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Research questions, abstract problems – a round table on Citizen Science

February 26, 2017

I recently participated in a round-table discussion entitled “Impossible Partnerships”, organized by The Cultural Capital Exchange at the Royal Institution, on the theme of Citizen Science; the Impossibe Partnerships of the title being those between the academy and the wider public. It is always interesting to attend citizen science events – I get so caught up in the humanities crowdsourcing world (such as it is) that it’s good to revisit the intellectual field that it came from in the first place. This is one of those blog posts whose main aim is to organize my own notes and straighten my own thinking after the event, so don’t read on if you are expecting deep or profound insights.


Crucible of knowledge: the Royal Institution’s famous lecture theatre

Galaxy Zoo of course featured heavily. This remains one of the poster-child citizen science projects, because it gets the basics right. It looks good, it works, it reaches out to build relationships with new communities (including the humanities), and it is particularly good at taking what works and configuring it to function in those new communities. We figured that one of the common factors that keeps it working across different areas is its success in tapping in to intrinsic motivations of people who are interested in the content – citizen scientists are interested in science. There is also an element of altruism involved, giving one’s time and effort for the greater good – but one point I think we agreed on is that it is far, far easier to classify the kinds of task involved, rather than the people undertaking them. This was our rationale in that 2012 scoping study of humanities crowdsourcing.

A key distinction was made between projects which aggregate or process data, and those which generate new data. Galaxy Zoo is mainly about taking empirical content and aggregating it, in contrast, say, to a project that seeks to gather public observations of butterfly or bird populations. This could be a really interesting distinction for humanities crowdsourcing too, but one which becomes problematic where one type of question leads to the other. What if content is processed/digitized through transcription (for example), and this seeds ideas which leads to amateur scholars generating blog posts, articles, discussions, ideas, books etc… Does this sort of thing happen in citizen science (genuine question – maybe it does).  So this is one of those key distinctions between citizen science and citizen humanities. The raw material of the former is often natural phenomena – bird populations, raw imagery of galaxies, protein sequences – but in the latter it can be digital material that “citizen humanists” have created from whatever source.

Another key question which came up several times during the afternoon was the nature of science itself, and how citizen science relates to it. A professional scientist will begin an experiment with several possible hypotheses, then test them against the data. Citizen scientists do not necessarily organize their thinking in this way. This raises the question: can the frameworks and research questions of a project be co-produced with public audiences? Or do they have to be determined by a central team of professionals, and farmed out to wider audiences? This is certainly the implication of Jeff Howe’s original framing of crowdsourcing:

“All these companies grew up in the Internet age and were designed to take advantage of the networked world. … [I]t doesn’t matter where the laborers are – they might be down the block, they might be in Indonesia – as long as they are connected to the network.

Technological advances in everything from product design software to digital video cameras are breaking down the cost barriers that once separated amateurs from professionals. … The labor isn’t always free, but it costs a lot less than paying traditional employees. It’s not outsourcing; it’s crowdsourcing.”

So is it the case that citizen science is about abstract research problems – “are golden finches as common in area X now as they were five years ago?” rather than concrete research questions – “why has the population of golden finches declined over the last five years?”

For me, the main takeaway was our recognition citizen science and “conventional” science is not, and should not try to be, the same thing, and should not have the same goals. The important thing in citizen science is not to focus on the “conventional” scientific out comes of good, methodologically sound and peer-reviewable research – that is, at most, an incidental benefit – but on the relationships between professional academic scientists and non-scientists it creates; and how these can help build a more scientifically literate population. The same should go for the citizen humanities. We can all count bird populations, we can all classify galaxies, we call all transcribe handwritten text, but the most profitable goal for citizen science/humanities is a more collaborative social understanding of why doing so matters.

Tales of many places: Data Infrastructure for Named Entities

January 28, 2017

The use of computational methods for ancient world geography are still very much dominated by the URI based gazetteer. These powerful and flexible reference lists, trail-blazed by projects such as the Pleaides and Pelagios projects, allow resources to be linked by common spatial referents they share. However, while computers love URIs unconditionally, the relationship they have with place is more ambivalent: a simmering critical tension which has given rise to what we call the Spatial Humanities. This critical tension between the ways humanists see place and the way computers deal with it has highlighted important geo-philosophical principles for the study of the ancient world. For me, one of the most important of these is the principle that places as entities which exist in some form of human discourse such as text, and places as locations which can be situated within the (modern) framework of latitude and longitude, must be separated. Gazetteers allow us to do this, which is why they are so important.

