Introduction
In this article, we explore some regional and national hobby metal detecting patterns in Norway and outline how these are largely the result of modern activities and management practices. Our main aim is to discuss some of the biases that affect the objects handed in by hobby detectorists and ask whether these artefacts are useful to those who seek to understand the past. Two aspects, namely how the metal-detected finds are recorded and how prolific individuals detectorist are, are particularly relevant. Our premise is that we regard the combined national hobby metal detecting finds record as ‘human’ big data (Green, Reference Green, Gillings, Hacigüzeller and Lock2020), an assumption we return to several times and ultimately challenge. We propose an open and pragmatic way of working with ‘messy’ and fragmented digital archaeological records—which are becoming increasingly detached from their analogue primary contexts—in a manner that transcends national borders, legislation, and practices.
Little research has been conducted on how recording and collection practices in Norway affect the metal-detected record. In England and Wales, work on data from the Portable Antiquities Scheme has shed light on how modern factors influence the collection and recording of metal-detected finds, particularly on a spatial-statistical level (e.g. Richards et al., Reference Richards, Naylor and Holas-Clark2009; Bevan, Reference Bevan2012; Robbins, Reference Robbins2013, Reference Robbins2014; Cooper & Green, Reference Cooper and Green2017). Assessing how such factors affect the Norwegian metal-detected record is a step towards understanding its potential and limitations as an archaeological source. Recognizing the specific national features of metal detecting is also useful for international comparisons, for both management and research purposes (Brodie, Reference Brodie2020: 87).
Hobby Metal Detecting and Legislation in Norway
The 16,948 records on which we base our analyses and discussion were gathered from Norway's five archaeological artefact databases (MUSITark). These serve as digital catalogues for the country's five regional archaeological museums (Figure 1). They are only accessible to museum employees and researchers granted (temporary) access. The nearly 17,000 finds make up the total number of archaeological objects reported by detectorists in Norway up to 2021.
Figure 1. Regions of the five archaeological museums, with the latter's locations (red dots). Left: County borders before 2020, with eighteen counties. A reform that came into effect on 1 January 2020 led to there being eleven counties. After a change of Government in 2021, referenda were held in many of the new counties and several returned to their former geographical and administrative boundaries on 1 January 2024. Right: county borders in 2023 (map: Jan Kristian Hellan).
Data about the objects are published in an open and searchable archive, called Unimusportalen (https://www.unimus.no/portal/#/), when fully catalogued. It is, however, not always clear whether an object was found and reported by a metal detectorist, since this information has most often been recorded in diverse ways and in different free-text fields. This can hinder access to data that should, and could, be easily available to the public (see Axelsen, Reference Axelsen2022 for further discussion).
Detectorists who are actively looking for archaeological objects or encounter them in their hunt for something else are the primary concern of archaeologists across Europe. The hobby and its practitioners are met by very different regional and national archaeological heritage management systems, including what, legally speaking, defines material remains as archaeological objects (e.g. Deckers et al., Reference Deckers, Dobat Ferguson, Heeren, Lewis and Thomas2018: 325; Dobat et al., Reference Dobat, Deckers, Heeren, Lewis, Thomas and Wessman2020: 272). At present, it is the Cultural Heritage Act (CHA) of 1978 that defines what forms part of the ‘official heritage’ (Harrison, Reference Harrison2013: 14) in Norway and hence what is the nation's primary archaeological source material.
In Norway, age is the main criterion used to decide whether something is protected (cf. Deckers et al., Reference Deckers, Dobat Ferguson, Heeren, Lewis and Thomas2018: 325). Unlike the automatic and formal protection offered to sites and monuments of a certain age in Norway (Gundersen, Reference Gundersen, Campbell, White and Thomas2019; CHA, 1978: § 4), objects, referred to as løse kulturminner (moveable heritage objects) in the Act, are given protection because no one is allowed to damage them (Holme & Stang, Reference Holme, Stang and Holme2020: 16; CHA, 1978: § 13). When it is deemed reasonable that it is no longer possible to establish the ownership of a moveable artefact (CHA, 1978: § 12), coins pre-dating ad 1650, all Sámi remains dated and pre-dating ad 1917, and all other physical remains dating and pre-dating ad 1537 are the property of the State (CHA, 1978). As a result, the collections that the five archaeological museums are responsible for hold a wide range of artefacts and materials from the prehistoric periods (until ad 1050) and the Middle Ages (c. ad 1050–1537).
