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project:jung_rilke_correspondance_network [2017/09/15 11:18] – [Data] wdparis2017 | project:jung_rilke_correspondance_network [2017/09/22 08:10] – [Jung - Rilke Correspondance Network] gassmich | ||
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- | ===== Jung - Rilke Correspondance Network | + | ===== Jung - Rilke Correspondence Networks |
- | (screenshots or sketches up here) | + | Joint project bringing together three separate projects: Rilke correspondance, |
- | Joint project bringing together three separate | + | Objectives: |
+ | * agree on a common metadata structure for correspondence datasets | ||
+ | * clean and enrich the existing datasets | ||
+ | * build a database that can can be used not just by these two projects | ||
+ | * experiment with existing visualization | ||
===== Data ===== | ===== Data ===== | ||
- | | + | **ACTUAL INPUT DATA** |
- | * | + | |
- | * List and link your actual and ideal data sources. | + | * For Jung correspondance: |
+ | * For Rilke correspondance: | ||
+ | * | ||
+ | |||
+ | Comment: The Rilke data is cleaner than the Jung data. Some cleaning needed to make them match: | ||
+ | 1) separate sender and receiver; clean up and cluster (OpenRefine) | ||
+ | 2) clean up dates and put in a format that IT developpers need (Perl) | ||
+ | 3) clean up placenames and match to geolocators (Dariah-DE) | ||
+ | 4) match senders and receivers to Wikidata where possible (Openrefine, | ||
+ | |||
+ | **METADATA STRUCTURE** | ||
+ | |||
+ | The follwing fields were included in the common basic data structure: | ||
+ | |||
+ | sysID; callNo; titel; sender; senderID; recipient; recipientID; | ||
+ | |||
+ | **DATA CLEANSING AND ENRICHMENT** | ||
+ | |||
+ | |||
+ | * Description of steps, and issues, in Process (please correct and refine). | ||
+ | |||
+ | |||
+ | Issues with the Jung correspondence is data structure. Sender and recipient in one column. | ||
+ | Also dates need both cleaning for consistency (e.g. removal of " | ||
+ | |||
+ | For geocoding the placenames: OpenRefine was used for the normalization of the placenames | ||
+ | |||
+ | The C.G. Jung dataset contains sending locations information for 16,619 out of 32,127 letters; 10,271 places were georeferenced. In the Rilke dataset all the sending location were georeferenced. | ||
+ | |||
+ | For matching senders | ||
+ | |||
+ | Doing this all at once poses some project management challenges, since several people may be working on same files to clean different | ||
+ | |||
+ | DATA after cleaning: | ||
+ | |||
+ | https:// | ||
+ | |||
+ | **DATABASE** | ||
+ | |||
+ | Issues with the target database: | ||
+ | Fields defined, SQL databases and visuablisation program being evaluated. | ||
+ | How - and whether - to integrate with WIkidata still not clear. | ||
+ | |||
+ | Issues: letters are too detailed to be imported as Wikidata items, although it looks like the senders and recipients have the notability and networks to make it worthwhile. Trying to keep options open. | ||
+ | |||
+ | As IT guys are building the database to be used with the visualization tool, data is being cleaned and Q codes are being extracted. | ||
+ | They took the cleaned CVS files, converted to SQL, then JSON. | ||
+ | |||
+ | |||
+ | |||
+ | Additional issues encountered: | ||
+ | |||
+ | - Visualization: | ||
+ | |||
+ | - Ensuring that the files from different projects respect same structure in final, cleaned-up versions. | ||
+ | |||
+ | |||
+ | |||
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===== Team ===== | ===== Team ===== | ||
- | | + | |
+ | |||
+ | | ||
+ | * Lena Heizman (Dodis / histHub): Mentoring with OpenRefine. | ||
+ | * Hugo Martin | ||
+ | * Samantha Weiss | ||
+ | * Michael Gasser (Archives, ETH Library): provider of the dataset [[https:// | ||
+ | * Irina Schubert | ||
+ | * Sylvie Béguelin | ||
+ | * Basil Marti | ||
+ | * Jérome Zbinden | ||
+ | * Deborah Kyburz | ||
+ | * Paul Varé | ||
+ | * Laurel Zuckerman | ||
+ | * Christiane Sibille (Dodis / histHub) | ||
+ | * Adrien Zemma | ||
+ | * Dominik Sievi [[user: | ||
| | ||
- | {{tag> | + | {{tag> |