My 2017 kicked off with a meeting in a snowy Leipzig (see above), Digital Infrastructure for Named Entities Data, which sought to further problematize the use of these computational methods to support the investigation of past place. As might be expected of an event driven by Pelagios, the use of URI-based gazetteers featured heavily. The Pleagios Commons was presented by the event’s organizer, Chiara Palladino, as both a community and an infrastructure. It centres on the general concept of “place”, and clusters of material which share the same properties. Pelagios may be seen, Chiara said, as the “Connecting structure behind the system”, aiming at a decentralized and federated approach to provide maps which combine geographical, chronological and biographical data. The event’s exploration of this key, overarching concept highlighted three main issues:

  1. Hodological views of past space

Ancient geographies should be seen in the context of hodological space – as pathways through the world, not points on top of it. Hodology, a concept discussed by several speakers, views space from the perspective of experience and mobility.  Hodological space concerns the tension between intent, possibility, and real (embodied) experience. It is frequently bidimensional, as evidenced in the example given by Sergio Brilliante, of western Crete in the Periplus (mariner’s account) of Pseudo-Skylax, which displayed the best route for travel, not the cartographically optimal one. I was struck by the modern parallel of the WWII Cretan “runner”, George Psychoundakis, who, in his riveting account of his role in the resistance in Crete, measured the distances over which his wartime missions took him on foot by the number of cigarettes he smoked on the journey.

It was noted that in Arabic scripts, geographic areas are generally not measured, except for the purposes of agriculture. A hodological approach was described as a counterpoint to “scientific method” in geography: one can frame geographic accuracy either in terms of “accurate” Cartesian maps, or as the consistent application of geo criteria.

  1. Name neutrality

Like any form of humanistic space, hodological space is never neutral. Place references in humanistic discourse are often the result of mutivocal, multi-authorial and partial accounts; and the workshop bore a heavy emphasis on this. Many surviving Classical texts are written by Greek or Athenian authors, so there is a strong Athenocentricism and Graecocentricism to them. Non-Greeks tend to be “hidden”. This seemed to me somewhat reminiscent of the Mercator projection (which most modern Web cartography relies upon), which “shrinks” mid-latitude countries and accentuates those at higher and lower latitudes, thus visually privileging the developed world at the expense of the developing countries (who could forget the scene in the West Wing when the Cartographers for Social Equality regale CJ Cregg on the subject). Similarly toponyms are not neutral, a problem which the separating of platial concept and platical location can help address. Our own Heritage Gazetteer of Cyprus is attempting to do this through application of “attestations” of agnostic geographic entities, an approach also being used by  Sinai Rusinek in her Hebrew gazetteer. Similarly Thomass Carlson described the gazetteer, which links cultural heritage to texts in the Syriac language. Carlson noted that names are a linguistic strategy not absolute entities.  The nature of names means that disambiguation does not work consistently. Even an expert reader might not be able to determine out what exactly a toponym refers to. While many ancient world gazetteers rely on URIs, URIs can never replace unambiguous linguistic names.  Context free URIs, which the gazetteer community has long relied on, are no longer sufficient to represent non-neutral humanistic place.

  1. Ontological (mis)alignment

Finally, a point well made by Maurizio Lana was that geographical ontologies must be bottom up to be truly representative. In his presentation he described the Geolat project, which deals with the use of spatial ontologies, and again frames names as cultural patterns. There is a driving force which pulls readers towards names, to what is easily identifiable. It is necessary to separate the study of entities from naming. This means that an ontology that is developed for one purpose might not be suitable for others. For example, in the Heritage Gazetteer of Cyprus we make use of Geonames as a means of locating archaeological entities, but the Feature Type list of Geonames is not nearly detailed or granular enough to adequately describe the different kinds of features which exist in the gazetteer. Therefore where geo-ontologies have come from, and why they do not align, can lead to very interesting conclusions about the nature of historical spatial structures.

