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Figure 1: Preview of NeoNet Med and NeoNet Atl dates for the Late Mesolithic/Early Neolithic transition of the North Central-Western Mediterranean and Southern European Atlantic river basins

Presentation

The NeoNet app aims to contribute to the study the pioneering front of the farming live-style (i.e., Neolithic) by focusing our study on the mobile border between the Last Hunter-Gathers economy and the Early Neolithic (ca. 7,000 BC to 3,500 BC) in the Central-Western Mediterranean and European South Atlantic basins. The interactive web app facilitates the selection of absolute dates (radiocarbon dates) by providing selection tools for:

  • spatial
  • geographical region of interest (ROI)
  • custom selection shape inside the ROI
  • chronology
  • date time span between a tpq and a taq in cal BC
  • main periods (Middle Mesolithic, Late Mesolithic, Early Neolithic, …)
  • date accuracy
  • some type of material life duration (short like, long life or others)
  • threshold of the maximum accepted standard deviation (SD)

The NeoNet app has been created in the frame of the NeoNet work group from a perspective of FAIR Science and collaborative working. It is still in development. This page is a tutorial for contributing and using the app. We will see how it works, what is the format dataset and what are our objectives

NeoNet app

The app is a RShiny hosted on the Università di Pisa server. The app is divided into five (5) panels:

  1. map panel: spatial filtering with selection menus on dates
  2. calib panel: calibration of the selected dates
  3. data panel: the whole dataset
  4. biblio panel: bibliographical references
  5. infos panel: credits and link to the webpage handbook of the app

To provide a handy user interface, NeoNet app joins a main dataset with to two correspondance tables:

  • main dataset: 140_id00140_doc_elencoc14.tsv
  • bibliographical references: id00140_doc_reference.bib
  • material life duration: id00140_doc_thesaurus.tsv

So the NeoNet dataset is composed by two TSV files (dataframes with tab-separated values) and one BIB file (BibTex file, see: NeoNet dataset v.1

1. map panel

The panel map is a geographical window provided by the Leaflet package. This panel is used for selection of radiocarbon dates by location, by chronology, by quality of dates. Once selected, dates can be calibrated

The different menus of the map panel

Figure 2: The different menus of the map panel

The current functions are:

  • Fig. 2, red box, top-left radio button group C14 on map: allows to cluster dates by spatial proximities (Marker Clusters)

  • Fig. 2, pink box, top-right layer button: allows to change the basemap.

  • Fig. 2, green box, inline text: reactive count of selected dates and sites. The bottom table is a reactive DT package datatable listing all the dates within the map extent (ROI) and the optional selection menus (tpq/taq, material life duration, maximum SD, periods, selection shapes)

basemaps

By default, the basemap is OSM, an OpenStreetMap general basemap, but it can be switch to Topo, an ESRI topographical basemap or others

Koppen Climate Classification 6 kyears ago (6000 cal BP) on Neonet dev version
Koppen Climate Classification 6 kyears ago (6000 cal BP) on Neonet dev version

select by location

By default only the data within the window extent (ROI) will be selected. But selection shapes can be drawn inside this ROI to have a spatial intersection:

Fig. 2, black box, top-left draw toolbar: selection shapes, polygons and rectanges, can freeze the date selection inside a given ROI. They can be removed with the trash button. All the dates inside the ROI and selected with the others filters will be visible on the map, but only those inside the selections shapes will be calibrated

selection inside a shape, here a single polygon. Before shape selection: 190 sites and 895 dates. After shape selection: 13 sites and 68 dates
selection inside a shape, here a single polygon. Before shape selection: 190 sites and 895 dates. After shape selection: 13 sites and 68 dates

retrieve coordinates from the map

As said, the default basemap of the app is OSM. It offers a well documented basemap where archaeological sites are sometimes already located, like the Ligurian site of Grotta della Pollera. Clicking on the map show the lat/long coordinates of the current point (under the tpq/tap slider). These coordinates can then be copied and used to modify the NeoNet dataset

get coordinates by clicking on the map
get coordinates by clicking on the map

select by chronology

  • Fig. 2, brown box, top-right checkboxes: allow to select dating by periods. The orange box, bottom-left legend, is reactive and update depending on selected periods

