A new form of research partnership for libraries
With the arrival of new metadata models, vocabularies and tools, cataloguing in libraries will step into a more multidimensional metadata world in the upcoming years. Record-based cataloguing will be replaced with the linking of metadata, which means creating relationships between entities. Through these relationships, the metadata are linked to each other resulting in a metadata network extending across organisational, sector or national borders.
Emerging technologies have recently challenged libraries to reconsider their role as a mere mediator between the collections, the researchers and the wider audiences. In the Digitisation Project of Kindred Languages, we have taken an approach, in which the library has become a central node that connects researchers and laymen to interplay and work for shared goals and objectives.
Scope and objectives
The National Library of Finland has been executing the Digitisation Project of Kindred Languages since 2012. The project seeks to digitise and publish approximately 1,200 monograph titles and more than 100 newspaper titles in various and, in some cases endangered, Uralic languages.
The Fenno-Ugrica online collection consists of 110,000 monograph pages and around 90,000 newspaper pages to which all users will have open access regardless of their place of residence. The project is financially supported by the Kone Foundation and is part of foundation’s Language Programme. The main objective of the Language Programme is to advance the documentation of rare Finno-Ugrian languages, the Finnish language, and minority languages in Finland.
Our objective within the Language Programme is to make sure that both old and new corpora in Uralic languages are made available for the open and interactive use of both the academic community and the language societies. To reach the targets, we will not only produce the digitised materials, but also their development tools to support linguistic research and citizen science.
The Digitisation Project of Kindred Languages is thus linked with the research of language technology. The mission is to improve the usage and usability of digitised content. During the project we have advanced methods that will refine the raw data for further use, especially in the linguistic research.
The machined-encoded text (OCR) contains quite often too many mistakes to be used as such in research. The mistakes in OCR texts must be corrected. For enhancing the OCR texts, the National Library of Finland developed an open source code OCR editor that enabled the editing of machine-encoded text for the benefit of linguistic research.
This tool was necessary to implement, since these rare and peripheral prints often included perished characters, which are sadly neglected by the modern OCR software developers, but belong to the historical context of kindred languages and thus are an essential part of the linguistic heritage.
The material offers a lot, but how to find it?
The majority of the digitised literature was originally published in the 1920s and the 1930s, which was an era when the many Uralic languages were converted into a medium of popular education, enlightenment and dissemination of information pertinent to the developing political agenda of the Soviet state.
The ‘deluge’ of popular literature, 1920s- 1930s, suddenly challenged the lexical orthographic norms of the limited ecclesiastical publications from the 1880s. Newspapers were now written in orthographies and in word forms that the locals would understand. Textbooks were written to address the separate needs of both adults and children. New concepts were introduced in the language.
This was the beginning of a renaissance and period of enlightenment. The linguistically oriented population can also find writings to their delight, especially lexical items specific to a given publication, and orthographically documented specifics of phonetics.
Crowdsourcing to nichesourcing
The written material from this period is a gold mine, but how to filter the material for the benefit of research? Could crowdsourcing play some role here? How does our library meet the objectives, which appear to be beyond its traditional playground?
The traditional methods of crowdsourcing cannot be implemented here, since the targets in crowdsourcing have often been split into several micro-tasks that do not require any special skills from anonymous people, a faceless crowd.
This way of crowdsourcing may produce quantitative results, but from the point of view of research, there is a danger that the needs of linguistic research are not necessarily met. Also, the number of pages is too high to deal with. The remarkable downside is the lack of shared goal or social affinity. There is no reward in traditional methods of crowdsourcing.
Nichesourcing is a specific type of crowdsourcing where tasks are distributed amongst a small crowd of citizen scientists (communities). Although communities provide smaller pools to draw resources, their specific richness in skill is suited for the complex tasks with high-quality product expectations found in nichesourcing.
Communities have purpose, identity and their regular interactions engender social trust and reputation. These communities can correspond to research more precisely. Instead of repetitive and rather trivial tasks, we are trying to utilise the knowledge and skills of citizen scientists to provide qualitative results.
Some selection must be made, since we are not aiming to correct all 200,000 pages which we have digitised, but to give such assignments to citizen scientists that would precisely fill the gaps in linguistic research. A typical task would be editing and collecting the words in such fields of vocabularies, where the researchers do require more information.
Research and society
For instance, there is a lack of Hill Mari words in anatomy. We have digitised the books in medicine and we could try to track the words related to human organs by assigning the citizen scientists to edit and collect words with the OCR editor.
From the perspective of nichesourcing, it is essential that altruism plays a central role, when language communities are involved. Our goal with nichesourcing is to reach a certain level of interplay where the language communities would benefit from the results.
For instance, the corrected words in Ingrian will be added to the online dictionary, which is made freely available to the public and the society to benefit from as well. This objective of interplay can be understood as an aspiration to support the endangered languages and the maintenance of lingual diversity, but also as a servant of ‘two masters’, research and society.