Talks by Darren Joblonkay
The management and organization of archaeological data in complex database management systems (DB... more The management and organization of archaeological data in complex database management systems (DBMS), and more recently data warehouses, such as the Online Cultural and Historical Research Environment (OCHRE), has become commonplace within the discipline. Traditionally, Near Eastern archaeologists have emphasized data interoperability and integration for inter-site comparison
of archaeological data, often through attempts to establish data “standards,” which has proven relatively unfruitful. Furthermore, as highly atomized, item-based data structures come to replace the traditional relational data model often utilized by archaeologists, it has become apparent that a data standard is not necessary as long as our data ontologies remain appropriately abstract (i.e., highly itemized). In doing so, we can conceive of DBMS not as simple repositories of data, but as analytical environments in their own right, wherein lies the potential for not only the accumulation, but the construction and contestation of knowledge from archaeological data (Knowledge Discovery from Archaeological Data [KDAD]). Following a brief excursus into the phenomenon of data mining and its implications within the discipline, this paper will focus on the implementation of a revised apriori algorithm (after Agrawal and Srikant 1994) for establishing associations among items in a dataset. The algorithm is applied to a dataset from Tell Mastuma, Syria, to elucidate heretofore unrecognized patterns among the data derived from Stratum I-2b. It is argued such patterns are indicative of past practices enacted at the site, and association rules are utilized to paint a more nuanced portrait of the community of Tell Mastuma during the Iron II.
The rapid proliferation of digital data in Near Eastern Archaeology, precipitated by an ever expa... more The rapid proliferation of digital data in Near Eastern Archaeology, precipitated by an ever expanding array of data capture technology, has created an urgent need to establish a collaborative research environment with the capacity to address long-standing issues of access, data compatibility, integration and analytical capability. The CRANE (Computational Research on the Ancient Near East) Project is a multidisciplinary consortium of archaeologists, historians, paleo-environmentalists and computer scientists that seeks to facilitate the creation of such a collaborative framework. CRANE has focused on the Orontes Watershed, a cohesive geographical unit and region uniquely positioned as a cultural microcosm of the broader Near East, as an initial operational test case. CRANE also seeks to create computation tools that will facilitate the modeling and visualization of the interrelationships of social, economic and environmental dynamics at multiple spatial and temporal scales of analysis in order to gain more meaningful insight into the rise and development of complex societies in the ancient Near East. This Workshop will present a series of papers organized into four thematic sessions, drawing on the results of the CRANE Project achieved to date, with the aim of exploring the analytical capability and research utility of the CRANE collaborative approach.
The perception amongst archaeologists that data is intrinsically theory-laden has become axiomati... more The perception amongst archaeologists that data is intrinsically theory-laden has become axiomatic within the discipline. Yet, while data is becoming more commonly perceived in the discipline as dynamic, mobile, and dialectic, the data environment (i.e. the DBMS) is typically seen as static and immobile. This is further exacerbated by a specious notion that databases are simply objective place-holders of raw data; a subaltern environment of the ubiquitous computer. As Chrysanthi, et al. (2012, 7) recently note, archaeological computing with its wide range of applications and methodologies has gradually become central to most archaeological practice, yet computer applications are still viewed merely as a set of tools, albeit ones that oft provide an innovative means to overcome traditional problems and constraints. While the latter is undoubtedly true, such a mentality runs the risk of marginalising such methods and separates computational approaches from a more generally conceived archaeological practice. The unfortunate result, is that despite their importance and ubiquity, archaeological database systems are rarely the subject of theoretical analysis; this has been particularly true in North America (Labrador 2012, 236). Furthermore, the majority of archaeologists fail to recognize the potential of computer generated archaeologies as an appropriate context for reflexive interpretation (Gidlow 2000, 25). Subsequently, I would like to propose that databases be perceived as analytic environments in their own right; an enriching “third space” (to adopt the terminology coined by Soja 1996), in which lies the potential for knowledge discovery from archaeological data (KDAD). I contest that it is within such domains that knowledge is readily imagined, constituted, contested and re-conceptualised. Archaeological databases not only constitute a set of tools that enhance archaeological interpretation, but also provide an interactive interpretative environment.
Since the onset of the ‘New Archaeology’ of the 1960s, when archaeologists first began to impleme... more Since the onset of the ‘New Archaeology’ of the 1960s, when archaeologists first began to implement computational data storage as a means to organize the vast quantities of archaeological data accumulated during excavation, archaeological data has been continually compiled into large, heterogeneous databases. Certainly, this process has provided archaeologists the opportunity to use the abundance of documented data at their disposal to search for more meaningful patterns in the archaeological record.