As often, there was a great background discussion with colleagues who were not physically present via Twitter, which I have captured as a raw Storify. Among the most engaging of these discussions was an exchange as to whether a place had to have a name, or rather whether place acts as a conceptual container for events (in which case what are they?). My previous belief in the former position found itself severely tested by this exchange, and the papers which touched on hodological views of the past provided reinforcements. I think I am now a follower of the latter view. Thank you to those Twitter friends for this, you know who you are.

Talking to ourselves: Crowdsourcing, Boaty McBoatface and Brexit

October 30, 2016

Back in April, I gave a talk at a symposium entitled Finding New Knowledge: Archival Records in the Age of Big Data in Maryland called “Of what are they a source? The Crowd as Authors, Observers and Meaning-Makers”. In this talk I made the point that 2016 marked ten years since Jeff Howe coined the term “crowdsourcing” as a pastiche of “outsourcing” in his now-famous Wired piece. I also talked about the saga of “Boaty McBoatface”, then making headlines in the UK. If you recall, Boaty McBoatface was the winner, with over 12,000 votes, of the Natural Environmental Research Council’s open-ended appeal to “the crowd” to suggest names for its new £200m polar research ship, and vote on the suggestions. I asked if the episode had anything to tell us about where crowdsourcing had gone in its first ten years.  Well, we had a good titter at poor old NERC’s expense (although in fairness I did point out that, in a way, it was wildly successful as a crowdsourcing exercise – surely global awareness of NERC’s essential work in climatology and polar research has never been higher). In my talk I suggested the Boaty McBoatface episode was emblematic of crowdsourcing in the hyper-networked age of social media. The crowdsourcing of 2006 was based, yes, on networks, enabled by the emerging ubiquity of the World Wide Web, but it was a model where “producers” – companies with T-Shirts to design (Howe’s example), astrophysicists with galaxy images to classify (the Zooniverse poster child of citizen science), or users of Amazon Mechanical Turk put content online, and entreated “the crowd” to do something with it. This is interactivity at a fairly basic level. But the 2016 level of web interactivity is a completely different ball game, and it is skewing attitudes to expertise and professionalism in unexpected and unsettling ways.

The relationship between citizen science (or academic crowdsourcing) and “The Wisdom of Crowds” has always been a nebulous one. The earlier iterations of Transcribe Bentham, for example, or Old Weather, are not so much exercises in crowd wisdom, but perhaps “crowd intelligence” – the execution of intelligent tasks that a computer could not undertake. These activities (and the numerous others I examined with Mark Hedges in our AHRC Crowd-Sourcing Scoping Survey four years) ago all involve intelligent decision making, even if it is simply an intelligent decision as to how a particular word in Bentham’s papers should be transcribed. The decisions are defined and, to differing degrees, constrained by the input and oversight of expert project members, which give context and structure to those intelligent decisions: a recent set of interviews we have conducted with crowdsourcing projects have all stressed the centrality of a co-productive relationship between professional project staff and non-professional project participants (“volunpeers”, to use the rather wonderful terminology of the Smithsonian Transcription Center’s initiative).

However events since April have put the relationship between “the crowd” and “the expert” on to the front pages on a fairly regular basis. Four months ago, the United Kingdom voted by the small but decisive margin of 51.9% to 48.1% to exit the European Union. The “Wisdom of [the] Crowd” in making this decision informed much of the debate in the run up to the vote, with the merits of “crowd wisdom” versus “expert wisdom” being a key theme. Michael Gove, a politician who turned out to be too treacherous even for a Conservative party leadership election, famously declared that “Britain has had enough of experts”. It is a theme that has persisted since the vote, placing the qualification obtained from the act of representing “ordinary people” through election directly over, say, the economic expertise of the Governor of the Bank of England:

Is this fault line between the expert and the crowd real, a social division negotiated by successful academic crowdsourcing projects, or is it merely a conceit of divisive political rhetoric?  Essentially, this is a question of who “produces” wisdom, and who “consumes” it, and in which direction do the cognitive processes which lead to decision making flow (and which way should they flow?). This highlights the nebulous and inexact definition of “the crowd”. It worked pretty well ten years ago when Howe wrote his article, and translated easily enough into the “crowd intelligence” paradigm of the late 2000s, and early academic crowdsourcing. In these earlier days of Web 2.0, it was still possible to make at least a scalar distinction between producers and consumers, between the crowd and the crowdsourcer (or the outsourcer and organization outsourced to, to keep with his metaphor); even though the role of the user as a creator and a consumer of content was changing (2006 was, after all, also the year in which Facebook and Twitter launched). But how about today? This is a question raised by a recent data analysis of Brexit by the Economist. In this survey of voters’ opinions, it emerges that over 80% of Leave voters stated that they had “more faith in the wisdom of ordinary people than the opinions of experts”. I find the wording of this question fascinating, if not a little loaded – after all, is it not reasonable to place one’s faith in any kind of “wisdom” than an “opinion”? But the implicit connection between generally a generally held belief and (crowd) wisdom is antithetical to independent decision making. This is crucial to any argument that “crowd wisdom” leads to better decisions – such as leaving the EU. In his 2004 book, The Wisdom of Crowds: Why the Many Are Smarter Than The Few, James Surowiecki talks of “information cascades” being a threat to good crowd decisions. In information cascades, people rely on ungrounded opinions of others that have gone before: the more opinions, the more ongoing, self-replicating reinforcement. Surowiecki says:

Independence is important to intelligent decision making for two reasons. First, it keep (sic) the mistakes that people make from becoming correlated … [o]ne of the quickest ways to make people’s judgements systematically biased is to make them dependent on each other for information. Second, independent individuals are more likely to have new information rather than the same old data everyone is already familiar with.

According to the Economist’s data, the Brexit vote certainly has some of the characteristics of information cascade as described by Surowiecki: many of those polled who voted that way did so at least in part of their faith in the “wisdom of ordinary people”. This is the same self-replicating logic of the NERC boat naming competition which led to Boaty McBoatface; and a product of the kind of closed-loop thinking which social media represents. Five years ago, the New Scientist reported a very similar phenomenon with different kinds of hashtags – depending on the kind of community involved, some (#TeaParty in their example) develop great traction among distinct groups of mutual followers with individuals tweeting to one another, whereas others (#OccpyWallStreet in this case) attract much greater engagement from those not already engaged. It’s a pattern that comes up again and again, and surely Brexit is a harbinger of new ways in which democracy works.

It is certainly embodies and represents the information cascade as one key aspect that Surowiecki would have us believe is not the Wisdom of Crowds as a means of making “good” decisions. There may be those who say that to argue this is to argue against democracy, that there are no “good” or “bad” decisions, only “democratic” ones.  That is completely true of course; and not for a moment here do I question the democratic validity of the Brexit decision itself. I also happen to believe that millions of Leave voters are decent, intelligent, honourable people who genuinely voted for what, in their considered opinion, was the best for the country. But since the Goves of the world made a point and a virtue of placing the Leave case in opposition to the “opinions of experts”, it becomes legitimate to ask questions about the cognitive processes which result from so doing. And the contrast of this divisive rhetoric with those constructive and collaborative relationships between experts and non-experts evident from academic crowdsourcing could not be greater.

But that in turn makes one ask how useful the label “expert” really is. What, in the rhetoric of Gove, Davies etc, actually consigns any individual person to this reviled category? Is it just anyone who works in a university or other professional organization? Who is and who is not an expert is a matter of circumstance and perspective, and it shifts and changes all the time. Those academic crowdsourcing projects understand that, which is why they were so successful. If only politics could take the lesson.


Quantitative, Qualitative, Digital. Research Methods and DH

September 21, 2016

This summer, there was an extensive discussion on the Humanist mailing list about the form and nature of research methods in digital humanities. This matters, as it speaks in a fundamental way to a question whose very asking defines Digital Humanities as a discipline: when does the development and use of a tool become a method, or a methodology? The thoughts and responses this thread provoked is testament to the importance of this question.  While this post does not aim to offer a complete digest of this thread, I wanted to highlight a couple of key points that emerged from it. A key theme was in one exchange, which concerned the point in any research activity which employs digital tools at which human interpretation enters. Should this be the creation of tools, the design of those tools, the adding of metadata, the design of metadata, and so on. If one is creating a set of metadata records relating to a painting with reference to “Charles I” (ran an example given by Dominic Oldman), the computer would not “understand” the meaning of any information provided by the user, and any subsequent online aggregation would be similarly knowledge-agnostic.

