Linked Open Data (LOD) should be the standard for the modeling and publication of research data, as it greatly improves the research process by facilitating access and reducing the likelihood of mistakes. To encourage our readers to create LOD, we have developed a workflow for the enrichment of datasets taken from analog and digital sources by interlinking and publishing them in Wikidata. This paper will discuss the main principles of LOD, as well as current attitudes towards it in the digital humanities. Our vision for LOD has lead us to create SPARQL Unicorn, a series of tools designed to make Wikidata easier to use. As an example of SPARQL Unicorn in action, the second half of our paper will describe the Wikidata integration of the inscriptions found on the early medieval Ogham stones. Sources, workflow, tools, and data models will be explained in detail, as two examples of (geo-) statistical analysis showcase the benefits of enriched LOD to researchers.
This paper introduces a workflow for digitizing analog editions in the open access data storage facility Wikidata1, and shows how the enriched data can be extracted and used for further research. For this purpose, we draw upon the Corpus Inscriptionum Insularum Celticarum (CIIC), the most complete analog catalog of Ogham stones assembled by R. A. S. Macalister (1945, 1949), the CISP project,2 and the Ogham in 3D Project.3 As we will show, the SPARQL Unicorn tool framework enables users unfamiliar with the SPARQL language to work with data stored in Wikidata. Our analysis of the created dataset by means of the SPARQLing Unicorn QGIS Plugin and the statistical scripting language R demonstrates the viability and usefulness of such an approach.
The SPARQL Unicorn tool framework and the ᚑᚌᚔ (Ogi) Ogham Project are developed and maintained by the Research Squirrel Engineers4 research network and specific working groups. The Research Squirrel Engineers are an open and international association of researchers with a background in software engineering, geoinformatics, and cultural heritage, which was founded by the authors of this paper, Sophie C. Schmidt5 and Florian Thiery6. Its members cooperate with other researchers and institutions to implement research projects and research software based on Linked Data and the Semantic Web, without institutional and funding dependencies.
This chapter begins with some basic information concerning the inscriptions on the Ogham stones and the Ogham alphabet itself. We will then introduce Linked Open Data (LOD) as a data modeling concept, and Wikidata and Wikimedia Commons as examples of this Open Science approach. Our vision of LOD lays the groundwork for the section on SPARQL Unicorn, a tool framework designed to facilitate the use of Wikidata. Last, but not least, we will describe the Ogi Ogham Project in detail: our sources, the workflow of the project, the import of data into Wikidata, and the modeling process.
1https://wikidata.org 2https://www.ucl.ac.uk/archaeology/cisp/database/manual/ 3https://ogham.celt.dias.ie 4http://squirrel.link 5Research Associate at the Deutsches Archäologisches Institut (NFDI4Objects) 6Research Software Engineer at the Römisch-Germanisches Zentralmuseum, Department of Scientific Information Technology
Ogham (Old Irish: Ogam) stones (Figure 1) are monoliths inscribed with
the Ogham script
The texts found on Ogham stones mostly refer to persons, tribes, or
family afiliations
The term ‘Linked Open Data’ describes the goal of interlinking data within the World Wide Web with other semantically related data. Tim Berners-Lee has proposed the Linked Data principles consisting of four simple rules (Figure 2):
2. Use HTTP URIs so that people can look up those names 3. When someone looks up a URI, provide useful information using the standards RDF* and SPARQL 4. Include links to other URIs, so that users can discover more things However, the shortcomings that Berners-Lee pointed out in 2006 remain a challenge today: “a surprising amount of data isn't linked [...] because of problems with one or more of the steps.” (Berners-Lee, 2006)
The concept of the Semantic Web as established by Berners-Lee (BernersLee et al., 2001) draws on Open Data to describe the web resources, links,
and machine-readable interfaces that are required for creating a Giant Global
Graph (Berners-Lee, 2007). Applying LOD techniques helps in creating
FAIR (findable, accessible, interoperable, reusable)
The model's seven spheres (Figure 3) are defined as follows: 1. OL (Data is available in the Web under an open license) 2. RE (Data is available as structured machine-readable data) 3. OF (Data is available in an open, non-proprietary, structured, and machine-readable data format) 4. RDF (Data is available as URIs and semantically modeled as RDF) 5. LOD (Data is available as a resource, semantically modeled as RDF, and semantically linked to other resources) 6. LOUD (LOD is available as usable data, according to the LOUD principles) 7. LOUD+FAIR (LOUD is available as findable, accessible, interoperable, and reusable data, according to the FAIR principles) 3.1