As in Finland (e.g. Wessman et al., Reference Wessman, Koivisto and Thomas2016: 86) and Denmark (e.g. Dobat, Reference Dobat2013), it is not illegal to use metal detectors in Norway, and people who want to do so only need permission from the landowner(s) to search almost freely in a given area. It is, however, forbidden to metal detect on and near archaeological sites and monuments (Gundersen, Reference Gundersen, Campbell, White and Thomas2019; see also Axelsen, Reference Axelsen2021, Reference Axelsen2022 for further details). Metal detectorists are required to hand in objects fitting the age criteria described above. The Norwegian Directorate for Cultural Heritage has also developed national guidelines for the private use of metal detectors, in an attempt to ensure that most metal detecting activity complies with the CHA (Directorate for Cultural Heritage, 2017; see also Axelsen, Reference Axelsen2022).
Most of the hobby metal-detected finds are reported and handed in to the country's county municipalities. The findspot, and any other information about the find, is then recorded in Askeladden, the Directorate for Cultural Heritage's official database where all known and protected cultural and environmental heritage in Norway and on Svalbard are listed. Most of the information from Askeladden is available to the public through the site Kulturminnesøk (https://www.kulturminnesok.no/). Objects found on land are handed by the county municipalities on to the archaeological museum responsible for their region because it is the regional archaeological museums that are responsible for managing the country's collections of non-maritime archaeological finds.
Organically grown databases
The creation and continued re-creation of the institutional archaeological databases of the regional archaeological museums in Norway has been described as ‘organic’ by some (Axelsen, Reference Axelsen2021: 57). This, in part, reflects how their development followed the design implemented when the databases were established in 1988 (Matsumoto & Uleberg, Reference Matsumoto, Uleberg, Piotrowska and Konieczny2015: 159). After two digitization projects in the 1990s, the joint university museums’ IT organization (MUSIT) was established in 2007, including both natural and cultural-historical museums, and ended in 2021 (Matsumoto & Uleberg, Reference Matsumoto and Uleberg2021). It was the result of a long-held and shared belief in a common national standard for the storing and sharing of scientific records, making them accessible and usable by researchers and the public alike (Uleberg & Matsumoto, Reference Uleberg and Matsumoto2009: 1–2; Matsumoto & Uleberg, Reference Matsumoto, Uleberg, Piotrowska and Konieczny2015: 159). Building on this work, the operation and maintenance of the cultural-historical university museums’ various collection databases is, for now, ensured through UniMus:Kultur (Uleberg et al., Reference Uleberg, Matsumoto, Pantos and Bonelli2023: section 1).
Data fields are largely identical in all five databases. Yet, despite a common standard being the goal, normalization and standardization of the individual records across and within museum regions have not been a priority (Uleberg & Matsumoto, Reference Uleberg and Matsumoto2009: 3; Uleberg et al., Reference Uleberg, Matsumoto, Pantos and Bonelli2023: sections 2 and 3). Many fields are free-text entries, with as little or as much text as a data recorder wants to enter and in a manner that suits them best. Consequently, fields that should be standardized, e.g. information such as the year a find was made or its coordinates, is not. Researchers who want to use the data thus have to spend time on extensive data cleaning after exporting what they need from the artefact databases.
Digital data floods of ‘human’ big data
Archaeological research increasingly relies on digital data and methods (e.g. Huggett et al., Reference Huggett, Reilly and Lock2018; Huggett, Reference Huggett2020: 15). Databases are rapidly growing, and seem even less likely to de-accession potentially useful digital records than their physical counterparts. While most physical and digital archaeological records have so far been collected by professionals, private finders have also contributed to these collections since the creation of the Norwegian archaeological university museums (Shetelig, Reference Shetelig1944). The situation is similar in many European countries, and the proportion of finds reported and handed in by non-professionals is increasing as the popularity of hobby metal detecting is growing.
