pull-left[
<img src="reproducibility_assets/figure-html/Rmarkdown.png" width="90%">
]
.pull-left[
<img src="reproducibility_assets/figure-html/Rmd_to_Word.png" width="90%">
]
---
class: inverse
#### version control
.center[
<img src="reproducibility_assets/figure-html/CAP_renewal_screenshot.png" width="100%">
]
---
#### version control: Git
* git watches repositories (like a directory) for changes
* git asks that you describe changes when they are made
* git remembers old versions if you need them
* git also keeps an eye out for conflicts, and forces you to resolve them
.footnote[Jeff Goldsmith ["Git"](https://speakerdeck.com/jeffgoldsmith/dsi-git-and-github)]
---
#### version control: Git + GitHub
when combined with a service such as GitHub
* ...allows multiple people to contribute to the same repository, and does all of the aforementioned for everyone at once
.center[
<img src="reproducibility_assets/figure-html/git_collaboration.png" width="65%">
]
.footnote[Jeff Goldsmith ["Git"](https://speakerdeck.com/jeffgoldsmith/dsi-git-and-github)]
---
#### version control: Git
.light-blue[tame the chaos] 👏
.center[
<img src="reproducibility_assets/figure-html/git_flow.png" width="80%">
]
---
class: inverse
#### version control: Git
.center[
<img src="reproducibility_assets/figure-html/bokis_on_git.png" width="80%">
]
---
background-image: url(https://media.giphy.com/media/PnXRAFOJFCt3i/giphy.gif)
background-position: 50% 50%
background-size: 50%
class: inverse
#### I am not saying it is easy
---
#### I am not saying it is easy
Kieran Healy on two revolutions in computing:
"On one side, the mobile, cloud-centered, touch-screen, phone-or-tablet model has brought powerful computing to more people than ever before."
"On the other side, tools for coding, data analysis, and writing are also revolutionary but mostly work by gluing together separate, specialized widgets that do much less to hide the operation system layer, and require knowledge of things like the file system."
.footnote[K. Healy [The Plain Person's Guide to Plain Text Social Science](https://kieranhealy.org/files/papers/plain-person-text.pdf)]
---
#### I am not saying it is easy
Very few people are trained in both data analysis and biology.
The practical and pragmatic issues of data analysis and data interpretation are not something that is taught at undergrad or graduate school level.
Most senior faculty do not know how to do this.
Nor do many junior faculty.
But our field increasingly *depends* on skilled interpretation of private + public data.
So how do we address this? Many layers, many approaches…
.footnote[Brown, C. Titus et al. [“2017 - Data Intensive Biology Summer Institute.”](https://osf.io/pyvfg/)]
---
#### OHI: nature ecology & evolution
.center[
<img src="reproducibility_assets/figure-html/lowndes_title.png" width="90%">
]
.footnote[Lowndes et al. (2017) [Our path to better science in less time using open data science tools](https://www.nature.com/articles/s41559-017-0160)]
---
#### OHI: framework
.center[
<img src="reproducibility_assets/figure-html/ohi_framework.png" width="90%">
]
.footnote[Lowndes et al. (2017) [Our path to better science in less time using open data science tools](https://www.nature.com/articles/s41559-017-0160)]
---
#### OHI: evolution of a workflow
.center[
<img src="reproducibility_assets/figure-html/lowndes_figure1.jpg" width="80%">
]
.footnote[Lowndes et al. (2017) [Our path to better science in less time using open data science tools](https://www.nature.com/articles/s41559-017-0160)]
---
#### BP: forethought
strive for reproducibility from the outset
"It's not thinking, 'This is easiest for myself right now.' It's thinking, 'When I'm working on this next week, next month, right before I graduate — how do I set myself up so that it's easier later?'
*-- Julia Stewart Lowndes in "A toolkit for data transparency takes shape", [Nature 2018](https://www.nature.com/articles/d41586-018-05256-0)*
.footnote[J. Thompson [bit.ly/jlt-rmed2018](bit.ly/jlt-rmed2018)]
---
#### Data Management Plan (DMP)
"...a written document that describes the data you expect to acquire or generate during the course of a research project, how you will manage, describe, analyze, and store those data, and what mechanisms you will use at the end of your project to share and preserve your data." Stanford Libraries [Data Management Plans](https://library.stanford.edu/research/data-management-services/data-management-plans)
* Describes how data will be:
- Collected
- Managed during the project
- Preserved after completion
.center[
<img src="reproducibility_assets/figure-html/dmp_tool.JPG" width="80%">
]
---
#### research data workflow: this is your world (or it will be soon) - .light-blue[now add to that publishing your data and code]
<img src="reproducibility_assets/figure-html/workflow_with_data.png" width="100%">
.footnote[J. Bryan from http://stat545.com/]
---
<!-- this starts the metadata + publishing lecture -->
#### why publish data
* big picture
+ increasingly a requirement
+ advancement of science
* researcher perspective
+ papers with publicly available data receive a higher number of citations than similar studies lacking available data<sup>1</sup>
+ data sharing is associated with higher productivity<sup>1</sup>
+ [citeable product](https://portal.lternet.edu/nis/mapbrowse?packageid=knb-lter-cap.621.1)
.footnote[<sup>1</sup>[Marwick et al. 2017](https://doi.org/10.7287/peerj.preprints.3192v1)]
---
.pull-left[
<img src="reproducibility_assets/figure-html/ClimateGate.png" width="105%">
]
.pull-right[
"The climate scientists at the centre of a media storm over leaked emails were yesterday cleared of accusations that they fudged their results and silenced critics, but a review found they had failed to be open enough about their work."