LOD in the Digital Humanities and Digital Archaeology
In 2011, Leif Isaksen described possible applications for Semantic Web (and
Linked Data) technology in the discipline of archaeology
In popular culture, the phrase hic sunt dracones (‘here be dragons’) is often used to designate areas on historical maps that are unknown to the authors. It has also been applied to the harvesting and storage of data (Wuttke, 2019): nowadays, researchers can share their research as LOD, enabling the com
munity to participate in the scholarly discourse in order to create new
knowledge; yet unfortunately, much of this data is neither findable nor accessible,
and is therefore not FAIR, resulting in modern “unknown data dragons.”
Often, these ‘data dragons’ are not interoperable and thus unusable for
further scholarly research. These shortcomings can be overcome with the
standards and recommendations outlined above: Semantic Web and LOD, the
FAIR principles, and LOUD
Wikidata and the Wikimedia Universe
Established in 2012, Wikidata12 is a data hub for structured data that was not
developed as a primary database for a specific project, but rather to gather
existing entries from other databases
Modeling decision-making processes is dificult in any kind of data base,
and Wikidata is no exception. To resolve this and other potential drawbacks
of Wikidata, it is possible to create a user-defined ontology based on, for
example, the CIDOC CRM CRMsci extension
In Wikidata, versions of the entries are recorded, but while the entry his11http://datadragon.link 12https://wikidata.org 13https://www.w3.org/TR/prov-o/ tory may be viewed, links to a specific version of an entry are impossible, because the Semantic Web and URIs are not designed to allow this. As anybody can edit the entries, the original author does not have data sovereignty, and false information may be entered. What is more, information cannot be flagged as debatable – it can only be deleted and discussed in the history view, which, in the absence of structured moderation or editing, may lead to duplicates and inconsistencies. However, despite all of these shortcomings, Wikidata is nonetheless suitable for a number of Open Science applications, as will be discussed in the following sections. 3.3
Our Vision LOD should be the standard in digital heritage data management, but unfortunately this is not yet the case. Currently, we see two main obstacles to achieving this goal: 1) data extraction requires SPARQL knowledge, and data hosting calls for extensive technical training, which only few researchers have the necessary time and resources to acquire; 2) researchers do not gain any professional recognition for opening up their archives to share and link their data, even though this would greatly enrich the research process in that it enables data to be found faster, reduces errors in transcription and citation, and leads to reproducible research practices. Wikidata allows for the direct creation of LOD as part of the Linked Open Data Cloud.14 Yet despite a number of existing applications,15 Wikidata lacks user-friendly tools for researchers and archaeologists, which is where the SPARQL Unicorn comes into play. 4
The SPARQL Unicorn was born at the Computer Applications and
Quantitative Methods in Archaeology conference 2019 in Kraków, Poland.16 Over
the course of this conference, it became abundantly clear that data
analysis and the creation and maintenance of databases play a central role in
archaeological and digital humanities-related research. However, very few
databases are freely and openly available and accessible, and even fewer are
connected to the Linked Open Data Cloud, which greatly hampers the
comparative analysis of records across multiple datasets. One data hub
that has recently picked up momentum is Wikidata, a repository based on
the SPARQL query language. Yet while supporters of free and open
research data have a strong afinity towards community-driven and
volunteer14https://lod-cloud.net
15https://hay.toolforge.org/directory/#/search/wikidata
16https://2019.caaconference.org
operated data collecting initiatives such as Wikidata, there is – in addition
to the various issues outlined above – a shortage of user-friendly, free, and
open tools for LOD technologies and repositories, including Wikidata
itself. To help mitigate these problems, we developed the SPARQL Unicorn,
which we would describe as a friendly tool series for researchers working with
Wikidata and other related triple stores. More specifically, the SPARQL
Unicorn aims to help researchers from the field of ancient studies use the
community-driven data from Wikidata by making it more accessible to those
without expertise in LOD or SPARQL
The SPARQLing Unicorn QGIS Plugin25
As it stands, the plugin oefrs three main functions: a) the simplified querying of LOD sources, b) the enrichment of geodata, and c) the transformation of GeoJSON to RDF data.