There have been at least two clear and steep increases in the quantity of recorded finds in Norway (Matsumoto & Uleberg, Reference Matsumoto and Uleberg2021: fig. 3). The first is the result of extensive burial mound excavations from 1870 to 1880. The second is a consequence of an increase in large and mandatory excavations after 2000 and the dramatic influx of reported hobby metal-detected finds after 2014 (see Axelsen, Reference Axelsen2021). This ‘flood’ of digital data is not unique to Norway, and has been referred to as a ‘data deluge’ in England (e.g. Bevan, Reference Bevan2015; Cooper & Green, Reference Cooper and Green2017) and overlaps with a long-standing concern over a ‘curation crisis’ within the field (see, e.g. for Sweden, Friberg & Huvila, Reference Friberg and Huvila2019: 364–66, with references). This is making existing issues concerning archaeology's data management practices even more pressing. Among these are a lack of standardization, both within a country and between them, and a common ontology that would make it easier to aggregate the many datasets that are available through infrastructure systems such as ARIADNEplus (Green, Reference Green, Gillings, Hacigüzeller and Lock2020: 433; see also Dobat et al., Reference Dobat, Deckers, Heeren, Lewis, Thomas and Wessman2020: 276).
Archaeological collections in general contain a multitude of different materials, such as various forms of grey literature, samples, photographs, field diaries, and physical remains. The same is true for the records from hobby metal detecting. We suggest that the digitized information on these finds constitute what Green (Reference Green, Gillings, Hacigüzeller and Lock2020: 432–33) has referred to as ‘human’ big data. In contrast to ‘big data’, human big data is not defined by its size, but rather by the opportunity it provides to aggregate multiple and varied datasets and search across them (see also Boyd & Crawford, Reference Boyd and Crawford2012: 663). Referring to Gattiglia (Reference Gattiglia2015: 114), who sees ‘big data’ as a concept, Green considers that, while ‘big data’ is high in volume, velocity, and variety, these factors are relative rather than absolute.
Building on this, Green (Reference Green, Gillings, Hacigüzeller and Lock2020: 433) offers the following useful definition of ‘human’ big data as ‘datasets that are too complex and/or large to process without the use of computer algorithms/scripts’. He adds that these datasets can also be analysed ‘in an exploratory manner’, with hypotheses deriving from the analyses rather than the other way around. This is similar to McCoy's description of the process of ‘knowledge discovery’, a term from the field of data science; the aim is to use quantitative and/or computational methods to find, for example, ‘new patterns’ (McCoy, Reference McCoy2017: 76). Working with this type of data requires embracing a certain level of ‘messiness’ (Gattiglia, Reference Gattiglia2015: 114). The degree of ‘mess’ can, however, be lessened by taking several precautionary steps, as outlined by Green (Reference Green, Gillings, Hacigüzeller and Lock2020: 433). These are: 1) plan ahead; 2) explore the history of the existing datasets; 3) document the quality of the datasets; 4) establish common ontologies; 5) use big data analytics to identify anomalies.
Although hobby metal-detected finds in Norway are, for now, hardly ‘big data’, strictly defined by a set quantity of tera- or petabytes (McCoy, Reference McCoy2017: 76), they do fit the definition of ‘human’ big data. To make it possible to gain quantitative and qualitative information across a growing number (and sizes) of datasets on a national, European, and even global scale, the precautionary measures suggested by Green are, we believe, a necessity (see also McCoy, Reference McCoy2017). Doing this in close cooperation with others—including knowledge exchanges and discussions of the process—is clearly beneficial, allowing data to be ‘things made’ rather than ‘things given’ (Huggett, Reference Huggett2020: 9).
Collecting and analysing the national metal detecting record
Our dataset consists of records collected on three separate occasions: 12 August 2019, 27 September 2021, and 14 March 2022. These dates are random, unconnected to the flow of incoming reported metal-detected finds. They are nonetheless given, so that any significant changes in the datasets connected to these dates can be scrutinized. The two first searches were conducted individually and joined in a combined database. The searches undertaken in 2021 and 2022 were more targeted than the first, as the recording of metal-detected finds seems to have become fairly standardized across the museums in the last five years (Table 1). We had both conducted several extensive and separate searches in the five archaeological artefact databases, leading up to the three main searches that form the foundation of our combined Access database and the analyses presented in this article. The search criteria used to identify the metal-detected finds are summarized in Table 1 (for how the search criteria were determined, see Axelsen, Reference Axelsen2021: 172–73; Fredriksen, Reference Fredriksen2023: 61–69).
Table 1. Combined results of database searches.