  • Fig. 2, blue box, bottom-left slider: allows to subset a range of accepted dates between a tpq and a taq (in cal BC)

select by dates quality

  • Fig. 2, purple box, bottom-right checkboxes and slider: a group of menus for selection on the material life duration and max accepted SD:
  • relatively to the duration of their material (short to long-life material)
  • below a maximum accepted threshold for the standard deviations (SD) for the dates

calibrate dates

The dates displayed in the table of the map panel will be calibrate when one of them has been clicked.

click on a date to calibrate a selected group of dates
click on a date to calibrate a selected group of dates

export selected dates and aera

Export selected dates and area sorted by clicking the download buttons (top left)

Export selected dates and aera
Export selected dates and aera

Dates will be exported as a GeoJSON file, with a unique id (idf_nn). The file can be curated and analysed in a GIS or using the NeoNet package (isochrones, etc.)

2. calib panel

The panel calib is used for analysis. Calibration of selected dates are done on-the-fly with the R package rcarbon. If the dates are numerous (e.g., > 100) the computing time could take times, be patient.

calibration of selected radiocarbon dates
calibration of selected radiocarbon dates

This date which have been clicked on the map panel will be shown bolded on the output figure

C14 group by filter

The c14 group by filter (Fig. 3, red box) allows to plot dates and to sum their probability densities depending on different levels of grouping:

  • by datation (by LabCode). Each radiocarbon date is plot separately (by default)

  • by site and layer (= SiteName and PhaseCode). Dates from the same site, having the same archaeological unit (layer, structure, etc.), are summed. See the PhaseCode field.

  • by site and period (= SiteName and Period). Dates from the same site, having the same period are summed

  • by period (= Period). Dates having the same period are summed

  • all C14. All dates are summed

The different menus of the calib panel

Figure 3: The different menus of the calib panel

plot area output

The plot area (Fig. 3, orange box) shows dynamically the SPD of the cabibrated dates seriated on their weighted means. The top-right button Download (Fig. 3, green box) allows to export the last plot in a PNG image

3. data panel

The complete dataset from the GitHub 140_140_id00140_doc_elencoc14.tsv file (ie, NeoNet dataset v.1). Today, the dataset counts 2506 dates:

Table 1: Dates sample
SiteName Country Period PhaseCode LabCode C14Age C14SD Material MaterialSpecies tpq taq Longitude Latitude bib bib_url
Vergentiere France MN Layer 3 Ly-2646 5110 130 wood charcoal n/d -4238 -3645 5.328700 47.78542 Lepage 1992 Lepage92
Piancada Italy EN Q: F2 OZB-949 6280 80 wood charcoal n/d -5471 -5031 13.096376 45.80579 Mazzucco et al. 2020 https://doi.org/10.1371/journal.pone.0232455.s002
Baume de Ronze France EN Ensemble 1a-1b Ly-6087 6340 40 wood charcoal n/d -5466 -5215 4.404267 44.31844 Banadora BD Banadora21
Cueva de Nerja Spain EN NM-9 OxA-26084 6254 33 animal bone Ovis aries -5311 -5072 -3.844529 36.76287 Garcia Borja et al. 2018 GarciaBorja18
Grotte de la Vieille Eglise France MN Layer 5A CRG-412 5135 105 wood charcoal n/d -4234 -3657 6.283400 45.90010 Banadora BD Banadora21
Abri Pendimoun France EN 1 Ly-5340 6490 75 plant seed Quercus sp. -5615 -5314 7.505944 43.81221 Binder 1995 Binder95

At first, these data were recorded in an Excel-like spreadsheet in order to facilitate their editing (filter, sorting, filling). As data came from various publications, a homogenization the different values (material, cultures, bibliographical references, etc.) has been done. The dataset mandatory fields are:

The recommended fields are:

  • Culture: a specification of the field Period

mandatory fields

Here we explain more precisely some of the mandatory fields

SiteName

The most accepted version of the site name. For example: Cova de l'Or offers a better designation than L'Or or Or.