In other words, where should human knowledge in the Digital Humanities lie? In the tool, or in the data, or both?

Whatever the answer, the key aspect is the point at which a convention in the use of a particular tool becomes a method. In a posting to the thread on 25th July, Willard McCarty stated:

The divergence is over the tendency of ‘method’ to become something fixed. (Consider, for example, “I have a method for doing that.” Contrast “What if I try doing this?”).

“Fixedness” is essential, and it implies some form of critically-grounded consensus among those using the method in question. This is perhaps easier to see in the social sciences that it is in the [Digital] humanities. For example, how would a classicist, or an historian, or a literature scholar approaching manuscripts through the method of close reading present and describe that method in the appropriate section of the paper? How would this differ from, say the equivalent section in a paper by a social scientist using grounded theory to approach a set of interviews? While there may be no differentiation in the rigour or quality of the research, but one suspects the latter would have a far greater consensus – and body of methodological literature – to draw upon to describe grounded theory, than the former would to describe close reading.

Many discussions on this subject remain content-focused still. What content means in itself has assumed a broader aspect. Whereas “content” in the DH may once have meant digitized texts, images and manuscripts, surely now it also includes web content such as tweets, transient social media, and blog posts such as this one. It is essential to continue to address the DH research life-cycle, as based on content, but I still but we need to tackle explicitly methodology (emphasis deliberate), in both its definition and epistemology, and defined by the presence of fixity, as noted by McCarty.” Methodological pluralism”, the key theme of the thread on Humanist this summer, is great, but for there to be pluralism, there must first be singularity. As noted, the social sciences have this in a very grounded way. I have always argued that the very terms “quantitative” and “qualitative” are understood, shared, written about and, ultimately, used in a much more systematic way in the social sciences than in the (digital) humanities, where they are often taken to express a simple distinction between “something than can be computed versus something that cannot”.

I am not saying this is not a useful distinction, but surely the Humanist thread shows that the DH should at least deepen the distinction to mean “something which can be understood by a computer versus something that cannot”.

I would like to pose three further questions on the topic:

1) how are “technological approaches” defined in DH – e.g. the use of a tool, the use of a suite of tools, the composite use of a generic set of digital applications?

2) what does a “technological approach” employing one or more tools enable us to do?

3) how is what we do with technology a) replicable and b) documentable?

Bolton Abbey, North Yorkshire

August 14, 2016


Pencil sketch, mostly harder pencils. August 2016.

Question: (how) do we map disappeared places?

September 2, 2015

A while ago I asked Twitter if there was a name for a long period of inactivity on blogs or social media. Erik Champion came up with some nice suggestions

which raise questions about whether blogging represents either the presence or absence of ‘loafing’; and  replied with a certain elegant simplicity:

Anyway, having been either ‘living’ or ‘loafing’ a lot these last few months, this is my first post since February.

I want to ask another question, but 140 characters just won’t cut it for this one. How does one represent a place in a gazetteer, or any other kind of database or GIS for that matter, which no longer exists? To take an example of ‘Mikro Kaimeni’, a tiny volcanic island in the Santorini archipelago mapped and published by Thomas Graves in his 1850 military survey of the Aegean:


Some sixteen years after this map was made, Santorini erupted and Mikro Kaimeni combined with the large central island, Neo Kameni:


Can such places be hermenutic objects by virtue of the fact that they are representing in the human record (in this case Graves’s map), even though they no longer exist as spatial footprints on the earth’s surface? I suppose they have to be. The same could go for fictional places (Middle Earth, Gotham City etc). What kind of representational issues does this create for mapping in the humanities more generally?

Digital Destinations: What to do with a digital MA

February 16, 2015

King’s Careers & Employability gathers statistics on graduate employment destinations for the Higher Education Statistics Agency (HESA).  Such data is available for the Department of Digital Humanities’ cohorts for the three academic years between 2010/11 and 2012/13, that is to say graduates of the MA Digital Humanities, the MA Digital Asset and Media Management and the MA Digital Culture and Society of those years. This information, which includes the sectors and organizations that alumni enter, and their job titles, is gathered from telephone interviews and online surveys six months after their graduation. Of those who graduated in 2012/13, 93.8% were in full time work, with the remainder undertaking further study in some form. 38.4% of those approached did not reply, or refused to provide answers. A certain health warning must therefore be attached to the information currently available; and in the last couple of years the numbers on all three programmes have grown considerably, so the sample size is small compared to the numbers of students currently taking the degrees. But in surveying the data that we do have, it is possible to make some preliminary observations.