When working with digitized (or ‘born-digital’) archaeological data, considering and treating the information as ‘human’ big data is potentially fruitful. It can be difficult to find and use different types of archaeological data in rapidly growing databases where the information they contain is not always standardized or normalized (Axelsen, Reference Axelsen2021: 54–55, 212). Open and exploratory qualitative and quantitative searches and analyses, we suggest, are a practical method for identifying, gathering, and making use of the material. Additionally, such exploratory searches are especially useful when undertaken by different people, with the aim of later combining the results and achieving ‘knowledge discoveries’. It requires time and effort, but, when well documented, the process can help improve both the current and future data quality and the potential of archaeological databases, and thus the potential for aggregating them.
Assumptions from archaeological theory always precede data collection and analysis, and indeed analysis will be constrained by the theoretical constructs applied during the recognition, categorization, and collection of the data (Huggett, Reference Huggett2020: 14). Being open and clear about the many factors that influence the chosen data are vital (e.g. Lock, Reference Lock2009: 82).
Relating to this, although our searches can be replicated by using the data provided in Table 1, it should be noted that some museums transfer partially catalogued records from their accession database to their artefact databases. Hence, the data in both databases may be deleted later when an artefact is deemed not to qualify as ‘official heritage’ and consequently is not included in the archaeological collections. Because of this, and the fact that some finds are handed in to the museums several years after they were discovered by hobbyists, the reported and recorded number of metal-detected finds will always be an estimation. Even though the number of finds in some areas means that many of the large-scale trends are unlikely to change significantly, others may look quite different within a relatively short time span.
On 12 August 2019, the database contained 10,277 unique records. On 27 September 2021 it was 15,274, and by 14 March 2022 it had reached 16,948. The increase between September 2021 and March 2022 is primarily owed to finds being discovered in 2020. There are, however, also minor increases in the number of recorded finds in most years between 2002 and 2019. These finds are likely to have been handed in some time after they were discovered by metal detectorists, and/or stored by the county archaeologists for a while before being passed on to the museums. Until 2021, it took all the museums at least two years to fully record the finds, but most of them seemed to have accessioned them as soon as they arrived. By 2023, only the Museum of Cultural History in Oslo spent more than two years on cataloguing a metal-detected find.
Do Messy Inputs Equal Useless Outputs?
The ‘organic growth’ of the Norwegian artefact databases has, not surprisingly, resulted in some inconsistencies in the recording of archaeological objects, particularly those handed in by metal detectorists and other private finders. Neither the digital recording systems nor the museum's internal infrastructure were equipped to handle the steep increase in the detecting activity from 2014 onwards (Figure 2). Consequently, archaeologists tasked with recording archaeological artefacts had to create makeshift ‘categories’ within various free-text fields when documenting the circumstances of discovery of a metal-detected find (Table 1). Additionally, there were too few people at some museums capable of recording archaeological objects in a timely manner while also ensuring the consistency and integrity of the treatment and documentation of the hobby metal-detected finds.
Figure 2. Yearly increase in the number of reported hobby metal-detected finds between 2000 and 2020, per museum and nationally.
One example of the lack of standardization within and between the archaeological museums is the field funnår (‘find year’). Although most records consulted note a year, the majority also include the date an object was found. There are also several cases of a descriptive and longer text in the find year field, such as ‘over a period of 34 years’, ‘probably [year]’, ‘[season] [year]’, and the date is given in various ways. For records without a year given in the relevant field, the year the find was accessioned was used.
Another factor to consider is the lack of a standardized way of describing the hobby metal-detected finds. As Table 1 shows, the number of hits using the chosen search terms does not necessarily match the actual number of metal-detected finds in the database. The Museum of Archaeology in Stavanger, for example, included the phrase ‘metal detecting’ in the description of all the collected material from archaeological excavations, if metal detectors were used on the project. When collecting and combining the datasets from all five archaeological museums, this should be taken into consideration. In the following, we highlight and discuss some of the key factors that are contributing to differences in detecting activity between the regions served by the five museums.
Regional and local differences in recording practices and metal detecting activity
Although the national guidelines for the private use of metal detectors have been in effect for a few years now, the same regional differences that were visible in the metal-detected material before 2017 (Axelsen, Reference Axelsen2021: 131–32, 139, 176–96) are still visible. There are, of course, large geographical and historical variations between the management areas of the archaeological museums. They also vary in size, population, population density, and the surface of cultivated land within and between the regions (Table 2). This must be taken into consideration when assessing where metal detectorists are able to operate. The Museum of Archaeology's area is the smallest, consisting of only one county with a land area of 8575 km2. The Arctic University Museum of Norway's management area, on the other hand, which cover the country's two most northern counties, is twice the size of Denmark (Figure 1, Table 2).
