How to Contribute to the CLLD Concepticon?
Contributing to the CLLD Concepticon is simple on the one hand and difficult on the other hand. If you are an experienced user of GitHub and know about the basic ideas behind pull requests and testing in Python, it will be easy to propose changes. Creating the change proposals, however, requires to study the way we encode data in the CLLD Concepticon. Basically, you can propose new concept lists using whatever method you want. We recommend, however, that you have a look at the methods we already created, since these may significantly ease the task of adding new concept lists, or changing the mappings we provide in existing ones.
GitHub Pull Requests
We won't give you any detailed explanations here but just assume that you find all information you need in this excellent HowTo:
If you experience any problems, just let us know.
Submitting Concept Lists
Let us assume you have a concept list which you would like to submit to our Concepticon, so that we can afterwards include it and link it. In this case, you could write us an email, but even better, you would file an issue using our issue tracker. Here, we collect and classify different kinds of issues. New concept lists are tagged accordingly, and here you can see all concept lists, which we would like to map but have not yet found time to include.
In our workflow, we distinguish different stages of concept list creation and indicate this with tags:
- scanned refers to those concept lists which are already available in a scanned version, so that we can start typing them off. Sometimes, concept lists are only available in some specific archive, and we don't have access to them immediately. In this case, our concept list issue is just tagged as "new concept list", not yet as "scanned".
- typed refers to those concept lists which have already been digitized.
- formatted refers to concept lists which have been already brought into the format needed for mapping, that is, they are given as TSV file, with one field indicating the number, one the concept label, and additional fields indicating additional data as given in the concept list.
Once you filed an issue and provide us with the important information, we will tag the issue accordingly, and try to follow it up. If you have the list in a typed version, or even in a formatted version, you could either directly attach it to your issue, or you could create pull request (see above) where you place your formatted but not yet linked concept list into the folder unlinked.
Linking Concept Lists
Suppose you have prepared a dataset that contains a concept list and that you would like to submit to the Concepticon, or you have detected a concept list you deem important but which you don't find in our current collection: What are the steps you need to undertake to submit this list to us, and to share it with the whole community? A simple way which is, however, not guaranteed to work immediately, is to write an email or file an issue about a missing concept list. If you do so, we will evaluate the proposal and see what we can do. Naturally, we'd appreciate it even more if you could provide us with
- a scanned version of the list, or even better
- a digitized (typed-off) version of the list, or even better
- a linked version of the list. In all these cases, you could still just write an email or attach the data to the issue, but you could also fork your own version of the concepticon (see "GitHub Pull Requests" above) and officially add the data. The advantage of this is that you could be listed as a co-author in the next of the yearly releases of the CLLD Concepticon. We gurantee co-authorship to all authors of linked versions of new missing concept lists. We officially thank all people who provided scans and digitized versions on the website at http://concepticon.clld.org.
Linking Concept Lists: The Manual Style
If you link a concept list manually, we will assume and check automatically and manually that this has been done properly. You can prepare your changes using whatever software you like, be it pure text-files or spreadsheet programs. In order to link a concept list, you need to supply the following information:
- the concept list itself, which should be placed into the folder conceptlists/. Here, we follow the convention of naming the file according to the schema FirstAuthor-Year-NumberOfItems.tsv. Each list needs to have the following fields (the order is irrelevant):
- ID: an identifier, following the schema FirstAuthor-Year-NumberOfItems-Number
- NUMBER: a number or a string that is unique to the given concept (CR: this is slightly ambiguous I think)
- ENGLISH or GLOSS: use ENGLISH, if the original language is ENGLISH, use GLOSS, if the original entry of the concept label is another language and the gloss is your translation
- CONCEPTICON_ID: either a valid id of our Concepticon, or an empty field, if you don't know how to map it (we automatically compute the amount of missing links and badge them for each concept list)
- CONCEPTICON_GLOSS: the corresponding gloss Apart from this, you can add as many further columns as you want. Here, we have further conventions:
- if you have translations of the gloss in different languages, label them accordingly (CHINESE, FRENCH, etc.)
- if you have a ranked list, provide the RANK as an integer and name the field RANK
- there are further "soft" conventions, which you can inspect by having a look at the different concept lists which are already mapped (CR: examples might be beneficial)
- the reference, provided as a BibTex entry in the filereferences.bib. Please use the schema FirstAuthorYear and add a, b, c, etc. if there are multiple entires for the same author and the same yere,
- a description of the basic characteristics of the list in the file conceptlists.tsv. Here, we recommend you to either contact us if there are further questions, or to just look up how we usually encode the respective values. Not all information is required, but it is our goal to try always to fill out as many cells for a new concept list as possible.
- if you have a scan of your list which does not fall under the copyright law (no full books, but pages in which one can see the concept lists should be acceptable), please label it as BibTexKey.pdf and put it in the folder sources
If you feel that you need to add new identifiers which are currently missing in the CLLD Concepticon, please contact us, and we will provide you with the relevant information on how to add new concept set identifiers. Please also do not hesitate to ask us if therea are any further questions.