Firstly, the good news is that all of our graduates from 2012/13 who responded to the survey were in employment, or undertaking further studies, within those six months. In the whole three-year period, MA DAMM graduates entered the digital asset management profession via corporations including EMAP, and the university library sector (Goldsmiths College).  They also entered managerial roles at large corporations including Coca-Cola and the Wellcome Trust. Digital media organizations feature strongly in MA DCS students’ destinations, with employers including NBC, Saatchi and Saatchi and Lexisnexis UK, with roles including design, social media strategy and technical journalism. Librarianship is also represented, with one student becoming an Assistant Librarian at a very high-profile university library. Others appear to have gone straight in to quite senior roles. These include a Director of Marketing, PR and Investments at an international educational organization, a Senior Strategy Analyst at a major international media group, and a Senior Project Manager at a London e-consultancy firm. One nascent trend that can be detected is that graduates of MA DH seem more likely to stay in the research sector.  Several HE institutions feature in MA DH destinations, including Queen Mary, the University of Oslo, Valencia University, the Open University and the University of London, as well as King’s itself; although graduates entering these organizations are doing so in technical and practical, roles such as analysts and e-learning professionals, rather than as higher degree research students. A US Office of the State Archaeologist, Waterstones and Oxford University Press also feature, reflecting (perhaps) MA DH’s strengths in publishing and research communication. Many of the roles which MA DH graduates enter are specialized, for example Data Engineer, Conservator Search Engine Evaluator, although more junior managerial jobs also figure.

As noted, the figures on which these observations are based must be treated with some caution; and doubtless as data for 2013/4 and beyond become available, clearer trends will emerge from across the three MA programmes. Currently, there is a range of destinations to which our graduates go, spanning the private and research sectors, and there is much overlap in the types of organizations for which graduates from all three programmes work and the roles they obtain. However, two broad conclusions can be drawn. Firstly, that all three programmes offer a range of skills based on a critical understanding of digital theory and practice which can be transferred to multiple kinds of organization/role. Secondly our record on full employment shows that there is growing demand for these skills, and that those skills are becoming increasingly essential to both the commercial and research sectors.

Of Historic Units and Cypriot heritage

December 15, 2014

The team behind the Heritage Gazetteer of Cyprus were in Nicosia last week, presenting a near-final form of the project to an audience of experts in Cypriot history and archaeology. The resource the project has been tasked by the A. G. Leventis Foundation to produce is very nearly complete, and will be launched to the world in January 2015.

The HGC has always been about the names of places, and how these names change over time. As I have blogged about previously, and as we outlined in our presentation to the International Cartographic Association’s Digital Approaches workshop in Budapest in September, this name-driven approach, which is based on three layers of data – modern toponyms, ‘Historical Units’ and ‘Archaeological Entities’ represents the limits of the current project. However what it cannot do raises important intellectual questions about how digital representations of place are organized and presented online. The aim of this post is to capture some of these questions, particularly with regard to our ‘Historic Unit’ data layer.

To recap the definitions: a modern toponym is, quite simply, the official name currently in use, and the only data sources for this are official ones – currently in the form of the Complete Gazetteer of Cyprus (Konstantinides and Chrisotodolou 1987). In our presentation last Thursday, we reiterated our definition of an HU as:

“Entities of substantial geographical extent and significance, such as towns, archaeological sites and the extents of kingdoms”

And AEs as:

“A discrete feature, with a distinct spatial footprint, formed in a definable period”