Table 2. Population size and density, area size, and percentage of cultivated land in each museum region. Data and percentages were collected and calculated from data of the Statistics Norway's open access tables ‘11342: Population and area (M) 2007 – 2020’, ‘06462: Agricultural area for selected crops (decares) (M) 1969 – 2020’, and ‘11506: Agricultural area, by use (decares) (C) 1969 – 2021’. Only ‘fulldyrka mark’ (arable land) in the category ‘cultivated land’ is included. Surface-cultivated and infield pastures are excluded.
Considering the size of the area it serves, population density, and amount of cultivated land, it is not surprising that the Museum of Cultural History in Oslo has the largest number of detectorists who report their finds and the highest number of recorded metal-detected finds. Some seventy-five per cent of Norway's cultivated land and forty-seven per cent of the population is within the management area of the museum (Table 2). There are, however, also large differences between the counties served by the Oslo-based museum, with almost ‘empty’ areas such as Agder and very find-rich counties such as Vestfold and Telemark, Viken (predominately within the area of the former county of Østfold), and Innlandet (Figure 3).
Figure 3. Number of reported and recorded metal-detected finds per county.
One reason for the difference in the number of recorded detectorists and quantity of reported metal-detected finds may be in the way findspots are recorded in Askeladden. Four labels are currently used to classify the location of an archaeological object: 1) automatically protected; 2) unresolved; 3) not protected; 4) removed (see Figure 4). Data from Askeladden show that the country's (per 2023) eleven counties use different classifications. These categories affect whether it is legal for a detectorist to continue detecting on, for example, parts of or an entire field. Detecting on a listed site is not permitted without an exemption from the CHA by the relevant county. Additionally, the guidelines for the private use of metal detectors advises detectorists to avoid detecting within a 25 m radius from sites labelled as automatically protected or unresolved (Directorate for Cultural Heritage, 2017: 3).
Figure 4. Distribution of differentially recorded findspots in the Askeladden database. The data was downloaded 30.1.2020.
For the archaeologists who record and list the sites, it is not necessarily evident whether an area should be recognized as, for example, automatically protected. A letter of 2019 from the Directorate for Cultural Heritage to the country's archaeological museums and counties stated that when an unspecified number of finds indicates the presence of a site, it should be considered as automatically protected (Directorate for Cultural Heritage, 2019). Because perceptions and practices concerning hobby metal detecting vary (Axelsen, Reference Axelsen2021: 71–74; Fredriksen, Reference Fredriksen2021), detectorists can continue detecting on finds-rich fields in counties where find spots are usually classified as not protected or removed.
In counties where findspots are normally categorized as automatically protected or unresolved, detectorists must either apply to the county to continue detecting on the site or move at least 25 m away from its perimeter. This affects the number of objects that can be reported and handed in from fields within a county. When compared to the others, Innlandet stands out as the county with the highest frequency of unprotected find spots. Counties other than Trøndelag, Vestland, Troms, and to some extent Rogaland, prefer to classify finds in the unresolved category (Figure 4).
Prolific detectorists as ‘super users’
The most important factor influencing the representativity of the recorded metal-detected material is the activity level of individual detectorists. At one archaeological museum, two detectorists handed in around 44.3 per cent of the hobby metal-detected finds. Nationwide, the thirty most prolific finders, which includes one detecting club, have handed in about 39.7 per cent of the total of 16,948 metal-detected finds. In all, some 1063 different names were recorded as having reported protected objects before 14 March 2022 (Table 3). Records including a slash, indicating that one or more detectorists have detected together, were excluded. Most recorded detectorists in the artefact databases handed in few finds: about ninety-three per cent had, until 2020, reported fewer than fifty objects, with 837 people (79 per cent of the 1063 recorded finders) reporting ten or fewer finds. On the other hand, eleven different names, i.e. only one per cent of the total number of detectorists, had reported more than 200 protected objects. Those in the middle, who handed in between fifty and 200 artefacts, consist of sixty-one people, making up close to six per cent of the (recorded) hobby detecting group.
Table 3. Number of reported and recorded metal-detected finds and hobby metal detectorists, and their percentages per museum.