Unfortunately, a preoccupation with data acquisition, organization, and management has led to a daunting amount of data, whose sheer volume appears to impede any form of comprehensive analysis. In the information sciences, large datasets that impede comprehensive and meaningful analysis are commonly referred to as “data graveyards”, a situation that has been described as “data rich but information poor” (Han et al. 2011). Recent advances in the information sciences have led to the development of a series of concepts and techniques, which assist in uncovering interesting data patterns buried in large, heterogeneous datasets; these concepts and techniques are known broadly as “data mining”.
The present paper provides a synthesis of the current state of database management and utilization in Meditteranean archaeology. Through a brief demonstration, I will illustrate the potential of machine-learning algorithms to reveal new patterns among large, heterogeneous archaeological datasets, to demonstrate how such techniques facilitate a more comprehensive understanding of the archaeological record.
Prior to the collapse of the Hittite Empire at the end of the LBA, sites across Anatolia and Syri... more Prior to the collapse of the Hittite Empire at the end of the LBA, sites across Anatolia and Syria evidence a homogenous and recognizable ceramic repertoire referred to as Drab Ware. Drab ware has been linked by scholars with the centralized political administration of the Hittite Empire (Gates 2001; Glatz 2009; Hanson and Postgate 1999); and although it is admittedly controversial to equate a ceramic tradition with a political entity, in this instance the indications are that this is broadly correct (Postgate 2007). Consequently, since the identification of this assemblage, scholars have sought to explain how such standardization was accomplished throughout an approximately 500km2 area. While some scholars argue the assemblage evidences the physical importation of pottery from a central point (or points) of distribution (Hanson and Postgate 1999; Postgate 2007; Müller 2005), others have argued the homogenized assemblage was a result of local craftspeople in different regions who learned common methods and standards (Gates 2001, Glatz 2009). The debate has been carried one step further, as after the decline of the Hittite Empire, new regional assemblages (characterized predominantly by painted wares) began to appear. Again, scholars have debated the origins of these wares.
In the following paper I outline a new theoretical paradigm, in which I will argue that advocating a revised dual-processual approach, which views the household as the primary socio-economic unit, allows for the rectification of two seemingly opposing models. The distribution and transformation of the ceramic assemblage in south-eastern Anatolia during the Late Bronze-Iron Age transition was a complex process, which involved corporate economic relationships at the household and communal scale, but was concomitantly confined by network relationships predominantly expressed by the ruling elite.
Cypriot Base Ring wares, or what are commonly referred to ‘Bilbils’, are a typological classifica... more Cypriot Base Ring wares, or what are commonly referred to ‘Bilbils’, are a typological classification of an assemblage of small juglets that appear for the first time at the beginning of the Late Bronze Age (ca. 1650 BCE) in Cyprus. The distinct shape of the vessel was new to the ceramic repertoire of LBA Cyprus and had no antecedents in Egypt or elsewhere in the Levant. The creation of these wares therefore represented a new tradition in commercial production and export. The Base Ring juglet was the most common among all Cypriot wares to be exported to Egypt, and undeniably has made up the largest proportion of all Cypriot pottery uncovered in Egypt thus far. Historically, the LBA in the Near East was characterized by ‘global’ diplomacy and interaction. In Egypt, the Late Bronze Age coincides with the Second Intermediate Period and the 18th Dynasty (ca. 1650-1352 BCE). For much of this period, Egypt was under the direct influence of a Syro-Palestinian population, the Hyksos, who facilitated trade between Cyprus, Syro-Anatolia, the Aegean, and Egypt. With the expulsion of the Hyksos, the 18th Dynasty in Egypt came to dominate this previously established network of exchange culminating in the Amarna period under Amenhotep IV. Provided the unique historical context in hich Base Ring I wares were manufactured and distributed, this particular ceramic form provides a unique opportunity to evaluate the role of a unique commodity within the socio-economic sphere of LBA Egypt.
Papers by Darren Joblonkay
Teaching Documents by Darren Joblonkay
A general survey of the growth and development of cultural heritage practices in the Middle East ... more A general survey of the growth and development of cultural heritage practices in the Middle East from the mid-19 th Century to the present; and an examination of contemporary issues in cultural heritage management in this region.
The growth and development of the discipline of Syro-Palestinian Archaeology in a general survey ... more The growth and development of the discipline of Syro-Palestinian Archaeology in a general survey of exploration, excavation and scholarly research; and an examination of the archaeological evidence from prehistoric times to the end of the Iron Age.
