dataesr/scientific-paragraphs-categorization huggingface dataset:
Database management technology thus advances beyond the routines of sorting and issuing that are familiar from historical bureaucracy. The latter is historicized into a trace element that can be interpreted in terms of the genealogy of data images. Documents from secret investigation files that were restrictively distributed behind closed doors become publicly accessible found objects, which can be copied losslessly and disembedded within a ›global archive,‹ redistributed infinitely, and thus also observed, tracked. Behind the archive's metadata functioning as a finding aid, there emerge ever more histories of traces, sedimented as growing data holdings of archive distribution made traceable. The nineteenth-century model of a visual crime scene calculation, which was meant to produce informational values beyond the immediate observable evidence-already contained in Bertillon's photogrammetric utopia of measuring, exploring, and storing photographically acquired photograms so as to be optimized for inquiries-reemerges here as a deferred archival calculus of computer regulated image banks.
Recent archival practices as they have developed especially in the last few decades in dealing with digital holdings also reorganize agency history stored in document form into an institutionally recalculated visibility depot. The logistical interface-including its most generally pragmatic functionality, namely »to relate any past document to the present of a here and now«365-follows standard protocols. Search terms are crosschecked with deposited keywords tacked on to historical images in the archive's meta-databases as tabular keys, which belong to files that have long since been closed from a forensic perspective. A search engine algorithm transports such de-bureaucratized material sortations to the user interface, emerges and organizes the agency's visual evidence on demand according to institutionally authorized categories of the relevant archival facility: according to the year, the place, the type of crime, according to photographic agents, formats, carrier material-or, potentially, as is the case in a Digital Humanities project at Yale University: according to a calculation of similarity created by a learning algorithm, which makes it possible to sort photographic collections at the level of the pixel according to »approximate nearest neighbors.
Astronomy is the paradigm case, with observations stretching in a chain from cuneiform tablets to papyrus rolls to parchment codices to paper books to digital database. Transcription is anything but mechanical: each moment of transcription is an occasion for commensuration of old and new disciplinary standards for reliable data-but also for loss of metadata as well as the detection of old errors or the insinuation of new ones  […]. But the new, handier archives do not supplant the old ones; layers of transcription simply accumulate. […] At any moment a query could send a researcher burrowing down through the layers of transcription in search of some overlooked detail that has suddenly become crucial. […] The archive is not and cannot be unchanging. But its usable past must be spliced and respliced with a mutable present in order to guarantee a usable future.
Everything becomes heavier when it has to be picked up and moved. […] However delicate, weightless, and ephemeral its subject matter, as soon as a painting must be shipped, it must be weighed and measured, packed and labelled. Postage must be paid. «385 Against the backdrop of this longstanding narrative of the »material mobility of pictures« (Roberts), the idea of a ›lossless‹ retro-digitization of historical photograph collections is clearly difficult to maintain, even setting aside the question of efficiency in passing down archivally relevant information that is bound to the analog original and for this very reason tends to become invisible in one-dimensional conversion (such as picture margins and frames, or inscriptions on the back, which at best turn up as »content« in meta-databases).
This occurs above all under the economic conditions of the global trade in images with archival images and stock photography,391 because the Bettmann Archive, which had grown to over two million photographs over the course of the twentieth century, was taken over by  Corbis in 1995. 392  There is also a conversion at the level of the institution: the image archive was transformed into an image database. Since then, the collection has been operated as a »stream of digital images«393-as a data stream whose flow is based on technological infrastructures of storage and transmission, which become additional elements of the material archival logistics of the photographic objects that continue to be preserved, rather than replacing these logistics. The analog originals are, on the one hand, deactivated in sub-zero cold storage394-that is, they are pulled from circulation and stored long-term in a secure iron ore mine of the Iron Mountain Corporation-but on the other hand they actively secure licensing claims.
395 This economically rationalized connection between photographic original and digital reproduction, archival depot and database, at once takes on a kind of bridging function between the materialities involved, binding the visibility and accessibility of a data image-commodified in many dimensions not least through the value-added chains of metadata collections-to the archival calculations of an inaccessible storage infrastructure such as that of the Iron Mountain Corporation. 396 The distributed materiality of an image database grounded in a computer network-starting with server farms, fiber optic cables, screen technologies-extends to the use of energy and raw materials, which routinely accumulate with the conservational storage and management of photographic objects. 393 Blaschke, Banking on Images, 165.