*Because forty names were recorded as having handed in finds at more than one museum, the total number of detectorists differs from the combined numbers from each museum.
These proportions are similar to what has been observed in other citizen science projects, where a so-called ‘one per cent’ or ‘90-9-1’ rule has been described (e.g. Haklay, Reference Haklay, Capineri, Haklay, Huang, Antoniou, Kettunen, Ostermann and Purves2016: 36). These projects show that it is common for a very small group representing about one per cent of the contributors or participants to be behind most of the activity, while the overwhelming majority only contribute occasionally. In other words, the ‘super users’—or ‘super detectorists’ in our case—are unlikely to be representative of the group in general. Although, being significant contributors and thus receiving much attention, they are, statistically speaking, outliers (Haklay, Reference Haklay, Capineri, Haklay, Huang, Antoniou, Kettunen, Ostermann and Purves2016: 36; see also Dobat et al., Reference Dobat, Christiansen, Jessen, Henriksen, Jensen and Laursen2019: 12–13).
The number of recorded detectorists in Norway may seem low when compared with other countries, such as the estimated 9600 metal detectorists in England and Wales (Robbins, Reference Robbins2014: 14). According to the Portable Antiquities Scheme annual reports (2018, 2019, 2020), individual contributors to the scheme numbered 4028 in 2018, 4143 in 2019, and 2846 in 2020. The 1063 recorded detectorists in Norway, in a population of c. 5,400,000, equals approximately twenty detectorists per 100,000 inhabitants. In terms of population size, the number of detectorists in Norway is similar to estimates of c. 15–30 detectorists per 100,000 inhabitants in other north-western European countries (Deckers Reference Deckers, Campbell, White and Thomas2019: 111).
It has been suggested that there is a conscious ‘selection’ of Norwegian medieval coins among metal detectorists in Norway, causing some to question the reliability of the recorded information for all metal-detected finds (Gullbekk et al., Reference Gullbekk, Sættem, Skogsfjord and Roland2019). The sale and circulation of Norwegian medieval coins without provenance (Gullbekk et al., Reference Gullbekk, Sættem, Skogsfjord and Roland2019: 178) certainly suggests that some people are illegally recovering these coins, with or without the aid of a metal detector (see also Mackenzie et al., Reference Mackenzie, Brodie, Yates and Tsirogiannis2020: 5). It should, however, be noted that the distribution of the Norwegian coins outlined by Gullbekk et al. (Reference Gullbekk, Sættem, Skogsfjord and Roland2019) seems to correlate with areas that have particularly prolific detectorists. Other possible explanations, or at least contributing factors, for the potential discrepancy in the coin material handed in by metal detectorists is that the hobbyists operating in these areas are:
1) more skilled, recognizing the coins, which, due to their small size and low levels of silver, are indeed hard to notice in cultivated soil;
2) more thorough than the less prolific finders—i.e. they investigate (more of) the so-called ‘poor’ signals (Axelsen, Reference Axelsen2021: 125).
Given what we know about other citizen science projects, it is plausible that prolific detectorists uncover and report not only more finds than the average detectorist, but also more different types of objects than the less prolific finders.
When looking at the distribution of the metal-detected finds in Norway (Figure 3), ‘hotspots’ appear in two geographical groupings, in south-eastern Norway and in northern Norway. In the two counties that are split between different museums, there are far more finds within one museum's area than the other. The recorded metal-detected finds in, for example, Nordland are concentrated in the northern municipalities, which lie within the Arctic University Museum of Norway's management area. The southern part of Nordland is at the outer limit of the NTNU University Museum's region.
Norway's concentrations of metal-detected finds are owed to a few individual detectorists and detecting clubs. Consequently, the productivity of a small minority, combined with how a handful of archaeologists choose to record findspots, may continue to influence the representativity of the collected material in the future. This can strengthen already visible patterns. Current trends could also change dramatically with an influx of prolific detectorists in areas which so far had very few mapped finds.
Qualitative-Quantitative Data
If the number of yearly reported finds is steady, or increases, Norway is likely to pass 30,000 hobby metal-detected finds during 2027. As exposed above, the combined national detecting dataset can be described as ‘human’ big data. Although it does not exceed a large and set number of tera- or petabytes (McCoy, Reference McCoy2017: 76), it still requires exploratory computational and quantitative analyses when examined as a whole. In addition, the many qualitative factors influencing the data must be considered. This is why we choose to describe these data as qualitative quantitative data.