Longitude and Latitude

In decimal degrees and a minimal precision of four (4) decimal digits (ex: 1.0453, 43.9211). Since the NeoNet modeling is supra-regional, the app does not need to record dates with high accuracy geographical coordinates. At the minimum, this accuracy can be a location inside the departmental/county boundaries (how to retrieve better coordinates from the map)

Period

The period abbreviation. The main common periods considered here are: LM (Late Mesolithic), UM (Undefined Mesolithic), LMEN (Late Mesolithic/Early Neolithic), EN (Early Neolithic), MN (Middle Neolithic), LN (Late Neolithic), UN (Undefined Neolithic)

periods names colors
EM Early Mesolithic #0000CF
MM Middle Mesolithic #1D1DFF
LM Late Mesolithic #3737FF
LMEN Late Mesolithic/Early Neolithic #6A6AFF
UM Undefined Mesolithic #8484FF
EN Early Neolithic #FF1B1B
EMN Early/Middle Neolithic #FF541B
MN Middle Neolithic #FF8D1B
LN Late Neolithic #FFC04D
UN Undefined Neolithic #E7E700

By default a different hexadecimal color is attributed to each period

PhaseCode

The PhaseCode field provides information about the archaeological context of a given date within a site. In most cases, it corresponds to an archaeological layer or structure. It is useful for layer/structure C14 grouping.

PhaseCode
Str. 12
SONDAGE S5 EB A -50 CM
Upper part of archaeol. Deposit
Porche_F8
1
Layer 16

At the site scale, these field values need to be homogeneized (for example: C.5 or layer 5 -> C5). The n/a value (i.e., not available) is reserved to dates without intra-site contextual information

LabCode

LabCode (i.e., laboratory code) should be unique. Their conventional syntax is ‘AbrevLab-number’, respecting the case letters (upper case and lower case). For example:

LabCode
GrN-12117
Beta-244535
R-1040a
CRG-277
Gif-469
Gif-218

See also the list of laboratories. Exceptionally, if a date has no LabCode – e.g., ‘Sep-H3 mix’ from Fontbregoua, 6082 +/- 35 BP – the convention is to use the PhaseCode (e.g., ‘Sep-H3 mix’) with an underscore as a prefix (e.g., ‘_Sep-H3 mix’) to get an unique key.

C14Age and C14SD

Conventional radiocarbon uncalibrated date (C14Age) and standard deviation error (C14SD). These two fields are used to calibrated the radiocarbon dates and calculate the tpq (terminus post quem) and taq (terminus ante quem).

C14Age C14SD
6950 100
6060 30
6430 80
5870 30
6460 140
6630 40
Material

Material life duration are read from the GitHub 140_id00140_doc_thesaurus.tsv file (ie, NeoNet dataset v.1. The two fields show the material type (column 1) and the material life duration (column 2), for example:

material.type life.duration
Triticcum d short.life
Carbo Ramnus long.life
Charbon- Prunus long.life
organic substance short.life
Cereal short.life
Buxus s long.life

Among these values, the published NeoNet dataset uses uniquely these ones:

Material
animal bone
human and animal bone
human bone
n/a
n/d
organic
plant seed
shell
wood charcoal
wood charcoal or plant seeds

The join between the main dataset and the material life thesaurus gives:

material.type life.duration
animal bone short.life
human bone short.life
n/a
n/d
organic short.life
plant seed short.life
shell long.life
wood charcoal long.life
MaterialSpecies
bib and bib_url

Every radiocarbon date should be referenced with (i) a short plain text bibliographical reference (bib field) and (ii) a DOI or, when missing, a BibTex key (bib_url field). We favor the earliest mention of the radiocarbon date.

bib

The plain text that will be plot for each radiocarbon date under the bibliographical reference section. Basically the name of the author(s) and the publication year, for example Guilaine et al. 1993, Binder 2018 or Manen et Sabatier 2013. The values of this field can be the same for two different publications (e.g. Delibrias et al. 1982 refers to two different publications the same year)

bib_url

Either a DOI or a unique BibTeX key. We favor the DOI as a unique bibliographical reference. The values of this field should be unique for a single publication (e.g. the BibTeX keys Delibrias82 and Delibrias82a). For example:

bib bib_url
Baills et al. 1993 Baills93
Perrin & Manen 2021 https://doi.org/10.1371/journal.pone.0246964
Perrin & Manen 2021 https://doi.org/10.1371/journal.pone.0246964
Allue 2005 Allue05
Montes et al. 2015 https://doi.org/10.21630/maa.2015.66.06
Biagi & Starnini 2016 Biagi16