Using automatic mapping software
The concepticon API allows you to automatically link your concept list to the concepticon. We currently support two different styles, one which exhaustively compars each gloss with each other, and one quick style, which compares only those glosses which have been filtered as similar enough in a first run. The styles also differe slightly in their output. Here is, how you can carry out a linking using the quick style of your list called "input.tsv"
$ concepticon map_concepts input.tsv # or $ concepticon map_concepts input.tsv > automatic.tsv # redirect output to file.
This script requires that the concepticon API has been installed, and that your input list contains at least two columns: one labeled "ID" and one labelded "GLOSS" or "ENGLISH".
The mapping procedure will output another list, containing three additional columns:
SIMILARITY (the latter ranke similarity on a scale between 1 and 5, with 1 being most similar, if there is a matching concept). If there are multiple possibilities of the same similarity, these are output in ranked order, preceded by the
<<< and followed by
>>>. Left-overs are marked by two question marks (
???). The last line also contains the percentage of mapped items with score <= 3, which gives you an idea on how much work still needs to be done to manually refine the mapping.
An excerpt of an example output is here:
ID GLOSS CONCEPTICON_ID CONCEPTICON_GLOSS SIMILARITY 1 hair 1040 HAIR 2 2 head 1256 HEAD 2 3 mouth 674 MOUTH 2 4 nose 1221 NOSE 2 ... 122 I 1209 I 1 123 thou 1215 THOU 2 124 he 1211 HE 2 125 die 1494 DIE 2 126 we excl. ??? <<< 127 you 1213 YOU 2 127 you 2312 YOU (OBLIQUE CASE OF YOU) 2 >>> 128 they 817 THEY 2 # 123 128 0.96
Checklist for pull requests
If you write a pull request to Concepticon, make sure that you have added the relevant information in the following files:
1 Have you correctly linked your concept list? If so, you should have a linked concept list with minimally the following columns: "ID" (use the form
FirstAuthorLastName-Year-NumberOfItems-ID to create the ID for you concept list), "NUMBER" (a digit, usually following the numberin in the source, or reflecting the order in the source), "ENGLISH" (if the concept list offers an official English translation) or otherwise "GLOSS" (which requires an additional column indicating the original language of the list), "CONCEPTICON_GLOSS" (the gloss as given in concepticon), and "CONCEPTICON_ID" (our Concepticon ID).
2 Have you added the metadata for your concept list? You find more information by looking into the file
conceptlists.tsv, please contact us if you run in trouble.
3 Have you added your reference for the concept lists, and all references which you used in your description, to our bibtex file
4 Have you added new concept sets to our Concepticon in the file
concepticon.tsv? If so, have you offered proper definitions?
5 Do you reference a source file in PDF, in your description of the concept list in
conceptlists.tsv? If so, have you added it (in the form
FirstAuthorLastNameYear) to the folder
6 Do you have to thank some person for help with the concept list? If you are contributing and not part of our core editorial team, we will add you, so please provide us with your name and affiliation. To keep track of whom to thank, please edit the
7 Have you tested your modifications by typing
$ concepticon test in the command line?
8 Have you computed the new statistics, by typing
$ concepticon stats and commited the files
In brief, whenever you add a new concept list, you could use the following check-list:
- concept linking properly done?
- metadata in
- references in
- new concept sets added?
- source file in PDF?
- thank and acknowledge contributors?
- tested the code?
- computed and committed new statistics?
After you have added your new concept lists, you should test whether the mapping and the format conforms to our standards. For this, we use the nose library. To test, if you have nose installed, just type:
The output will tell you whether your mapping has succeded. If you run into problems, just let us know, and we try to help as best as we can.
We have certain conventions on how to deal with problems when linking concepts to the Concepticon. Here, we currently list them without specific order of preference.
Missing translations are indicated as NAN, as an example see the list by
Missing Concept Sets
If we don't find a concept set for a concept and deem the concept to be too specific to be further mapped, we leave the field empty. All these concept sets are later assigned to a class of concept sets called "NAN".
We do NOT allow to carry out N-N mappings between concepts in a concept lists and concept sets in the Concepticon. As a work-around, however, we allow to multiple a respective concept in a given source and assign it to two different concept sets. This has been done, for example, in the list Matisoff-1978-200, where the concept "vagina or breast/milk" clearly indicates that the author means two distinct entries, but lists them in the same line of the list. Similarly, one may encounter that people make a further distinction within a wordlist, by adding in brackets that, for example, there are actually two words for "frog" in some varieties, a "big frog" and a "small frog". In these cases it is also important to split the respective entry, as it has been done in the list by List-2016-180, although, admittedly, the actual decision was already done in the compilation of the concept list.