diff --git a/src/Dimensions/dimension.jl b/src/Dimensions/dimension.jl
index 38d07a631..74cdc620b 100644
--- a/src/Dimensions/dimension.jl
+++ b/src/Dimensions/dimension.jl
@@ -554,3 +554,20 @@ mean(A; dims=Ti)
 @dim Ti TimeDim "Time"
 
 const Time = Ti # For some backwards compat
+
+function Base.convert(::Type{D1}, dim::D2) where {D1<:Dimension{T},D2} where T
+    basetypeof(D2) <: basetypeof(D1) ||
+        throw(ArgumentError("Cannot convert $D1 to $D2"))
+    rebuild(dim, convert(T, val(dim)))
+end
+
+function Base.promote_rule(
+    ::Type{D1}, ::Type{D2}
+) where {D1<:Dimension{T1},D2<:Dimension{T2}} where {T1,T2}
+    T = promote_type(T1, T2)
+    if basetypeof(D1) == basetypeof(D2)
+        basetypeof(D1){T}
+    else
+        Dimension{T}
+    end
+end
\ No newline at end of file
diff --git a/src/Lookups/lookup_arrays.jl b/src/Lookups/lookup_arrays.jl
index 9f69dc1cb..1d2a0b25e 100644
--- a/src/Lookups/lookup_arrays.jl
+++ b/src/Lookups/lookup_arrays.jl
@@ -1,4 +1,3 @@
-
 """
     Lookup
 
@@ -159,11 +158,15 @@ NoLookup() = NoLookup(AutoValues())
 
 rebuild(l::NoLookup; data=parent(l), kw...) = NoLookup(data)
 
+Base.convert(::Type{L1}, lookup::Lookup) where {L1<:NoLookup{A}} where A =
+    NoLookup(convert(A, axes(lookup, 1)))
+
 # Used in @d broadcasts
 struct Length1NoLookup <: AbstractNoLookup end
 Length1NoLookup(::AbstractVector) = Length1NoLookup()
 
 rebuild(l::Length1NoLookup; kw...) = Length1NoLookup()
+
 Base.parent(::Length1NoLookup) = Base.OneTo(1)
 
 """
@@ -176,7 +179,7 @@ is provided by this package.
 `AbstractSampled` must have  `order`, `span` and `sampling` fields,
 or a `rebuild` method that accepts them as keyword arguments.
 """
-abstract type AbstractSampled{T,O<:Order,Sp<:Span,Sa<:Sampling} <: Aligned{T,O} end
+abstract type AbstractSampled{T,A,O<:Order,Sp<:Span,Sa<:Sampling,M} <: Aligned{T,O} end
 
 span(lookup::AbstractSampled) = lookup.span
 sampling(lookup::AbstractSampled) = lookup.sampling
@@ -192,6 +195,24 @@ function Base.:(==)(l1::AbstractSampled, l2::AbstractSampled)
     parent(l1) == parent(l2)
 end
 