Function A (Figure 4) permits assisted querying of predefined triple stores, e.g. Wikidata, Nomisma,29 Linked Ogham Data,30 and Roman Open Data.31 It also makes it possible to add another SPARQL endpoint. The SPARQLing Unicorn QGIS Plugin will automatically search for semantically described geospatial data in the widely used vocabularies GeoSPARQL32 and WGS84 Geo Positioning,33 e.g. geosparql:asWKT, geosparql:asGeoJSON, geo:lat and geo:long.
To assist the user, the plugin provides query examples for the predefined triple stores which can be used as query templates. The plugin will automatically detect geospatial-related (inferred) classes/concepts (Figure 4, right). As shown in Figure 4, the user can select one of the geospatial concepts by clicking on it (e.g. Stone), and the plugin will automatically replace the class in the query template. Additionally, the user can restrict the spatial area by a bounding box (Figure 5) or a loaded geospatial layer. This results in a GeoSPARQL function34 query using geof:sfIntersects, as shown in Figure 6 (if the triple store supports GeoSPARQL).
If a user employs the Linked Ogham Data SPARQL endpoint, the Concept + Label query template, the geospatial concept Stone, or the bounding box shown in Figure 5, this will result in a QGIS vector layer that can be saved in common geo data file formats, e.g. GeoJSON, or a shapefile. By way of example, Figure 7 shows the distribution of Ogham stones on the Dingle Peninsula.
Function B allows the enrichment of geo data using LOD resources from the Linked Open Data Cloud, especially Wikidata (e.g. Ogham site elevation levels). Geospatial data, in particular, can always be seen in an application context, which usually requires additional data from other knowledge domains. Semantically interpreted Linked Data may represent such a resource 29http://nomisma.org/sparql 30https://digits.mainzed.org/ogham/ 31https://romanopendata.eu/sparql/epnet.html 32http://www.opengis.net/ont/geosparql# 33http://www.w3.org/2003/01/geo/wgs84_pos 34http://www.opengis.net/def/function/geosparql/ for data enrichment.
Function C converts geospatial information from formats such as GeoJSON into RDF formats like Turtle, which enables the publication of archaeology-related geo data as Linked Data. 5
The ᚑᚌᚔ (Ogi) Ogham Project was initially created in 2019 by members of the Research Squirrel Engineers network in conjunction with the SPARQL Unicorn project,35 and is now supported by the Wikimedia Foundation. The project is a work in progress, whose aims include the digitization and publication of the analog catalog compiled by Macalister (1945, 1949), as well as the linking of existing online resources into Wikidata.36 The standards applied in the creation of this set of LOD mean that the data involved will become FAIR. The Wikidata repository can be used to support reproducible statistical and geostatistical analysis of the data. We will draw on Macalister's corpus to illustrate this point and to demonstrate the value of modeling analog catalogs as LOD. 5.1
Sources on Ogham Stones and Script There are several sources, both analog and digital, for information on Ogham stones. As it is our goal to link existing datasets to each other, we will introduce them here in some detail. 5.1.1
Traditional Ofline Sources Our main source of information is the aforementioned Corpus Inscriptionum Insularum Celticarum (CIIC) compiled by Macalister (1945, 1949), in which a large number of Ogham stones in Ireland (CIIC 1-317), Wales (CIIC 317-456), England (CIIC 457-499), the Isle of Man (CIIC 500-505), and Scotland (CIIC 506-520) are recorded. In the first phase of the project, we concentrated on the Irish37 Ogham stones (CIIC 1-317). The CIIC is the most important reference work for Ogham inscriptions, and its numbering system, CIIC, has also been used to reference stones in other sources.
