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This paper is about data in the humanities. Most of my colleagues in literary and cultural studies would not necessarily speak of their objects of study as “data.” If you ask them what it is they are studying, they would rather speak of books, paintings and movies; of drama and crime fiction, of still lives and action painting; of German expressionist movies and romantic comedy. They would mention Denis Diderot or Toni Morrison, Chardin or Jackson Pollock, Fritz Lang or Diane Keaton. Maybe they would talk about what they are studying as texts, images, and sounds. But rarely would they consider their objects of study to be “data.” However, in the humanities just as in other areas of research, we are increasingly dealing with “data.” With digitization efforts in the private and public sectors going on around the world, more and more data relevant to our fields of study exists, and, if the data has been licensed appropriately, it is available for research. The digital humanities aim to raise to the challenge and realize the potential of this data for humanistic inquiry. As Christine Borgman has shown in her book on Scholarship in the Digital Age, this is as much a theoretical, methodological and social issue as it is a technical issue. Indeed, the existence of all this data raises a host of questions, some of which I would like to address here. For example: What is the relation between the data we have and our objects of study? – Does data replace books, paintings and movies? In what way can data be said to be representations of them? What difference does it make to analyze the digital representation or version of a novel or a painting instead of the printed book, the manuscript, or the original painting? What types of data are there in the humanities, and what difference does it make? – I will argue that one can distinguish two types of data, “big” data and “smart” data. What, then, does it mean to deal with big data, or smart data, in the humanities? What new ways of dealing with data do we need to adopt in the humanities? – How is big data and smart data being dealt with in the process of scholarly knowledge generation, that is when data is being created, enriched, analyzed and interpreted?

Web koostuu miljardeista web-sivuista, joiden sisältöä voidaan hakea Googlen kaltaisilla hakukoneilla ja selailla linkkien avulla. Tämän ihmiselle näkyvän ”sivujen verkon” (Web of Pages) sisälle on rakentunut dataan perustava ”tiedon verkko” (Web of Data), semanttinen web. Se linkittää toisiinsa käsitteitä ja tietoa (dataa) tietokoneiden ymmärtämällä tavalla. Semanttisen webin kehittäminen käynnistyi toden teolla 20 vuotta sitten vuonna 2001 webin infrastruktuuria koordinoivan World Wide Web -konsortion (W3C) ja sen johtajan, webin ”isän” Tim Berners-Leen johdolla. Samana vuonna järjestettiin Suomessa konferenssi Semantic Web Kick-off in Finland ja ensimmäiset kotimaiset tutkimushankkeet käynnistyivät. Artikkelissa esitellään semanttisen webin idea, lyhyt kansainvälinen historia ja Suomessa tehtyä tutkimustyötä Aalto-yliopistossa ja Helsingin yliopistossa erityisesti digitaalisten ihmistieteiden saralla

This article tackles the issue of integrating heterogeneous archival sources in one single data repository, namely the European Holocaust Research Infrastructure (EHRI) portal, whose aim is to support Holocaust research by providing online access to information about dispersed sources relating to the Holocaust (http://portal.ehri-project.eu). In this case, the problem at hand is to combine data coming from a network of archives in order to create an interoperable data space which can be used to search for, retrieve and disseminate content in the context of archival-based research. The scholarly purpose has specific consequences on our task. It assumes that the information made available to the researcher is as close as possible to the originating source in order to guarantee that the ensuing analysis can be deemed reliable. In the EHRI network of archives, as already observed in the case of the EU Cendari project, one cannot but face heterogeneity. The EHRI portal brings together descriptions from more than 1900 institutions. Each archive comes with a whole range of idiosyncrasies corresponding to the way it has been set up and evolved over time. Cataloging practices may also differ. Even the degree of digitization may range from the absence of a digital catalogue to the provision of a full-fledged online catalogue with all the necessary APIs for anyone to query and extract content. There is indeed a contrast here with the global endeavour at the international level to develop and promote standards for the description of archival content as a whole. Nonetheless, in a project like EHRI, standards should play a central role. They are necessary for many tasks related to the integration and exploitation of the aggregated content, namely: ● Being able to compare the content of the various sources, thus being able to develop quality-checking processes; ● Defining of an integrated repository infrastructure where the content of the various archival sources can be reliably hosted; ● Querying and re-using content in a seamless way; ● Deploying tools that have been developed independently of the specificities of the information sources, for instance in order to visualise or mine the resulting pool of information. The central aspect of the work described in this paper is the assessment of the role of the EAD (Encoded Archival Description) standard as the basis for achieving the tasks described above. We have worked out how we could develop a real strategy of defining specific customization of EAD that could be used at various stages of the process of integrating heterogeneous sources. While doing so, we have developed a methodology based on a specification and customization method inspired from the extensive experience of the Text Encoding Initiative (TEI) community. In the TEI framework, as we show in section 1, one has the possibility to model specific subsets or extensions of the TEI guidelines while maintaining both the technical (XML schemas) and editorial (documentation) content within a single framework. This work has led us quite far in anticipating that the method we have developed may be of a wider interest within similar environments, but also, as we believe, for the future maintenance of the EAD standard. Finally this work, successfully tested and implemented in the framework of EHRI [Riondet 2017], can be seen as part of the wider endeavour of European research infrastructures in the humanities such as CLARIN and DARIAH to provide support for researchers to integrate the use of standards in their scholarly practices. This is the reason why the general workflow studied here has been introduced as a use case in the umbrella infrastructure project PARTHENOS which aims, among other things, at disseminating information and resources about methodological and technical standards in the humanities.