525 Ibid. technology »that aim to combine, connect, reformat, or rescale information« are generally employed. 526 Secure storage is not a passive process, but a »permanent restructuring«527 that continually produces new differences between archival objects. The archive preserves materials by inscribing itself in them. Access to the archive-which for its part is non-volatile, designed in anticipation of future use-occurs via the production of metadata in a transcription process that transmits the archival arrangement as a code to be called up. As has already been explained regarding digital databases and streaming technologies, this general archival traffic form is tied to the standards of information management in media technologies. The distribution of archival data proceeds according to protocols, follows administrative rules.
534 As justifiable as this skepticism may be in many respects, it is also noteworthy that there is now a whole series of institutional archival agents developing professional digital agendas. Even in the debate surrounding the self-understanding of archive studies, there has recently been increasing support under the umbrella term »digital historiography« for a shared evaluation of the best practices of genuinely digital archival processes,535 which have long been the reality in practice. Instead of simply supplying digital reproductions generated within the archive to the dominant portals of commercial providers, institutions such as the USHMM are increasingly maintaining in-house databases and platforms, which have to align the archival material that is made accessible in this way with digital standards of data management technology, rules of protocol, and formats like JPEG and MPEG, but nevertheless provide it with an institutionally secure locatability.
Between 1996 and 2002 the Shoah Foundation Visual History Archive secured 547 Blaschke, Banking on Images, 117. 548 »The Google search engine and commercial social media platforms such as Facebook, Twitter, YouTube and Instagram continually generate data from the interactions of millions of users. Access to data/tools is sold to marketeers and is employed to target, predict and manage these platforms' users. So-called application programming interfaces (APIs) make parts of vast databases accessible to third parties, including researchers. Concurrently, an industry has emerged whose companies collect, sell, combine and analyse data sets for all kinds of purposes, ranging from targeted advertising and market research to credit ratings, risk assessments and mass surveillance. The collection of data from massive data sets also yields a glimpse of a future when certain sorts of businesses will thrive on the exploitation of vast amounts of stored information« (Karin van Es, Mirko Tobias Schäfer, »Introduction: New Brave World,« in: van Es, Schäfer (eds.
), The Datafied Society. Studying Culture through Data, Amsterdam: Amsterdam University Press, 2017, 13-24, here: 14). 549 The background is explained in: Mike Masnick, »Holocaust History Preserver Shoah Foundation's Patents Being Used to Sue Google, Facebook, Hulu, Netflix, Amazon,« TechDirt (blog), March 14, 2012. https://www. techdirt. com/articles/20120310/01381118066/ holocaust-history-preserver-shoah-foundations-patents-being-used-to-sue-googlefacebook-hulu-netflix-amazon. shtml. ten patents related to database management of multimedia content. Some of these were adopted and further developed by the industry, as Todd Presner contends in a detailed examination of the IT architecture of the most extensive video archive of witnesses in the world: »Some of the patents-such as the ›Digital Library System‹ and ›Methods and Apparatus for Management of Multimedia Assets‹-have been referenced by more than seventy other patents from companies such as Xerox (for developing a browser-based image storage and processing system) and Microsoft (for semiautomatic annotation of multimedia objects).
«553 In the final analysis, this conceals a fundamental conflict that the institutional organizations have to negotiate in particular when engaging with the digitization dynamics of social media, which they de facto conform to and support, while simultaneously attempting to resist them as archival authorities and gatekeepers: »[…] institutions of Holocaust memory  […]  have played an admirable, even pioneering role in digitizing the Holocaust culture and creating searchable databases, but they have kept a fearful distance from truly open, interactive, web-based media formats or exposing their data to the World Wide Web. In this regard, digital Holocaust Culture is at odds with popular digital culture whose users are driven by the ability to shape content in the process of consumption. «554 Hierarchies among archival holdings, their taxonomic classification, the internal coherence of a collection's unity tend to unravel here in favor of increased mobility and uncontrollable operations of recontextualization.
574 The most advanced discussion here seems to be taking place in art history-from the question of machine readability of images (such as for automated keywording and comparative style analysis) to those visual infographics that the Digital Humanities itself creates as products of its own data visualization practices; cf. These videos are able to be used operationally as database material in the first place, however, above all because human agents performed a manual indexing of the entire collection. In the course of this work, an institutionally controlled, consistent thesaurus was generated according to prescribed Humanities (cf. https://www. avindhsig. wordpress. com). An interesting »Distant Viewing TV« approach focuses on surveying the ›big data‹ of American television history: »Distant Viewing TV (distanttv.