Macalister describes two diefrent word categories: formula words and nomenclature words. Examples of formula words are MAQI ᚋᚐᚊᚔ (son, e.g. CIIC 203, Q67978531) or MUCOI ᚋᚒᚉᚑᚔ (tribe/sept, e.g. CIIC 197, Q69388229). Examples of nomenclature words are CUNA ᚉᚒᚅᚐ (wolf/hound, e.g. CIIC 154, Q68002826) and CATTU ᚉᚐᚈᚈᚒ(battle, e.g. 35https://www.wikidata.org/wiki/Q73901970 36https://www.wikidata.org/wiki/Q70873595 37https://w.wiki/Wmz CIIC 58, Q70892430). Other names refer to deities, such as the god Lugh (LUC ᚂᚒᚌ), who appears in names such as LUGADDON ᚂᚒᚌᚌᚐᚇᚑᚅ (CIIC 4, Q70899515).
As most of the stones are damaged, linguistic analysis often yields
divergent readings and reconstructions
Of course, the archaeological and linguistic research conducted in the
intervening years means that the CIIC is not the only relevant source. It is,
however, the most complete, and since subsequent scholarship has
continued to use Macalister's numbering system for the Ogham stones, the CIIC
is an expedient starting point for our data acquisition. Later sources, such as
We used the spatial information given in Macalister's catalog – county,
barony, and townland – as well as the inscriptions themselves to identify the
stones in other resources. A townland (Irish: baile fearainn),38 the most
precise category describing the location of the stones, is a spatial unit of Gaelic
origin, though it has been modified by later re-structuring processes such
as the Ordnance Survey. This information was used for linking the data
to OpenStreetMap with the help of Townlands,39 and in some cases
Logainm.40 Most Ogham stones recovered so far have been re-used over the
centuries and can now be found as lintels in huts, in the walls of churches
etc.
Online Databases Several online databases for Ogham-related research exist. The Thesaurus Indogermanischer Text- und Sprachmaterialien (TITUS) database41 hosted by Jost Gippert dates from 1996. It is online, but it is neither open nor interoperable, and cannot be interlinked with other datasets, which prevented us from using it in our case study.
Another rich source of information on Ogham stones is the database of 38https://data-osi.opendata.arcgis.com/datasets/559dc2f725004823b51923e1d6ba5889_0/data 39https://www.townlands.ie/ 40https://www.logainm.ie/en/ 41http://titus.uni-frankfurt.de/ogam/frame.htm the Celtic Inscribed Stones Project (CISP)42 assembled by University College London, which gathered numerous inscriptions (not only in Ogham) and published them online in 2001. This database has no API, and one can only click through the various entries. It is online, but neither linked nor open, which is wholly understandable given the year of its publication. We would like to thank Dr. Kris Lockyear, who generously made the project's Access database available to us and gave us permission to use the data.
Some more recent open research projects oefr online and open data, including the Ogham in 3D Project,43 which creates 3D scans of known Ogham stones in Ireland (as of January 2021, there were c. 160 scanned stones44). An online platform45 oefrs 3D data (3D PDF and OBJ files), as well as EPIDOC46 files with annotated stone inscriptions for download under a Creative Commons License. An example is stone CIIC 180, Emlagh East (Imleach Dhún Séann), Co. Kerry,47 which is shown in Figure 8.
Another important resource is the Historic Environment Viewer,48 which contains a WebGIS that provides access to the records of the National Monuments Service's Sites and Monuments Record (SMR) and the National Inventory of Architectural Heritage (NIAH). While this repository is very helpful, there are no links to other datasets.