This definition of an AE is relatively clear. Most importantly, the reference to a ‘distinct spatial footprint’ means that it is related to mappable feature, which is extrinsic to any definition in the HGC data structure. However, a colleague at the meeting expressed the general view when he described HUs as being “the most interesting aspect, but also the most problematic”. Currently, they are defined on the map as a polygon, drawn by the user when they create the HU record. In some cases, a polygon can be defined relatively straightforwardly. For example the Venetian walls of Nicosia form a discrete spatial footprint, that can be traced using the HGC’s geocoding tool. But in most cases, this requires a subjective judgement, and thus a subjective representation, that is arguably inimical to the positivist interpretation which any robust database requires; and imposes exactly the kind of Cartesian absolutism that I and others have railed against in several recent and forthcoming publications. Further, creating an HU in this way can lead to our grouping data points that are actually very different in nature. Sometimes an HU will equate to a modern toponym (such as Marchello, in Nea Paphos), and sometimes it does not. Hellenistic kingdom of Paphos is another example of a composite; whereas medieval/Venetian Nicosia is a defined location. As another colleague commented on the project recently:

“The concept of Historical Units is something that I think needs some additional definition. I understand that other standards have the same fuzzy things, but poorly defined things add increasing difficulty as the dataset grows. My reading … is that you mean geographical feature which is uncomfortably close to Archaeological Entity. Have you considered just calling them ‘historical features’ and having a containment / recursive relationship?”

As we take the HGC forward therefore, we propose to modify this artificial footprinting mechanism, so that an HU is rather represented by a set of thematically, but not necessarily geographically, conjoined AEs.

Nea Paphos - an example of an HU in the HGC

Nea Paphos – an example of an HU in the HGC

This speaks to a much more fundamental problem of how archaeological data – bearing in mind that the HGC is about names, and is thus more a creature of history than of archaeology – is recorded. Much rhetoric of the semantic web in the discipline, at least in its earlier phases, focused on the need to link archaeological datasets ‘organically’, where data produced by one site can be linked and contextualized with that from another, without the excavation teams of either having to adopt a priori methods or procedures for data production. This may hold true to an extent, but our experience with HUs especially shows that when combining such data, some kind ofa posteriori aggregation process must be undergone. Otherwise, quite simply, one adds little to the data by linking it. In our current model, this is imposed by the user doing the aggregating; but the subjectivity this introduces is fraught with difficulties. Therefore, our next steps will be to develop our categorising and attributing capabilities for AEs, and begin aggregating into HUs on that basis. They will therefore be grown from the ground up in a way that is guided by the HGC data structure, rather than imposed from the user downwards.

On to prehistory: the Ancient Places of Cyprus

October 19, 2014


I currently have the great good fortune to be a visiting scholar at Stanford University’s Center for Electronic Spatial and Textual Analysis (CESTA). I have two aims while here: working on the monograph (on spatial narratives – more blogging on this to follow) upon which my term’s research leave from King’s is contingent, and developing a new project, recently christened “The Archaeology of Place in Ancient Cyprus”. This is follows the A G Leventis Heritage Gazetteer of Cyprus, which I have blogged about previously; but rather than being concerned with historical names, which are written down and attested, this phase is focusing on the prehistoric period – where, of course, there are no written records, and thus no known place-names (and no documented attestations of their spellings, forms etc). In the Archaeology of Place, We are creating a seed dataset which seeks to represent Cypriot archaeology of the prehistoric period, before any contemporary place-names are documented.  This involves a multistage process of critical quantification: starting with published material on prehistoric sites and features, we are examining how these can be defined in objective (and computable) terms, and how different units of archaeology can be represented at different scales. This will lead to a broader examination the ‘toponymic spaces’ of prehistoric features: how do the areas they occupy on the Earth’s surface relate to more recent place-name structures? And what strategies can we use to grow this dataset in the future, beyond the corpus of material currently available in print?

Critical quantification is key to this project.  I have real problems with the way the words ‘quantitative’ and ‘qualitative’ are often used in the Digital Humanities. They – as far as I can see – are terms that have evolved over a long period of time in the social sciences, where they have a well-understood meaning and a solid methodological grounding. In the DH, they are frequently used as catchy labels for ‘things which either can or cannot be machine-read respectively’. This is undoubtedly not helpful, given the great complexity and diversity of ‘humanities data’ – a term which, itself, is surely too broad to be all that useful.