]
.footnote[[NCEAS crescynt-training](https://nceas.github.io/crescynt-training/)]
---
#### concerns about sharing data
most common concerns can be addressed *with metadata*
.pull-left[
.center[**concern**]
<hr>
* inappropriate use due to misunderstanding of research purpose or parameters
* security and confidentiality of sensitive data
* lack of acknowledgement / credit
]
.pull-right[
.center[**solution**]
<hr>
* provide rich abstract, purpose, use constraints, and supplemental information
* use constraints to specify who may access the data and how
* specify a required data citation within the use constraints
]
.footnote[[DataONE education modules](https://www.dataone.org/education-modules)]
---
class: inverse
<br>
<br>
<br>
"Without clear instructions, many researchers struggle to avoid chaos in their file structures, and so are understandably reluctant to expose their workflow for others to see. This may be one of the reasons that so many requests for details about method, including requests for data and code, are turned down or go unanswered (Collberg & Proebsting 2016)."
.footnote[[Marwick et al. 2017](https://doi.org/10.7287/peerj.preprints.3192v1)]
---
#### what do we mean by data repository?
<table>
<thead>
<tr>
<th style="text-align:left;"> system </th>
<th style="text-align:left;"> long.term </th>
<th style="text-align:left;"> versioned </th>
<th style="text-align:left;"> citable </th>
<th style="text-align:left;"> discoverable </th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;"> Google Drive </td>
<td style="text-align:left;"> maybe </td>
<td style="text-align:left;"> maybe </td>
<td style="text-align:left;"> no </td>
<td style="text-align:left;"> no </td>
</tr>
<tr>
<td style="text-align:left;"> GitHub </td>
<td style="text-align:left;"> yes </td>
<td style="text-align:left;"> yes </td>
<td style="text-align:left;"> no </td>
<td style="text-align:left;"> no </td>
</tr>
<tr>
<td style="text-align:left;"> University Server </td>
<td style="text-align:left;"> maybe </td>
<td style="text-align:left;"> no </td>
<td style="text-align:left;"> no </td>
<td style="text-align:left;"> maybe </td>
</tr>
<tr>
<td style="text-align:left;"> KNB* </td>
<td style="text-align:left;"> yes </td>
<td style="text-align:left;"> yes </td>
<td style="text-align:left;"> yes </td>
<td style="text-align:left;"> yes </td>
</tr>
</tbody>
</table>
.small[\*KNB (the Knowledge Network for Biocomplexity) is an international repository intended to facilitate ecological and environmental research]
.footnote[[NCEAS crescynt-training](https://nceas.github.io/crescynt-training/)]
---
#### where to publish?
.center[
<img src="reproducibility_assets/figure-html/r3data.png" width="60%">
]
is wonderful but I would start with...
* institutional resources
* lab, colleagues
* conferences
---
#### metadata standards: there are many
.center[
<img src="reproducibility_assets/figure-html/metadata_standards_list.png" width="90%">
]
---
#### metadata standards: what is a standard?
standards provides a structure to describe data with:
- common terms to allow consistency between records
- common definitions for easier interpretation
- common language for ease of communication
- common structure to quickly locate information
in search and retrieval, standards provide:
- documentation structure in a reliable and predictable format for computer interpretation
- a uniform summary description of the dataset
.footnote[[DataONE education modules](https://www.dataone.org/education-modules)]
---
#### metadata: the who, what, why, where, when
- principal investigator
- funding sources
- data collector/producer
- project description
- sample and sampling procedures
- weighting
- substantive, temporal, and geographic coverage of the data collection
- data source(s)
- unit(s) of analysis/observation
- variables
- technical information on files
- data collection instruments
.footnote[B. Marshall [Metadata for Research Data](https://speakerdeck.com/bmarshall/metadata-for-research-data)]
---
class: inverse
<br>
<br>
<br>
<br>
"data without the contextual information needed to interpret it (and ultimately reproduce the results) is useless"
.footnote[B. Marshall [Metadata for Research Data](https://speakerdeck.com/bmarshall/metadata-for-research-data)]
---
#### what makes good metatadata?
- consistency with commonly used fields (e.g., YYYY-MM-DD)
- use a standard vocubulary
- spell out acronyms
- provide all the critical information for: *identification; entities and attributes; data quality; data lineage; access, use, and liability constraints; accessing the data; spatial reference*
- complete title: who, what, when, where, and scale
- be specific, and quantify where possible
- use descriptive and clear writing
- fully document geographic locations
- use keywords wisely (use a thesausus when possible)
- remember that a computer will read this:
+ avoid special characters
+ avoid tabs, indents, carriage returns
+ copy from a text file (not a file with rich text like Word or RTF)
.light-blue[**detail, there is no such thing as too much!**]
.footnote[[DataONE education modules](https://www.dataone.org/education-modules)]
---
#### a special note about titles
.center[
<img src="reproducibility_assets/figure-html/recently_added_titles.png" width="100%">
]
---
#### orcid
.center[
<img src="reproducibility_assets/figure-html/orcid.png" width="50%">
]
[orcid.org](https://orcid.org/)
</textarea>
<script src="https://remarkjs.com/downloads/remark-latest.min.js"></script>
<script>var slideshow = remark.create({
"highlightStyle": "github",
"highlightLines": true,
"countIncrementalSlides": false
});
if (window.HTMLWidgets) slideshow.on('afterShowSlide', function (slide) {
window.dispatchEvent(new Event('resize'));
});
(function() {
var d = document, s = d.createElement("style"), r = d.querySelector(".remark-slide-scaler");
if (!r) return;
s.type = "text/css"; s.innerHTML = "@page {size: " + r.style.width + " " + r.style.height +"; }";
d.head.appendChild(s);
})();</script>
<script>
(function() {
var i, text, code, codes = document.getElementsByTagName('code');