It is therefore safe to conclude that there is a lack of Ogham research data in the Linked Open Data Cloud. This results in various challenges, and makes comparative analysis of records across multiple datasets dificult. However, some useful information can be found in the Wikimedia universe with its variety of tools and projects under the umbrella of the Wikimedia Foundation, as will become clear in the following section. 5.1.3 Ogham in the Wikimedia Universe The Wikimedia project universe49 provides researchers with a large number of free and open access data hubs. This includes the free encyclopedia Wikipedia, the free media repository Wikimedia Commons, the free knowledge base Wikidata, as well as the bibliographic extension to Wikidata, Scholia. Wikipedia, for example, contains articles on the Ogham alphabet50 and 42https://www.ucl.ac.uk/archaeology/cisp/database/ 43https://ogham.celt.dias.ie/menu.php?lang=en 44https://ogham.celt.dias.ie/menu.php?lang=en&menuitem=81&overviewinfo=epidoc_stone_details 45https://ogham.celt.dias.ie/menu.php?lang=en&menuitem=81&overviewinfo=file 46https://epidoc.stoa.org/gl/latest/ 47https://t1p.de/o3d180 48https://webgis.archaeology.ie/historicenvironment/ 49https://meta.wikimedia.org/wiki/Wikimedia_projects 50https://en.wikipedia.org/wiki/Ogham Ogham inscriptions.51 Some bibliographic information concerning Ogham has already been assembled in Scholia, but the collection requires further attention52 to expand the small number of existing items related to the topic.53
Wikidata Commons oefrs a set of free Ogham images, 54 including a chart of the Ogham alphabet,55 Macalister's drawing of CIIC 81 at Garranes, Barony of Kinalmeaky (Figure 9), and the photograph of CIIC 81 in University College Cork's Stone Corridor (Figure 1) with the inscription C[A]SSITT[A]S MAQI MUCOI CALLITI (CASSITTAS son of the tribe CALLITI, the hard ones). 5.2
Workflow The first step of our Ogi Ogham Project workflow (Figure 10) is the extraction of spatial information on the Ogham stones and their inscriptions from Macalister's ofline catalog. This spatial information is then linked to Open Street Map data, other Geo LOD resources, as well as further Ogham data, which allows the mapping of databases according to location and information on the inscription (e.g. the CISP database). As a next step, this data can be imported into Wikidata, making it possible to extract the enriched information with SPARQL Unicorn and to analyze it further with software such as QGIS (using the SPARQLing Unicorn Plugin) or R (see Section 5.3) in a process that can be applied to data from other sources as well. In the following sections, we will first discuss Wikidata modeling and the import process for spatial information, before presenting two concrete examples of how our workflow can be applied. 5.2.1
Wikidata Import The Association of Research Libraries (ARL, 2019) recommends using OpenRefine 56 for inserting, publishing, and maintaining information stored in Wikidata. Our basis for editing in OpenRefine are CSV files, which contain all information along with links to other Wikidata entities. We manually compiled these CSV files from sources such as Macalister, Logainm, and Open Street Map. Our first import 57 contained CSVs for 51https://en.wikipedia.org/wiki/Ogham_inscription 52https://ogham.celt.dias.ie/menu.php?lang=en&menuitem=80 53https://scholia.toolforge.org/topic/Q184661 54https://commons.wikimedia.org/wiki/Category:Ogham 55https://commons.wikimedia.org/wiki/Ogham_alphabet 56https://openrefine.org/ 57https://github.com/ogi-ogham/ogham-wikidata ‘Ogham sites/townlands,’58 ‘Ogham collections,‘59 and ‘Ogham stones.’60 OpenRefine oefrs the possibility of creating individual mapping schemes for Wikidata, which we applied to, among other things, Ogham sites61 and Ogham stones62. The results of this mapping process can be transformed and exported by OpenRefine to QuickStatements. 63 The Quick Statements 2 Tool64 is capable of creating new Wikidata entities and updating existing ones automatically based on the QuickStatements syntax.65 In light of our own experience with this workflow, we can highly recommend using OpenRefine and QuickStatements as Wikidata import tools. 66 5.2.2 Wikidata Modeling: Words Wikidata contains a number of Ogham-related entities67 which describe Ogham as an early medieval writing system (Q184661), Ogham stones as stones with Ogham inscriptions (Q2016147), Ogham sites as sites where Ogham stones have been found (Q72617071), and Ogham letters as characters in the Ogham alphabet (Q41812345).