Presner describes this enormously time-consuming process of datafication as an operation of subtraction, which abstracts from certain information in the audiovisual material because it cannot extract it: The result is a massive data ontology that has expelled the latent content, the performative, the figural, the subjunctive, the tone of questioning and doubt, the expressiveness of the face, and the very acts of telling (and failing to tell) that mark the contingency of all communication. […] In other words, what goes missing in the ›pursued objectivity‹ of the database is narrativity itself […] Of course, this is because databases are not narratives or people telling stories; they are formed from data (such as keywords) arranged in relational tables that can be queried, sorted, and viewed in relation to tables of their data.
577 On the other hand, the indexing of the archival database also adds informational resources in the form of metadata, which, in addition to nonlinear access modes and equally accelerated and granularly resolvable search processes, facilitate significantly expanded sorting capabilities, allowing the entire holdings to be scalable in new ways and potentially intelligible by means of digital humanities tools of data visualization: »seeing connections that a human eye could not possibly detect or track. «578 The thesaurus contains a metadata network of words comprising around 50,000 different keywords, which is not only able to search for individual keywords, but can also be visualized as network graphs showing the relations between data sets-an algorithmic distant reading of the material meant to reveal patterns and provide a visual way to grasp, if not meaningful connections, at least the centers and peripheries of the keywording.
579 The fact that this database-driven quantification also gives rise to ethically problematizable modes of ›distant‹ readings-such as when survivors of the Shoah become flattened as »data points« and pixels of rasterized data visualizations-can be offset, in Presner's view, by a kind of computer driven big-data ›égalité‹: »[C]omputational or algorithmic analysis can be ethical precisely because it takes into account the fullness of the archive insofar as all the indexed data related to the narrative of every survivor is part of the analysis. «580 Notwithstanding such archive-ethical evaluations, there is the additional question of the incipient performance parameters of algorithmic image recognition beyond manually constructed networks of words, which point the way for automated, »non-human storage readings« (Wolfgang Ernst), but are primarily intended to make it possible to filter the ambient information overload that has arisen due to the constant proliferation of digitally ›born‹ stored material.
In this vision, more data, stored digitally, processed by computers (and then, however, visualized again for people pursuing academic agendas), recalculate a world history of culture that is inclusive of the peripheries of the long tail and is not only based on a broader empirical database, but also more objective in terms of its processing because it is less dependent on individual or institutionally reproduced interpretations and their dependencies on a certain location, instead detecting divergent patterns without any previously invested qualitative bias. At least, that is the promise. Popularized in an application that traces trajectories of the history of word usage through historical space, such as Google's NGram Viewer584-which in German-speaking areas indicates a curve for the example term »Holocaust« that reached its peak in 1985, the year that SHOAH was released, and currently has almost sunk again to the significantly lower level of around 1961-the problem, from the perspective of visual theory, is a priori much more complex: But between the endless columns of figures and the shapes that a human gaze recognizes there is a gaping chasm.
Google's reCAPTCHA587 ultimately drew the reverse conclusion for the benefit of their own digitization plans, taking the millions of daily verifications that users are not robots588 and applying them to scanned words that cannot be processed correctly by text recognition software. While serial image content recognition puzzles as well as video and audio captchas continue to be used to protect against automated spambots,589 Google now prefers to feed street signs and house numbers into the reCAPTCHA widget in order to have an army of volunteers, working anonymously, correct the deficits in the database of its mapping service. Lisa Gitelman has more closely examined this model of positioning digital images as resistant barriers to ubiquitous machine readability in her study on the text image pages of Portable Document Files: If it is a commonplace today that words and images and sounds are closer together than they have ever been before-now that all of them come as data strings, in bits and bytes-nonetheless there are important ways that ›as computational data structures, images differ radically and fundamentally from electronic text.
Thanks to this technology we can search directly for image contents and not, as has primarily been the case until now, for image captions. 613 However, relatively simple crosschecks such as the classification of negative images (entirely unproblematic for human agents), still produce rather uninspiring results. 614 But from the viewpoint of human perceptual routines, what an image contains, what it represents or symbolizes, what it refers to, how iconic and indexical components flow into the aesthetic process of perceiving ›something‹ (as something), will only be able to be simulated algorithmically in reductionist form, even in the future. Even if the effort to classify and identify objects represented in an image has by now achieved error rates under 2%, in the case of the ImageNet database, when it comes to more demanding tasks, it is still the case that: »This doesn't mean an algorithm knows the properties of that object, where it comes from, what it's used for, who made it, or how it interacts with its surroundings.