As Lock has argued, scale is an underlying factor for most archaeological work: ‘We routinely move from pot sherds to questions of social and economic relationships’, albeit without asking whether such work is ‘enabled or hindered by computer technology’ (Lock, Reference Lock2009: 76; see also Huggett, Reference Huggett2020). All data can be qualitative and quantitative, it simply depends on the level at which one is working (Lock, Reference Lock2009: 75). As suggested earlier, this is not unique for the hobbyist material, as the messy ‘human’ nature of big (or small) archaeological datasets is difficult to avoid. This also means that hobby metal detecting in Norway is rather typical—both for archaeological material in general and for the objects found by detectorists in particular.
Our results show that detectorists, but also archaeologists, influence the representativity and general data quality of the recorded material. Even so, the material handed in by the hobbyists can, and already is, leading to new discoveries and insights about the past. Below, we briefly highlight the issue of a lack of trust, which is particularly pressing for the reuse of the metal-detected material. We suggest ways of alleviating this relatively widespread mistrust and coping with the flood of data collected by citizens. A frequent issue for quantitative data, particularly data collected as part of citizen science projects, is that it is ‘used for purposes they are not suitable or fit for’ (Balázs et al., Reference Balázs, Mooney, Nováková, Bastin, Jokar Arsanjani, Vohland, Land-Zandstra, Ceccaroni, Lemmens, Perelló and Ponti2021: 147). This can be counteracted by some of the steps outlined below.
Coping with data floods from citizen scientists
One response to hobby metal detecting in countries lacking a national and common standard for recording finds has been to establish public finds recording schemes. This practical response to the growing popularity of hobby metal detecting is designed to make information about the metal-detected finds available and accessible to both the public and researchers (Dobat et al., Reference Dobat, Deckers, Heeren, Lewis, Thomas and Wessman2020).
Compounded with digital records that stem from archaeological projects, the rapidly escalating quantities of digital data from private individuals are causing Danish, English, and Welsh archaeology to experience their versions of big data floods (Bevan, Reference Bevan2012; Dobat et al., Reference Dobat, Deckers, Heeren, Lewis, Thomas and Wessman2020). Other countries with similar recording schemes, such as Flanders in Belgium (MEDEA), Finland (FindSampo), and the Netherlands (PAN), may experience the same data growth in years to come (e.g. Deckers et al., Reference Deckers, Bleumers, Ruelens, Lemmens, Vanderperren and Marchal2016; Vos et al., Reference Vos, Heeren, Ruler, Smallenbroek and Lassche2018; Wessman et al., Reference Wessman, Thomas, Rohiola, Koho, Tuominen, Jameson and Musteaţă2019). When data from these schemes are made accessible and adhere to a common standard and ontology, their scientific value and thereby the potential for new discoveries will increase as this will enable both qualitative and quantitative aggregation (Gattiglia, Reference Gattiglia2015: 113).
Compared to other European recording programmes, the Norwegian archaeological heritage system was among the earliest to make their data publicly available and reusable. This includes the metal-detected objects. Parts of the country have been overwhelmed with new finds, creating a backlog in fully recording the reported finds; although they are eventually fully recorded. Most of the stored information is made available to both the general public and researchers. Because of the lack of standardization in input data, it is, however, often not possible to identify finds has having been metal-detected, which is troublesome given the public interest in and origin of this finds group (Axelsen, Reference Axelsen2022).
Consequently, Norwegian databases, such as Kulturminnesøk and Unimusportalen, already meet the aims of the European Finds Recording Network, as summarized by Dobat and colleagues (Reference Dobat, Deckers, Heeren, Lewis, Thomas and Wessman2020). Work on a national digital finds recording scheme was initiated in summer 2023 by the Directorate for Cultural Heritage and the Museum of Cultural History in Oslo. This can ease the administrative burden for the national heritage management system, as well as the volunteer work of some of the country's most prolific citizen scientists (Axelsen, Reference Axelsen2022).
Trust and reuse of data
Many archaeologists do not trust the ability or willingness of some detectorists to offer accurate information about the finds they report (see Gullbekk et al., Reference Gullbekk, Sættem, Skogsfjord and Roland2019; Axelsen, Reference Axelsen2021: 122–26). Consequently, there is a lack of trust towards the data originators from those who would normally use the recorded data (Huggett, Reference Huggett, Wilson and Edwards2015: 18). Despite this, material collected by metal detectorists is frequently used in studies that include archaeological material obtained by conventional means (see Røstad, Reference Røstad2016 or Amundsen, Reference Amundsen2021 for recent examples).
