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John Unsworth (2000) proposed a tentative list of scholarly primitives, and although he made a reservation that it was not meant to be exhaustive, one omission is striking, namely the exclusion of communicating. It is even more visible once one realises that all the examples he provides in the paper of comparison IBabble), linking (Blake Archive), or sampling (VRML visualisation of Dante’s Inferno) have the indispensable communication component attached to them. The aim of this presentation is two-fold. First of all, we will reclaim the role of communication as one of the fundamental functional primitives, crucial in all stages of the research workflow. To use Unsworth’s nomenclature, communication takes advantage of the additive characteristics of scholarly primitives and enters into combinations with all other scholarly primitives. Secondly, right after reestablishing the communication as a scholarly primitive we will swiftly proceed to problematise the notion of its universality for all disciplines through exploration of the specificity of scholarly communication in the humanities. We will achieve that using New Panorama of Polish Literature (NPLP.pl) as a case-study, outlining the relevant digital infrastructure for the humanities. It has long been suggested that communication should be seen as a fundamental element of the research workflow, rather than an activity running somewhat separate to the research practice (Latour and Woolgar 1986; Garvey 1979; Galison and Galison 1997; Nielsen 2011). Recently this idea wass reinforced by Hillyer et al. (2017) who describe open science as “opening of the entire research cycle” and include communication as one of its key elements. It means that dissemination is no longer perceived as the final stage of a research process but becomes an integral part of all scholarly activities. New digital methods and tools (Dallas et al. 2017), including electronic communication and social media (Kjellberg 2010), facilitate this process. allowing scholars to communicate and collaborate with each other and the wider audience quickly and efficiently at all stages of their work. This also includes intermediary results of the work, including raw and secondary data (Castelli, Manghi, and Thanos 2013). The incorporation of communication into all stages of the research workflow also means that choosing a certain communication strategy is obviously influenced by the perceived goal, but also the goal influences other phases of the research process. This feedback loop more precisely on the example of NPLP, a research infrastructure for literary scholars enabling the creation of extended, multimedia monographs and presenting scholarly arguments through linking text with image, visualisation, map and video content. Yet, Creating a new digital collection forces researchers to rethink how their work is presented, categorised and displayed . For instance in "Postmodern Sienkiewicz" collection (http://nplp.pl/en/kolekcja/postmodern-sienkiewicz/) authors divided their articles into shorter fragments with additional iconography allowing for non-linear reading and access through image-interface. These activities required additional work on the stage of data collection, analysis and interpretation. In conclusion we will tackle upon the question remains to what extent such communication practices are universal for all sciences and what could be treated as reserved for the humanities in the spirit of Diltheyan disctinction between explaining (in sciences) and understanding (in the humanities). {"references": ["Castelli, D., P. Manghi, and C. Thanos. 2013. 'A Vision towards Scientific Communication Infrastructures: On Bridging the Realms of Research Digital Libraries and Scientific Data Centers'. International Journal on Digital Libraries 13 (3\u20134): 155\u201369. https://doi.org/10.1007/s00799-013-0106-7.", "Dallas, Costis, Nephelie Chatzidiakou, Agiatis Benardou, Michael Bender, Aur\u00e9lien Berra, Claire Clivaz, John Cunningham, et al. 2017. 'European Survey on Scholarly Practices and Digital Needs in the Arts and Humanities - Highlights Report'. Zenodo. https://doi.org/10.5281/zenodo.260101.", "Galison, Peter, and Joseph Pellegrino University Professor Peter Galison. 1997. Image and Logic: A Material Culture of Microphysics. University of Chicago Press.", "Garvey, WILLIAM D. 1979. 'CHAPTER 1 - The Role of Scientific Communication in the Conduct of Research and the Creation of Scientific Knowledge'. In Communication: The Essence of Science, edited by WILLIAM D. Garvey, 1\u201339. Pergamon. https://doi.org/10.1016/B978-0-08-023344-4.50006-4.", "Hillyer, Rebecca, Alejandro Posada, Denisse Albornoz, Leslie Chan, and Angela Okune. 2017. 'Framing a Situated and Inclusive Open Science: Emerging Lessons from the Open and Collaborative Science in Development Network'. 2017.", "Kjellberg, Sara. 2010. 'I Am a Blogging Researcher: Motivations for Blogging in a Scholarly Context'. First Monday 15 (8). https://doi.org/10.5210/fm.v15i8.2962.", "Latour, Bruno, and Steve Woolgar. 1986. Laboratory Life: The Construction of Scientific Facts. Princeton University Press.", "Nielsen, Michael A. 2011. Reinventing Discovery\u202f: The New Era of Networked Science. Princeton, N.J.: Princeton University Press. http://press.princeton.edu/titles/9517.html.", "Unsworth, John. 2000. 'Scholarly Primitives: What Methods Do Humanities Researchers Have in Common, and How Might Our Tools Reflect This?' In . King's College London. http://people.brandeis.edu/~unsworth/Kings.5-00/primitives.html."]}