As outlined above, a variety of formula and nomenclature words can be
found in Ogham inscriptions. A list of these words according to
We used the database of archaeological finds uploaded by the Department of Culture, Heritage and the Gaeltacht (the above-mentioned Historic Environment Viewer), to check our information. Although the locations of some items in this database are listed as unknown, attempts at clarification of their precise whereabouts were undertaken by local experts, to whose findings we adhered (this applies to a total of 16 cases; concerning CIIC 204, for example, we followed the experts' evaluation that Macalister had erroneously given its location as Curraghmore West instead of East).
The website Logainm also proved helpful, as it linked a monument about which Macalister's catalogue yielded only imprecise information to a specific townland. In instances where Macalister provided further information on the stone's location by describing the area or certain landmarks, we were able to use these details to improve the precision of the spatial data. For example, Macalister's comment that the stone CIIC 48 was found south of the village allowed us to tentatively identify the townland in question. In the rare cases in which two townlands with the same name were located right next to each other, we opted for the larger of the two, crosschecking this educated guess with the Historic Environment Viewer.
In this way, 185 out of the 196 townlands mentioned by Macalister could
be identified and the corresponding information entered into Wikidata: the
townland's anglicized name; its Gaelic alias; the province, county, barony,
civil parish, and electoral division it belongs to; and a point coordinate
indicating the middle of the townland polygon. The dataset was linked by
providing the OSM, Logainm, and OSi GeoHive IDs, as well as the link to
the Townlands IDs from which we derived most of our data. In order to map
the eleven Ogham stones whose location remained unknown, we resorted to
the center of the barony as indicated by Macalister
As stated above, decisions such as these are currently dificult to model using Wikidata. A bespoke ontology with self-defined semantic modeling rules could be a step towards more transparency in decision modeling.69
Table 1 shows the example of the Wikidata model for the Ogham sites in Garranes Townland, Co. Cork. Each site is described with a label, a description, an alias (Irish name), the country, the province, and other administrative divisions, a coordinate location, as well as external identifiers linked to OpenStreetMap and the Logainm website. Wikidata also oefrs the possibility of setting statements for reference information, thereby linking inform69more information at https://doi.org/10.5281/zenodo.4091743 ation to its source. This was done for several properties of an Ogham site including administrative divisions, location, and external identifiers (Table 2), so as to provide a reference for each piece of controversial information with regards to the stones' location. 5.2.4
Wikidata Modeling: Stones The entries on Ogham stones in Wikidata follow a basic modeling structure: P31 (instance of) Ogham stone (Q2016147), P361 (part of) Ogham stones (Q67978809)/Ogi-Ogham Project (Q70873595), P17 (country) Ireland (Q27), P625 (coordinate location) derived from the Ogham site, P189 (location of discovery) county and Ogham site, P1684 (inscription) and P1545 (series ordinal). Some of the stones contain additional information as shown in Table 3 for CIIC 81.70 Our goal is to model all known Ogham stones. We would like to add details on P186 (material used), P195 (collection), P2043/P2049/P2048 (length, width, height), P6568 (inscription mentions), P5816 (state of conservation) and P18 (image). The sources of this in-depth information are shown in Table 4. As discussed above, references such as these are especially relevant in cases of conflicting information regarding the texts and their interpretation. 5.3
Analysing Ogham The information on the Ogham stone sites collected in Wikidata enables a multitude of analytical approaches. By way of example, we will concentrate on spatial analysis and the exploration of word counts.