  • the DOI exists: Add the complete DOI to the field: https://10.1016/j.jaa.2016.01.007

  • the DOI doesn’t exists: The complete bibliographical reference has to be included into the BIB document (eg., id00140_doc_reference.bib). In the BIB file, the bibliographical reference keyis the name of the first author and the two last digits of the year (eg., Guilaine93):

@book{Guilaine93,
title={Dourgne: derniers chasseurs-collecteurs et premiers {\'e}leveurs de la Haute-Vall{\'e}e de l'Aude},
author={Guilaine, Jean and Barbaza, Michel},
year={1993},
publisher={Centre d'anthropologie des soci{\'e}t{\'e}s rurales; Arch{\'e}ologie en Terre d'Aude}
}

The same key of this reference is added to the bib_url field. For example, the key value Guilaine93 to map the main dataset to the BIB file.

bib bib_url
Guilaine et al. 1993 Guilaine93
… …

4. biblio panel

Bibliographical references are recorded in id00140_doc_reference.bib file. If only exist a BibTeX key, and no DOI, this file results of the join between the bib_url field of the C14 spreadsheet and the BIB file.

@Article{Binder18,
title = {Modelling the earliest north-western dispersal of Mediterranean Impressed Wares: new dates and Bayesian chronological model},
author = {Didier Binder and Philippe Lanos and Lucia Angeli and Louise Gomart and Jean Guilaine and Claire Manen and Roberto Maggi and Italo M Muntoni and Chiara Panelli and Giovanna Radi and others},
journal = {Documenta praehistorica},
volume = {44},
pages = {54-77},
year = {2018},
publisher = {University of Ljubljana Department of Archaeology},
}

@InProceedings{Briois09,
title = {L'abri de Buholoup: de l'{\'E}pipal{\'e}olithique au N{\'e}olithique ancien dans le piedmont central des Pyr{\'e}n{\'e}es},
author = {François Briois and Jean Vaquer},
booktitle = {De M{\'e}diterran{\'e}e et d'ailleurs...: m{\'e}langes offerts {\`a} Jean Guilaine},
pages = {141-150},
year = {2009},
}

In the app, this BibTex file is rendered in HTML with an APA citation format (field long.ref) with the read.bib() and the markdown() functions (among others).

5. infos panel

Infos & credits

Adding and verifying data

Adding data

Follow the above recommendations

Verifying data

NeoNet brings together many of the dates already published. The most frequent work is to check the quality and standardise the archaeological information. Here is a workflow that can save you time:

  • retrieve the archaeological information of a given date

  • type the LabCode number of a date in Google Scholar, ex: "OxA-14449" (with the quotes)

  • retrieve the bibtex or DOI of the date publication (cf. bib)

  • click on Cite (red square) and then on BibTeX (green square) buttons

Then you can copy the bib reference as plain text and paste it in a file (any notepad, Word, Excel, etc.)

@article{moore2007project,
title={Project “Early farming in Dalmatia”: Danilo Bitinj 2004-2005 (Preliminary results)},
author={Moore, Andrew and Men{\dj}u{\v{s}}i{\'c}, Marko and Smith, Jennifer and Podrug, Emil},
journal={Vjesnik arheolo{\v{s}}kog muzeja u Zagrebu},
volume={40},
number={1},
pages={15--24},
year={2007},
publisher={Arheolo{\v{s}}ki muzej u Zagrebu}
}

Credits

Currently, the NeoNet database and app received the contributions of the NeoNet workgroup collaborators:

The NeoNet Mediteranean dataset has been published in the Journal of Open Archaeology Data under this BibTex reference:

@article{Huet22,
author = {Huet, Thomas and Cubas, Miriam and Gibaja, Juan .F. and Oms, F. Xavier and Mazzucco, Niccolo},
title = {NeoNet Dataset. Radiocarbon Dates for the Late Mesolithic/Early Neolithic Transition in the North Central-Western Mediterranean Basin},
journal = {Journal of Open Archaeology Data},
year = {2022},
volume = {10},
number = {3},
pages = {1-8},
doi={10.5334/joad.87},
}

The development version of the app is on GitHub: zoometh/neonet where you can check the contribution rules and the relevant license.

Acknowledgement

We are especially thankful to Federico Bianchi of the University of Pisa for the technical support