Abstract‘Social and Cultural Innovation’ is a syntagma that is receiving increased usage among researchers since it was the title chosen by the European Strategy Forum Research Infrastructures for the working group that deals with research infrastructures primarily connected with Social Sciences and the Humanities. Innovation refers to the creation of new products and services by bringing a new idea to the market. Economic growth turns on infrastructures, which provide access to services and knowledge, e.g. by overcoming the digital divide. The current migrant and refugee crisis has made it clear with extraordinary effectiveness that a most urgent objective is to work out policies of social and cultural innovation to the advantage of new citizens – policies that will make them feel welcome in full dignity.

This book is available as open access through the Bloomsbury Open programme and is available on www.bloomsburycollections.com. It is funded by Trinity College Dublin, DARIAH-EU and the European Commission.This book explores the challenges society faces with big data, through the lens of culture rather than social, political or economic trends, as demonstrated in the words we use, the values that underpin our interactions, and the biases and assumptions that drive us. Focusing on areas such as data and language, data and sensemaking, data and power, data and invisibility, and big data aggregation, it demonstrates that humanities research, focussing on cultural rather than social, political or economic frames of reference for viewing technology, resists mass datafication for a reason, and that those very reasons can be instructive for the critical observation of big data research and innovation.

Obtaining high-quality labelled data for training a classifier in a new application domain is often costly. Transfer Learning (a.k.a. “Inductive Transfer”) tries to alleviate these costs by transferring, to the “target” domain of interest, knowledge available from a different “source” domain. In transfer learning the lack of labelled information from the target domain is compensated by the availability at training time of a set of unlabelled examples from the target distribution. Transductive Transfer Learning denotes the transfer learning setting in which the only set of target documents that we are interested in classifying is known and available at training time. Although this definition is indeed in line with Vapnik’s original definition of “transduction”, current terminology in the field is confused. In this article, we discuss how the term “transduction” has been misused in the transfer learning literature, and propose a clarification consistent with the original characterization of this term given by Vapnik. We go on to observe that the above terminology misuse has brought about misleading experimental comparisons, with inductive transfer learning methods that have been incorrectly compared with transductive transfer learning methods. We then, give empirical evidence that the difference in performance between the inductive version and the transductive version of a transfer learning method can indeed be statistically significant (i.e., that knowing at training time the only data one needs to classify indeed gives an advantage). Our clarification allows a reassessment of the field, and of the relative merits of the major, state-of-the-art algorithms for transfer learning in text classification.

This book is a collection of seventeen papers which describe the impact that the ARIADNE project and its successor, ARIADNEplus (2019-2022) have had on the archaeological community, both in Europe and further afield. Each case study has been contributed by organisations involved in the ARIADNE Infrastructure who cover many countries from across Europe as well as Argentina and Japan. These papers were originally presented at the CAA Conference in Krakow, April 2019 and cover aspects such as data management, application of standards and guidelines, the use of CIDOC-CRM and Open Data to name but a few.

Discusses thew relations and dependencies between CoreTrustCertification and FAIR data objects principles.