To gather and import Wikidata data into a format that is usable in the statistical programming language R, a package called WikidataQueryServiceR (Popov, 2020) can be used. It is an API client for the Wikidata Query Service71 and implements the function query_wikidata. query_wikidata transforms the data retrieved from Wikidata by means of an input SPARQL query into a dataframe, which is one of the most widely used classes for tabular data in R. The scripts for the analytical approaches described in the following sections can be found on GitHub.72
In our investigation of the spatial relations between the Ogham sites and word frequencies, several R packages were utilized.73 In addition, we also employed QGIS and the SPARQLing Unicorn QGIS Plugin to conduct various types of spatial analysis on the modeled Ogham stones. 5.3.1
Spatial Analysis It is evident from the density and distribution analysis carried out by means of the R project oghamaps74 (Schmidt, 2021) and QGIS (Figures 11 and 12) that the majority of Ogham sites are located in the counties of Kerry, Cork, and Waterford (Table 5), and the Dingle Peninsula (western hotspot in Figure 12). The south of Ireland is the main distribution area with decreasing density of sites from west to east.
To further examine the various areas, percolation analysis was applied; an
explorative clustering algorithm
In our example, the change in the mean cluster size is shown in relation to the clustering radius (Figure 14). At the points where the curve flattens, only a small number of sites appear to be integrated into the existing clusters. As a result, we can see how dense the points inside small clusters are, and how far away the next points lie. Many Ogham sites are about 10 km away from each other, with the next steps in the distribution occurring at a radius of 22, 34, and 44 km, after which almost all stones are incorporated into a single cluster. At 22 km, all Ogham stones in the south of Ireland belong to a single cluster, whereas several distinct clusters still exist in the north – a clear indicator of the lower density of Ogham stones in this area. 5.3.2
Analysis of Word Frequency The foregoing discussion begs the question: which words are most frequently found on the 317 Ogham stones in Ireland? And do some of these words regularly appear in combination with others?
To answer these questions, we used the Ogham Extractor Tool, available
on Github,76 and the table ciictowords2
76https://github.com/ogi-ogham/oghamextractor/ the CIIC stones are recorded. As our focus was on their meaning and not on variances in spelling, we resorted to the most common forms of the words in question (for example, MAQI instead of MAQ).
The resulting word list was used to a) show how often the most common
words occur (Figure 13) and b) how often words co-occur (Figure 15). As
discussed above, MAQI (son) and MUCOI (tribe) are most common, followed
by LUG (god), AVI (grandson, descendant), and ANM (name). This,
combined with the preponderance of names in the inscriptions, underscores the
importance of familial afiliation in the communities that used the Ogham
alphabet. The religious dimension also appears to have played a significant
role
The second word analysis looks at the co-occurrence of words on the Ogham stones (Figure 15). In this case, we wished to determine whether or not specific names or topics always appear in combination.
Our analysis shows a range of values between 0 and 21. The diagonal must be ignored, as it reflects how often a word occurs all in all (co-occurrence of words with themselves). The most frequent co-occurrence is of the words MAQI and MUCOI (21 times) – once again, son and tribe. As MAQI is the most common word overall, it also has the most co-occurrences with other words. Given that the dataset yielded by the Ogham inscriptions is rather small and consists of a limited number of words, the most common co-occurrence frequency is 0, as some words do not co-occur with others at all (e.g. CARI, loves).77 By contrast, two words that are seldom used – VIR (man, 7x) and CATTU (battle, 3x) – do co-occur, even though the compound word CATTUVIR (man of battle) also exists. This particular case of co-occurrence gives us another brief glimpse at the workings of the society behind these monuments and the importance it attached to warfare. 6
In this paper, we discussed LOD and its role as the emerging standard for research data management and semantic data modeling in the digital humanities, digital archaeology, and archaeoinformatics, as well as its practical implementation in Wikidata. Acknowledging that the SPARQL query language is not yet widely known, we introduced the SPARQL Unicorn tool framework developed by the community of Research Squirrel Engineers with the aim of helping researchers use SPARQL. One of the cornerstones of this framework is the SPARQLing Unicorn QGIS Plugin, which is already published and enables researchers to query Wikidata for geospatial and other LOD within the 77It should be noted, however, that the dataset has been reduced to the words that occur at least three times in total. QGIS environment.
