oeg-upm / morph-csv Goto Github PK

CSVW Parser with Python

Move all the resources as well as the results obtained to another branch of the repo

We can add the rr:class of the subject maps from the generated R2RML applying a regex to the ttl file searching for the names of the ObjectMaps correspondings with each subject to include the rdf:type of the subject using the rr:class predicate

Create a package for downloading and manage all the resources of morph-csv (mappings, data, queries)

Based on the functions provided by the mapping, create new columns on the source data

based on the constraints, normalize the data when:

• csvw:separator is defined in CSVW
• two TM have the same source

Any reason why it is MIT?

After the applications of the rules, remove the duplicates of the raw data with uniq command

Merge this repo with morph-csv 1.0 (https://github.com/oeg-upm/morph-csv) without losing all the track of the development (commits, releases, etc)

Create new docker image and update docker-compose

generate the schema based on the mapping rules

Clean unnecessary files from the repository

For example, in Q9 of GTFS-MAdrid-Benh FK should be created (and they are declared in the CSVW) but the morph-csv output does not contain any PK
https://morph.oeg.fi.upm.es/demo/morphcsv/run/gtfs/9

"foreignKey": [
          {
            "columnReference": "route_id",
            "reference": {
              "resource": "/data/ROUTES.csv",
              "columnReference": "route_id"
            }
          },
          {
            "columnReference": "shape_id",
            "reference": {
              "resource": "/data/SHAPES.csv",
              "columnReference": "shape_id"
            }
          },
          {
            "columnReference": "service_id",
            "reference": {
              "resource": "/data/CALENDAR.csv",
              "columnReference": "service_id"
            }
          },
          {
            "columnReference": "service_id",
            "reference": {
              "resource": "/data/CALENDAR_DATES.csv",
              "columnReference": "service_id"
            }
          }
        ],