So we are beginning with what can definitely be quantified.  When I. A. Todd et al define a ‘tomb’ in the cemetery at Kalavassos for example, we can treat this is a piece of discrete information, much as we are treating an attested name as a discrete piece of information in the HGC (with its own URI, and the possibility of other URIs for “smaller” pieces of information, such as finds, with which it has a container relationship). But in the future we will consider what other attributes could be added to each of these, for example, relationships with modern features which might not have been documented at the time. Online images, and pieces of related data from the geoweb. Even social media elements. This will open up the possibility for more in-depth experimentation using GIS – for example investigating least-cost pathways between sites in the northern Vasilikos Valley with points of known importance on the south coast, and how the finds, features and pits of those sites might be used to enrich that analysis. We will also undertake a broader consideration of what this exercise tells us about the epistemology of archaeology, and its quantitative aspects, might mean. While it makes perfect sense for quantification to follow the ‘objectivity’ of the material involved – beginning with physical objects, with clearly defined sites, and obvious statements that can be made about their attributes – we are interested in where the affordances of the digital environment of a database might take us in terms of contextualising them with purely digital objects; and how this might help us mediate spatial narratives of Cyprus’s distant past.

Image biographies?

May 11, 2014

Last week, thanks to my Fellowship of the Software Sustainability Institute, I attended Electronic Visualization and the Arts in Florence. This fascinating and wide-ranging conference bought together a tremendous range of people and ideas. Strategy, application, theory. A fascinating take on crowd-sourcing appeared in the form of a project of ETH-Bibliotek in Zurich, cataloging a massive image archive of daily life working for Swissair using the knowledge of Swissair retirees.


Another issue that came up was the challenge associated with archiving a digital image for the  very long term – 150 years or more? Today we still have images taken in the 1920s and 1930s, can digital imaging deliver similar longevity? The short answer is almost certainly not. One strategy discussed, by Graham Diprose and Mike Seabourne, is to archive digital artwork and photography by printing it on specially prepared paper; an approach they describe as a ‘technology proof form of insurance’. I think this raises important issues about how images, digital or otherwise, are dealt with as ‘objects’. This topic has a certain hinterland in the domain of cultural heritage, as the concept of the ‘object biography’ has been discussed since at least 1999, when Chris Gosden and Yvonne Marshall wrote that ‘as people and objects gather time, movement and change, they are constantly transformed, and these transformations of person and object are tied up with each other’ (‘The Cultural Biography of Objects’, World Archaeology, Volume 31 No. 2 [October 1999]: 169-178). The key difference with images – an susbset class of objects that has only existed for a little over one hundred years – subject, significance and material can be separated. What an image depicts is separate from the materiality of the photograph itself — and from the cloud of numbers that make up a digital image. Such considerations encourage us to think about what the ‘biography’ of an image might look like. And this is important. The Gosden-Marshall model of the object biography has gained currency in a number of major museums, including the Pitt Rivers. The implications of the image biography, where meaning and material are preserved side by side, will be preserved side by side, can only be done if the relationships between these two are also preserved. This will include methods for preserving metadata (a point made in the session by Nick Lambert); but it also accords, I think, with the broader intellectual direction of where visualization is going.


Florence, Piazza degli Ottaviani. The EVA venue is on the left.

To explain this: this year, in London, EVA International will celebrate its 25th anniversary.  In the last twenty five years, much digital visualization has been contingent of the presentation of 3D material on the 2D screen. My sense from the last three or so EVA Londons, confirmed by EVA Florence, is that in the next twenty five years, visualization will involve the 2D screen less and less. A greater proportion of demos at EVA London now involve objects, not screen-based presentations. Carol MacGillivray, Bruno Mathez and Frederic Fol Leymarie’s  Diasynchonosope project in 2013 and Gary Priestnall, Jeremy Gardiner, Jake Durrant & James Goulding’s Projection Augmented Relief Models in 2012 are particularly striking examples, but there are many more.  Preserving these visulaziations, including more conventional digital images, will require an integrated cloud of thinking on software sustainability, and its relationship to curation practice, digital augmentation and policy. I look forward to seeing more illustrations of this in London in July. I was also happy to participate in a network meeting of EVA international on the third day.The meeting ended with a small ceremony to inaugurate a plaque in the newly refurbished room to commemorate the event (see photo – this is a facsimile, pending the real thing being engraved). Image