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Talks by Darren Joblonkay
of archaeological data, often through attempts to establish data “standards,” which has proven relatively unfruitful. Furthermore, as highly atomized, item-based data structures come to replace the traditional relational data model often utilized by archaeologists, it has become apparent that a data standard is not necessary as long as our data ontologies remain appropriately abstract (i.e., highly itemized). In doing so, we can conceive of DBMS not as simple repositories of data, but as analytical environments in their own right, wherein lies the potential for not only the accumulation, but the construction and contestation of knowledge from archaeological data (Knowledge Discovery from Archaeological Data [KDAD]). Following a brief excursus into the phenomenon of data mining and its implications within the discipline, this paper will focus on the implementation of a revised apriori algorithm (after Agrawal and Srikant 1994) for establishing associations among items in a dataset. The algorithm is applied to a dataset from Tell Mastuma, Syria, to elucidate heretofore unrecognized patterns among the data derived from Stratum I-2b. It is argued such patterns are indicative of past practices enacted at the site, and association rules are utilized to paint a more nuanced portrait of the community of Tell Mastuma during the Iron II.
Unfortunately, a preoccupation with data acquisition, organization, and management has led to a daunting amount of data, whose sheer volume appears to impede any form of comprehensive analysis. In the information sciences, large datasets that impede comprehensive and meaningful analysis are commonly referred to as “data graveyards”, a situation that has been described as “data rich but information poor” (Han et al. 2011). Recent advances in the information sciences have led to the development of a series of concepts and techniques, which assist in uncovering interesting data patterns buried in large, heterogeneous datasets; these concepts and techniques are known broadly as “data mining”.
The present paper provides a synthesis of the current state of database management and utilization in Meditteranean archaeology. Through a brief demonstration, I will illustrate the potential of machine-learning algorithms to reveal new patterns among large, heterogeneous archaeological datasets, to demonstrate how such techniques facilitate a more comprehensive understanding of the archaeological record.
In the following paper I outline a new theoretical paradigm, in which I will argue that advocating a revised dual-processual approach, which views the household as the primary socio-economic unit, allows for the rectification of two seemingly opposing models. The distribution and transformation of the ceramic assemblage in south-eastern Anatolia during the Late Bronze-Iron Age transition was a complex process, which involved corporate economic relationships at the household and communal scale, but was concomitantly confined by network relationships predominantly expressed by the ruling elite.
Papers by Darren Joblonkay
Teaching Documents by Darren Joblonkay
of archaeological data, often through attempts to establish data “standards,” which has proven relatively unfruitful. Furthermore, as highly atomized, item-based data structures come to replace the traditional relational data model often utilized by archaeologists, it has become apparent that a data standard is not necessary as long as our data ontologies remain appropriately abstract (i.e., highly itemized). In doing so, we can conceive of DBMS not as simple repositories of data, but as analytical environments in their own right, wherein lies the potential for not only the accumulation, but the construction and contestation of knowledge from archaeological data (Knowledge Discovery from Archaeological Data [KDAD]). Following a brief excursus into the phenomenon of data mining and its implications within the discipline, this paper will focus on the implementation of a revised apriori algorithm (after Agrawal and Srikant 1994) for establishing associations among items in a dataset. The algorithm is applied to a dataset from Tell Mastuma, Syria, to elucidate heretofore unrecognized patterns among the data derived from Stratum I-2b. It is argued such patterns are indicative of past practices enacted at the site, and association rules are utilized to paint a more nuanced portrait of the community of Tell Mastuma during the Iron II.
Unfortunately, a preoccupation with data acquisition, organization, and management has led to a daunting amount of data, whose sheer volume appears to impede any form of comprehensive analysis. In the information sciences, large datasets that impede comprehensive and meaningful analysis are commonly referred to as “data graveyards”, a situation that has been described as “data rich but information poor” (Han et al. 2011). Recent advances in the information sciences have led to the development of a series of concepts and techniques, which assist in uncovering interesting data patterns buried in large, heterogeneous datasets; these concepts and techniques are known broadly as “data mining”.
The present paper provides a synthesis of the current state of database management and utilization in Meditteranean archaeology. Through a brief demonstration, I will illustrate the potential of machine-learning algorithms to reveal new patterns among large, heterogeneous archaeological datasets, to demonstrate how such techniques facilitate a more comprehensive understanding of the archaeological record.
In the following paper I outline a new theoretical paradigm, in which I will argue that advocating a revised dual-processual approach, which views the household as the primary socio-economic unit, allows for the rectification of two seemingly opposing models. The distribution and transformation of the ceramic assemblage in south-eastern Anatolia during the Late Bronze-Iron Age transition was a complex process, which involved corporate economic relationships at the household and communal scale, but was concomitantly confined by network relationships predominantly expressed by the ruling elite.