Improving Data Quality by Rules: A Numismatic Example. Tolle, K. & Wigg-Wolf, D. November, 2020. 🏷️ /unread![Improving Data Quality by Rules: A Numismatic Example [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex The archaeological data dealt with in our database solution Antike Fundmünzen in Europa (AFE), which records finds of ancient coins, is entered by humans. Based on the Linked Open Data (LOD) approach, we link our data to Nomisma.org concepts, as well as to other resources like Online Coins of the Roman Empire (OCRE). Since information such as denomination, material, etc. is recorded for each single coin, this information should be identical for coins of the same type. Unfortunately, this is not always the case, mostly due to human errors. Based on rules that we implemented, we were able to make use of this redundant information in order to detect possible errors within AFE, and were even able to correct errors in Nomimsa.org. However, the approach had the weakness that it was necessary to transform the data into an internal data model. In a second step, we therefore developed our rules within the Linked Open Data world. The rules can now be applied to datasets following the Nomisma. org modelling approach, as we demonstrated with data held by Corpus Nummorum Thracorum (CNT). We believe that the use of methods like this to increase the data quality of individual databases, as well as across different data sources and up to the higher levels of OCRE and Nomisma.org, is mandatory in order to increase trust in them. 【摘要翻译】我们的数据库解决方案 Antike Fundmünzen in Europa (AFE) 中处理的考古数据 in Europa (AFE) 中的考古数据是由人类输入的。 人输入的。基于关联开放数据（LOD）方法，我们将数据与 Nomisma. 链接到 Nomisma.org 概念，以及其他资源，如 Online Coins of 罗马帝国在线钱币（OCRE）等其他资源。由于每枚钱币都记录了面额、材质等信息，因此我们的数据是开放的、 等信息都记录在每一枚钱币上，因此这些信息对于同一类型的钱币来说应该是相同的。 相同类型的钱币。遗憾的是，情况并非总是如此，这主要是由于 人为错误。根据我们实施的规则，我们能够利用这些冗余信息 冗余信息，以检测 AFE 中可能存在的错误，甚至能够纠正 Normo 中的错误。 甚至能够纠正 Nomimsa.org 中的错误。不过，这种方法有 不过，这种方法也有不足之处，那就是必须将数据转换为内部数据模型。 模型。因此，在第二步中，我们在关联的 开放数据世界中开发了我们的规则。现在，这些规则可以应用于采用Nomisma.org建模方法的数据集。 org建模方法的数据集。 Nummorum Thracorum（CNT）所拥有的数据进行了演示。我们相信，使用这样的方法可以 我们相信，使用这样的方法可以提高单个数据库的数据质量，以及不同数据源之间 和 Nomisma.org 的更高层次的数据质量。 我们相信，使用这样的方法来提高单个数据库的数据质量，以及不同数据源和更高层次的 OCRE 和 Nomisma.org 的数据质量，是提高它们的信任度所必须的。
@article{tolle2020,
title = {Improving {Data} {Quality} by {Rules}: {A} {Numismatic} {Example}},
copyright = {http://creativecommons.org/licenses/by-nc-nd/3.0/de/deed.de},
shorttitle = {通过规则提高数据质量：钱币学实例},
url = {https://publikationen.uni-tuebingen.de/xmlui/handle/10900/101838},
doi = {10.15496/publikation-43217},
abstract = {The archaeological data dealt with in our database solution Antike Fundmünzen
in Europa (AFE), which records finds of ancient coins, is entered by
humans. Based on the Linked Open Data (LOD) approach, we link our data
to Nomisma.org concepts, as well as to other resources like Online Coins of
the Roman Empire (OCRE). Since information such as denomination, material,
etc. is recorded for each single coin, this information should be identical for
coins of the same type. Unfortunately, this is not always the case, mostly due to
human errors. Based on rules that we implemented, we were able to make use of
this redundant information in order to detect possible errors within AFE, and
were even able to correct errors in Nomimsa.org. However, the approach had
the weakness that it was necessary to transform the data into an internal data
model. In a second step, we therefore developed our rules within the Linked
Open Data world. The rules can now be applied to datasets following the Nomisma.
org modelling approach, as we demonstrated with data held by Corpus
Nummorum Thracorum (CNT). We believe that the use of methods like this to
increase the data quality of individual databases, as well as across different data
sources and up to the higher levels of OCRE and Nomisma.org, is mandatory in
order to increase trust in them.