A short overview of the Ogi Ogham Project demonstrated the practical application of our digitization and linking workflow for the creation of LOD, and showcased how OpenRefine and QuickStatements can be employed to import that data into Wikidata. Two analytical approaches that have already been implemented illustrated the potential of our toolkit to foster open and reproducible research.
In the future, we will focus on the steps necessary for modeling our own bespoke Ogham ontology and hosting it in a triple store, which will increase our flexibility with regard to semantic modeling, and will allow us to use the Wikidata entries as links to the Linked Open Data Cloud. This planned development work is part of the project Irische ᚑᚌᚆᚐᚋSteine im Wikimedia Universum and is funded by the Wikimedia Deutschland Fellow-Programm Freies Wissen.78
As has become clear, the Ogham data is perfectly suitable for text analysis (e.g. text as a graph using a graph database like Neo4J79), and will lend itself equally well to network analysis of the relationships between persons and tribes – all that is needed is the further enrichment of Ogham data through the addition of sources and information (including provenance information) by the community.80
Timo Homburg and Martina Trognitz, fellow members of the Research Squirrel Engineers network, have been of great support, both in the development of our project and its presentation in this paper. We would also like to thank Dr. Kris Lockyear for his encouragement and for kindly making the CISP database accessible to us, and Dr. David Wigg-Wolf for language corrections.
78http://ogham.squirrel.link 79https://neo4j.com 80The Research Squirrel Engineers welcome new squirrels interested in feeding the Linked Data Cloud with Ogham nuts! n i s t n i o p t n a ific n g i s
4 ahp YB r G C . C is , s t
d ly i a n hm a c n S io ie t a h l p o o c S r e [ P n :4 i o t 1 u re i b r u t ig i
s F d description desc description add. information townland geographic location county town project Ireland Northern Ireland province county barony civilparish electoraldevision lat lon OpenStreetMapID LogainmID example Garranes Townland Garranes Townland, Co. Cork An Garrán townland (Q2151232) Ogi-Ogam Project (Q70873595) Ireland (Q27) Province Munster (Q131438) County Cork (Q162475) Barony Kinalmeaky (Q20616069) Templemartin (Q60557037) Templemartin (Q59724324) 51.816389 -8.761667 6168494 8299 P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) Q85384744 Q85384744 Q85384744 Q85384744 Q85384744 property label description alias P31 (instance of) P361 (part of) P361 (part of) P18 (image) P17 (country) P625 (coordinate location) P2868 (subject has role) P186 (material used) P195 (collection) P189 (location of discovery) P2043 (length) P2049 (width) P2048 (height) P1684 (inscription) P518 (applies to part) P1545 (series ordinal) P6568 (insc. mentions) P5816 (state of conservation) description desc description add. information ogham stone Ogi Ogam Project Ogam Stones photo or drawing modern country lat lon qualifier stone material collection of ogham stones ifndspot stone length stone width stone height ogham inscription qualifier number ogham words stone status qualifier ogham stone Ogham Stones Ireland 51.816389;-8.761667 stone Stone Corridor UCC County Cork Garranes Townland length/ width/ height inscription series ordinal (81) series ordinal (4) MAQI MUCOI preserved County Kerry Cork Waterford Kilkenny Kildare Mayo description P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) P248 (stated in) Number of Ogham stones 127 81 47 12 8 8 ARL (2019). ARL White Paper on Wikidata Opportunities and Recommendations. https://scholarworks.iupui.edu/bitstream/handle/1805/18902/ ARL-white-paper-on-Wikidata.pdf.
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