Modern factors are clearly influencing the metal-detected material, in Norway and elsewhere. This, we contend, does not mean that the material is useless or ‘unfit’ for archaeologists who seek to understand the past. The biases affecting the distribution patterns of metal-detected finds, such as the productiveness of individual detectorists and the recording practices of archaeologists, is a growing field of research (e.g. Bevan, Reference Bevan2012; Cool & Baxter, Reference Cool and Baxter2016; Cooper & Green, Reference Cooper and Green2017; Oksanen & Lewis, Reference Oksanen and Lewis2020). By conducting exploratory, quantitative, and/or qualitative analyses of the material, we can better understand how we can and cannot use the finds discovered by detectorists.
Because non-professionals often lack the detailed knowledge and standards of the professionals, the data they gather can be met with suspicion and may lead to some researchers refusing to use the information at all. This can, as Balázs et al. (Reference Balázs, Mooney, Nováková, Bastin, Jokar Arsanjani, Vohland, Land-Zandstra, Ceccaroni, Lemmens, Perelló and Ponti2021: 147) point out, to some extent be remedied by ensuring that the relevant metadata and paradata is acquired and stored (see also Huggett, Reference Huggett2020: 12; Huvila, Reference Huvila2022). In Norway, the information about archaeological objects uncovered and reported by metal detectorists, although meant to follow a certain standard set by the national guidelines, varies in its accuracy. This is, in part, due to factors and practices that create biases in the collections and which are specific to hobby metal detecting (cf. Robbins, Reference Robbins2013, with references; see also Axelsen, Reference Axelsen2021: 205–08 for a summary of the situation in Norway). Moreover, the technical skills and digital literacy of the individuals using metal detectors to search for protected objects are, allegedly, affecting the precision of the reported data (Gundersen et al., Reference Gundersen, Rasmussen and Lie2016: 165–68; Axelsen, Reference Axelsen2021: 122–26). Worryingly, this information is not stored anywhere. Neither public finds recording schemes nor archaeological systems are, for now, taking this into account.
Although the many free-text fields in the Norwegian artefact databases allow for a substantial amount of contextual information to be recorded, the records are still ‘largely de-contextualised’ (as Huggett, Reference Huggett, Wilson and Edwards2015: 18 has argued; see also Huggett, Reference Huggett2020: 12). The information that has been given is recorded, usually by someone who is not the finder, and documented in a format that suits archaeological catalogues. What we lack is a systematic way of recording how the data was originated, how it has been treated, by whom, and how this and the digital systems themselves affect the material and how it can be used. To increase trust in hobby detecting records and thus the future use of it, that knowledge is vital. In other words, we need to ‘[find] the people within the systems’ (Huggett, Reference Huggett2020: 15, in reference to and paraphrasing Seaver, Reference Seaver2018: 382) to understand their ‘actions and decisions’. Hence a robust way of recording such information is necessary to ensure the integrity of the material.
Concluding Remarks
Our examination of some of the regional and national hobby metal detecting patterns in Norway indicates that these are primarily the result of modern activities, such as that of a few very prolific finders in certain areas, and management practices. We urge researchers who wish to use metal-detected material to consider these factors in future research. This study, by employing what we have referred to as ‘human’ big data (or simply ‘large datasets’) is a step towards ‘address[ing] sampling biases within the data’ and achieving a better understanding of ‘national monument event databases’ (Huggett, Reference Huggett2020: 13).
Key factors were the observations and reflections we both made when working with the databases individually. Working at two different regional archaeological museums, with their own histories and recording practices, meant that our perspectives and experiences differed. When combining our efforts, we had immediate access to a wider network of museum workers and archival information. This led to fruitful exchanges about the nature of the records and the way they should be interpreted and used.
We hope that this study will stimulate further discussion on the human and messy nature of archaeological data, whether generated by the public or professional archaeologists, as well as promote the comparison of data beyond national borders and legislations. The findings presented here are a step towards avoiding assumptions on the extent and characteristics of Norwegian metal detecting—and by extension European hobby detecting—in future discussions.
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