【摘要翻译】我们的数据库解决方案 Antike Fundmünzen in Europa (AFE) 中处理的考古数据
in Europa (AFE) 中的考古数据是由人类输入的。
人输入的。基于关联开放数据（LOD）方法，我们将数据与 Nomisma.
链接到 Nomisma.org 概念，以及其他资源，如 Online Coins of
罗马帝国在线钱币（OCRE）等其他资源。由于每枚钱币都记录了面额、材质等信息，因此我们的数据是开放的、
等信息都记录在每一枚钱币上，因此这些信息对于同一类型的钱币来说应该是相同的。
相同类型的钱币。遗憾的是，情况并非总是如此，这主要是由于
人为错误。根据我们实施的规则，我们能够利用这些冗余信息
冗余信息，以检测 AFE 中可能存在的错误，甚至能够纠正 Normo 中的错误。
甚至能够纠正 Nomimsa.org 中的错误。不过，这种方法有
不过，这种方法也有不足之处，那就是必须将数据转换为内部数据模型。
模型。因此，在第二步中，我们在关联的
开放数据世界中开发了我们的规则。现在，这些规则可以应用于采用Nomisma.org建模方法的数据集。
org建模方法的数据集。
Nummorum Thracorum（CNT）所拥有的数据进行了演示。我们相信，使用这样的方法可以
我们相信，使用这样的方法可以提高单个数据库的数据质量，以及不同数据源之间
和 Nomisma.org 的更高层次的数据质量。
我们相信，使用这样的方法来提高单个数据库的数据质量，以及不同数据源和更高层次的 OCRE 和 Nomisma.org 的数据质量，是提高它们的信任度所必须的。},
language = {en},
urldate = {2021-06-01},
author = {Tolle, Karsten and Wigg-Wolf, David},
month = nov,
year = {2020},
note = {🏷️ /unread},
keywords = {/unread},
}
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Unfortunately, this is not always the case, mostly due to human errors. Based on rules that we implemented, we were able to make use of this redundant information in order to detect possible errors within AFE, and were even able to correct errors in Nomimsa.org. However, the approach had the weakness that it was necessary to transform the data into an internal data model. In a second step, we therefore developed our rules within the Linked Open Data world. The rules can now be applied to datasets following the Nomisma. org modelling approach, as we demonstrated with data held by Corpus Nummorum Thracorum (CNT). We believe that the use of methods like this to increase the data quality of individual databases, as well as across different data sources and up to the higher levels of OCRE and Nomisma.org, is mandatory in order to increase trust in them. 【摘要翻译】我们的数据库解决方案 Antike Fundmünzen in Europa (AFE) 中处理的考古数据 in Europa (AFE) 中的考古数据是由人类输入的。 人输入的。基于关联开放数据（LOD）方法，我们将数据与 Nomisma. 链接到 Nomisma.org 概念，以及其他资源，如 Online Coins of 罗马帝国在线钱币（OCRE）等其他资源。由于每枚钱币都记录了面额、材质等信息，因此我们的数据是开放的、 等信息都记录在每一枚钱币上，因此这些信息对于同一类型的钱币来说应该是相同的。 相同类型的钱币。遗憾的是，情况并非总是如此，这主要是由于 人为错误。根据我们实施的规则，我们能够利用这些冗余信息 冗余信息，以检测 AFE 中可能存在的错误，甚至能够纠正 Normo 中的错误。 甚至能够纠正 Nomimsa.org 中的错误。不过，这种方法有 不过，这种方法也有不足之处，那就是必须将数据转换为内部数据模型。 模型。因此，在第二步中，我们在关联的 开放数据世界中开发了我们的规则。现在，这些规则可以应用于采用Nomisma.org建模方法的数据集。 org建模方法的数据集。 Nummorum Thracorum（CNT）所拥有的数据进行了演示。我们相信，使用这样的方法可以 我们相信，使用这样的方法可以提高单个数据库的数据质量，以及不同数据源之间 和 Nomisma.org 的更高层次的数据质量。 我们相信，使用这样的方法来提高单个数据库的数据质量，以及不同数据源和更高层次的 OCRE 和 Nomisma.org 的数据质量，是提高它们的信任度所必须的。","language":"en","urldate":"2021-06-01","author":[{"propositions":[],"lastnames":["Tolle"],"firstnames":["Karsten"],"suffixes":[]},{"propositions":[],"lastnames":["Wigg-Wolf"],"firstnames":["David"],"suffixes":[]}],"month":"November","year":"2020","note":"🏷️ /unread","keywords":"/unread","bibtex":"@article{tolle2020,\n\ttitle = {Improving {Data} {Quality} by {Rules}: {A} {Numismatic} {Example}},\n\tcopyright = {http://creativecommons.org/licenses/by-nc-nd/3.0/de/deed.de},\n\tshorttitle = {通过规则提高数据质量：钱币学实例},\n\turl = {https://publikationen.uni-tuebingen.de/xmlui/handle/10900/101838},\n\tdoi = {10.15496/publikation-43217},\n\tabstract = {The archaeological data dealt with in our database solution Antike Fundmünzen \nin Europa (AFE), which records finds of ancient coins, is entered by \nhumans. Based on the Linked Open Data (LOD) approach, we link our data \nto Nomisma.org concepts, as well as to other resources like Online Coins of \nthe Roman Empire (OCRE). Since information such as denomination, material, \netc. is recorded for each single coin, this information should be identical for \ncoins of the same type. Unfortunately, this is not always the case, mostly due to \nhuman errors. Based on rules that we implemented, we were able to make use of \nthis redundant information in order to detect possible errors within AFE, and \nwere even able to correct errors in Nomimsa.org. However, the approach had \nthe weakness that it was necessary to transform the data into an internal data \nmodel. In a second step, we therefore developed our rules within the Linked \nOpen Data world. The rules can now be applied to datasets following the Nomisma. \norg modelling approach, as we demonstrated with data held by Corpus \nNummorum Thracorum (CNT). We believe that the use of methods like this to \nincrease the data quality of individual databases, as well as across different data \nsources and up to the higher levels of OCRE and Nomisma.org, is mandatory in \norder to increase trust in them.\n\n【摘要翻译】我们的数据库解决方案 Antike Fundmünzen in Europa (AFE) 中处理的考古数据\nin Europa (AFE) 中的考古数据是由人类输入的。\n人输入的。基于关联开放数据（LOD）方法，我们将数据与 Nomisma.\n链接到 Nomisma.org 概念，以及其他资源，如 Online Coins of\n罗马帝国在线钱币（OCRE）等其他资源。由于每枚钱币都记录了面额、材质等信息，因此我们的数据是开放的、\n等信息都记录在每一枚钱币上，因此这些信息对于同一类型的钱币来说应该是相同的。\n相同类型的钱币。遗憾的是，情况并非总是如此，这主要是由于\n人为错误。根据我们实施的规则，我们能够利用这些冗余信息\n冗余信息，以检测 AFE 中可能存在的错误，甚至能够纠正 Normo 中的错误。\n甚至能够纠正 Nomimsa.org 中的错误。不过，这种方法有\n不过，这种方法也有不足之处，那就是必须将数据转换为内部数据模型。\n模型。因此，在第二步中，我们在关联的\n开放数据世界中开发了我们的规则。现在，这些规则可以应用于采用Nomisma.org建模方法的数据集。\norg建模方法的数据集。\nNummorum Thracorum（CNT）所拥有的数据进行了演示。我们相信，使用这样的方法可以\n我们相信，使用这样的方法可以提高单个数据库的数据质量，以及不同数据源之间\n和 Nomisma.org 的更高层次的数据质量。\n我们相信，使用这样的方法来提高单个数据库的数据质量，以及不同数据源和更高层次的 OCRE 和 Nomisma.org 的数据质量，是提高它们的信任度所必须的。},\n\tlanguage = {en},\n\turldate = {2021-06-01},\n\tauthor = {Tolle, Karsten and Wigg-Wolf, David},\n\tmonth = nov,\n\tyear = {2020},\n\tnote = {🏷️ /unread},\n\tkeywords = {/unread},\n}\n","author_short":["Tolle, K.","Wigg-Wolf, D."],"key":"tolle2020","id":"tolle2020","bibbaseid":"tolle-wiggwolf-improvingdataqualitybyrulesanumismaticexample-2020","role":"author","urls":{"Paper":"https://publikationen.uni-tuebingen.de/xmlui/handle/10900/101838"},"keyword":["/unread"],"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://api.zotero.org/groups/2386895/collections/XX2NLPN2/items?format=bibtex&limit=100","dataSources":["k3QfbE45mGbcFcKRM","Ce3zJ448FfXtsN7qp"],"keywords":["/unread"],"search_terms":["improving","data","quality","rules","numismatic","example","tolle","wigg-wolf"],"title":"Improving Data Quality by Rules: A Numismatic Example","year":2020}