A full collection of GOP Annuals, 62 thick quarto volumes, occupies eleven feet of shelf-space. Each Annual has its pages numbered consecutively from one up to eight hundred or so, and each was originally issued with an alphabetical index, but even so, looking for a particular item is a formidable task, if we do not know in which volume it is to be found. Moreover, these volume indexes do not usually give authors, and do not cover the Christmas and Summer Extras. I therefore decided, several years ago, to try to compose a series of Indexes covering all the bound Girl's Own Annuals, 1880-1941, 62 in all, with summer and Christmas Extras, using the Hypercard program running on an Apple Macintosh. The indexes do not include any of the reduced-size GOP magazines published from 1941 to 1956.
The first two indexes covered fiction stories only, one arranged by author and the other by title. These two Fiction Indexes were published in 1992, bound together as a single octavo volume of approximately 200 pages, by A.&B. Whitworth, 17 Hill Street, Colne, Lancashire, England, under the title Girl's Own Guide, by E. Honor Ward.
The non-fiction articles were then indexed by author and by subject category. These two Non-Fiction Indexes were not published in print form, but were made available, along with the two Fiction Indexes, on the original version of this website, which was developed by Professor Tom Ward and was hosted on the website of the University of Durham.
The current, updated website has taken the original indexes and imported them into database form, in order to take advantage of the searching and sorting possibilities of the online database format. Some editing of the original data has also taken place in order to improve readability.
The current Index to the Girl's Own Paper is now fully searchable and sortable by multiple criteria, including title, author, volume and year of publication. The Non-Fiction Indexes can also be searched and sorted by subject category. Finally, a separate Author Index has been compiled from the original data, cross-referenced for variant author credits and pseudonyms, allowing researchers to concentrate on finding stories and articles by specific authors.