«632 The fact that the USHMM is quite interested in epistemologically ambitious, more invasive digital tools of archival evaluation and heuristics-that is, it does not insist on a fundamental primacy of ›analog‹ processing and classical ›hermeneutic‹ interpretation-is demonstrated by a research project that started in 2007 under the title »Geographies of the Holocaust,« which sought to use data-based processes of geovisualization to explore the scope of a »spatial turn« in Holocaust research. 633 The approach of algorithmically processing geographical information that is related, for instance, to the system of concentration and extermination camps,634 death marches,635 the mass murders carried out by the Einsatzgruppen,636 or to the creation of Jewish ghettos637-in short, this is a matter of translating spatially oriented historical information into dynamic cartographic representations, virtually modelled environments, and other interactive modes of visualization used in Geographical Information Science (GIS)-conceives of the extensive collection of digitized texts and image documents at the USHMM Archive as database material from which patterns are to be extracted through quantitative analyses: »[…] spatial analysis and geovisualization can complement and help specify the humanistic understanding of space and place by exploring and quantifying relationships among things and people to discover and visualize spatial patterns of activity.
It has not gone unnoticed, at least among the project participants, that due to the origin of the documents, which should always be critically considered on a meta-historiographic level-and in this context, with very few exceptions, concerns precisely the photographic and film sources of the Nazi period-there is also the danger of reproducing the »totalizing gaze« of the historical perpetrators in the presumption of transparency and clarity of data visualization: »[…] we see the act of mapping as, in part, critical engagement with the world envisioned by the perpetrators. «642 The GIS data images are fundamentally digital interpretations, mediated by software, of an archive that is operatively interpreted already in the course of compiling the database-the archive is datafied selectively, in a way that is driven by specific interests, if only because the potentially informative contents of an archival photograph can neither be exhaustively indexed (as mentioned above in discussing the keywording of the Visual History Archive of the Shoah Foundation) nor quantified without some loss.
It is not just that the stream-its volumes, the concrete information-technological reification of its computer-network-based connecting operationsis always channeled differently. The image transported through this stream, which has generally speaking become trackable in real time, is likewise not truly stable, but adaptively modulated, and thus continually adapting to registered datasets and infrastructural circumstances: by taking account of the available connection qualities, geolocational markings, accumulated tracking and profile data of the clients sending server requests, to the variable technological-situative capacity of the end devices waiting on the horizon of these operations. The distributed image comes into existence in relation to such calculated feedback loops, which constantly create more data that require processing and are effectively not distinct from the image, but part of it, continually expanding the information it comprises.
In this sense, objects will become their own archive. «694 The sensors that are distributed for purposes of observing the environment collect data that is fused, secured, and algorithmically processed in superordinate storage units-which Christoph Engemann and Florian Sprenger have highlighted as a question about the relationship between distribution and centralization: »Is the gadgets' intelligence local or are the local gadgets just interfaces of a remote, potentially centralized ›intelligence‹?«695 Data transport, in any case, remains at the level of sensors communicating among one another only in exceptional cases, which is why, following Katherine Hayles, they can be understood as »sub-cognizers«: »[…] distributed cognition concentrates on creating complex interrelated systems in which small sub-cognizers that perform within a very limited range of operation are combined with readers that interpret that information, which in turn communicate with relational databases that have the power to make correlations on much wider (and extensible) scales.
Those algorithms can pore over millions of signs and storefronts without getting tired. By hoovering up vast amounts of information visible on the world's streets-signs, business names, perhaps even opening hours posted in the window of your corner deli-Google hopes to improve its already formidable digital mapping database. […] Earlier this year […] Google's cloud division showed they could predict income, race, and voting patterns for US cities with software that logs the make, model, and year of cars in Street View Photos. «704 The trajectory of the geomedial indexing of real topography thus no longer only aims to include ever more spaces-for whose expansive coverage the provider now puts cameras in backpacks, screws them onto trolleys, tricycles, and snowmobiles in order to measure hiking trails, museums, car-free parks, and alpine terrain705-but increasingly seeks to deepen and consolidate the information that can be obtained via the acquisition modes of visual capture: »Sensor networks […] always transform places, facts, and circumstances into machine-readable code.
«706 To this end, numerous monitoring and tracking systems are based on so-called smart cameras, which localize and identify objects, persons, environmental aspects, making it possible to transmit them as data points. 707 In the Internet of Things, intelligent cameras are special (and especially intrusive) things insofar as they are able to capture other things (and processes) locally without their active participation, store them visually and link them with an address. And it is precisely ›unnetworked‹ things that thus become ›readable,‹ things that (more or less intentionally) do not carry a transponder and yet in the course of their visual detection nonetheless appear in the global space of IoT addressing, namely as image-based sensor data and in relation to the position of ›space-consuming‹ image sensor acquisitions.