+function Base.promote_rule(
+    ::Type{S1}, ::Type{S2}
+) where {S1<:AbstractSampled{T1,A1,O1,Sp1,Sa1,M1},
+         S2<:AbstractSampled{T2,A2,O2,Sp2,Sa2,M2}
+} where {T1,A1,O1,Sp1,Sa1,M1,T2,A2,O2,Sp2,Sa2,M2}
+    A = promote_type(A1, A2)
+    T = eltype(A)
+    O = promote_type(O1, O2)
+    Sp = promote_type(Sp1, Sp2)
+    Sa = promote_type(Sa1, Sa2)
+    M = promote_type(M1, M2)
+    if basetypeof(S1) == basetypeof(S2)
+        basetypeof(S1){T,A,O,Sp,Sa,M}
+    else
+        AbstractSampled{T,A,O,Sp,Sa,M}
+    end
+end
+
 for f in (:getindex, :view, :dotview)
     @eval begin
         # span may need its step size or bounds updated
@@ -306,7 +327,7 @@ A = ones(x, y)
   20    1.0  1.0  1.0   1.0
 ```
 """
-struct Sampled{T,A<:AbstractVector{T},O,Sp,Sa,M} <: AbstractSampled{T,O,Sp,Sa}
+struct Sampled{T,A<:AbstractVector{T},O,Sp,Sa,M} <: AbstractSampled{T,A,O,Sp,Sa,M}
     data::A
     order::O
     span::Sp
@@ -326,6 +347,17 @@ function rebuild(l::Sampled;
     Sampled(data, order, span, sampling, metadata)
 end
 
+function Base.convert(
+    ::Type{S1}, lookup::AbstractSampled
+) where {S1<:Sampled{T,A,O,Sp,Sa,M}} where {T,A,O,Sp,Sa,M}
+    Sampled(convert(A, parent(lookup));
+        order=order(lookup),
+        span=span(lookup),
+        sampling=sampling(lookup),
+        metadata=convert(M, metadata(lookup)),
+    )
+end
+
 # These are used to specialise dispatch:
 # When Cycling, we need to modify any `Selector`. After that
 # we switch to `NotCycling` and use `AbstractSampled` fallbacks.
@@ -342,7 +374,7 @@ An abstract supertype for cyclic lookups.
 
 These are `AbstractSampled` lookups that are cyclic for `Selectors`.
 """
-abstract type AbstractCyclic{X,T,O,Sp,Sa} <: AbstractSampled{T,O,Sp,Sa} end
+abstract type AbstractCyclic{X,T,A,O,Sp,Sa,M} <: AbstractSampled{T,A,O,Sp,Sa,M} end
 
 cycle(l::AbstractCyclic) = l.cycle
 cycle_status(l::AbstractCyclic) = l.cycle_status
@@ -418,7 +450,7 @@ $SAMPLED_ARGUMENTS_DOC
     leap years breaking correct date cycling of a single year. If you actually need this behaviour, 
     please make a GitHub issue.
 """
-struct Cyclic{X,T,A<:AbstractVector{T},O,Sp,Sa,M,C} <: AbstractCyclic{X,T,O,Sp,Sa}
+struct Cyclic{X,T,A<:AbstractVector{T},O,Sp,Sa,M,C} <: AbstractCyclic{X,T,A,O,Sp,Sa,M}
     data::A
     order::O
     span::Sp
@@ -464,18 +496,31 @@ But this can easily be extended, all methods are defined for `AbstractCategorica
 All `AbstractCategorical` must provide a `rebuild`
 method with `data`, `order` and `metadata` keyword arguments.
 """
-abstract type AbstractCategorical{T,O} <: Aligned{T,O} end
+abstract type AbstractCategorical{T,A,O,M} <: Aligned{T,O} end
 
 order(lookup::AbstractCategorical) = lookup.order
 metadata(lookup::AbstractCategorical) = lookup.metadata
 
 const CategoricalEltypes = Union{AbstractChar,Symbol,AbstractString}
 
+function Base.:(==)(l1::AbstractCategorical, l2::AbstractCategorical)
+    order(l1) == order(l2) && parent(l1) == parent(l2)
+end
+
+function Base.promote_rule(::Type{S1}, ::Type{S2}) where {
+    S1<:AbstractCategorical{T1,A1,O1,M1}, S2<:AbstractCategorical{T2,A2,O2,M2}
+} where {T1,A1,O1,M1,T2,A2,O2,M2}
+    T = promote_type(T1, T2)
+    A = promote_type(A1, A2)
+    O = promote_type(O1, O2)
+    M = promote_type(M1, M2)
+    AbstractCategorical{T,A,O,M}
+end
+
 function Adapt.adapt_structure(to, l::AbstractCategorical)
     rebuild(l; data=Adapt.adapt(to, parent(l)), metadata=NoMetadata())
 end
 
-
 """
     Categorical <: AbstractCategorical
 
@@ -533,10 +578,22 @@ function rebuild(l::Categorical;
     Categorical(data, order, metadata)
 end
 
-function Base.:(==)(l1::AbstractCategorical, l2::AbstractCategorical)
-    order(l1) == order(l2) && parent(l1) == parent(l2)
+function Base.promote_rule(::Type{S1}, ::Type{S2}) where {
+    S1<:Categorical{T1,A1,O1,M1}, S2<:Categorical{T2,A2,O2,M2}
+} where {T1,A1,O1,M1,T2,A2,O2,M2}
+    T = promote_type(T1, T2)
+    A = promote_type(A1, A2)
+    O = promote_type(O1, O2)
+    M = promote_type(M1, M2)
+    Categorical{T,A,O,M}
+end
+function Base.convert(::Type{S1}, lookup::AbstractCategorical) where {
+    S1<:Categorical{T,A,O,M}
+} where {T,A,O,M}
+    Categorical(convert(A, parent(lookup));
+        order=order(lookup), metadata=convert(M, metadata(lookup)),
+    )
 end
-
 
 """
     Unaligned <: Lookup
@@ -971,4 +1028,4 @@ function promote_first(a1::AbstractArray, as::AbstractArray...)
     end
 
     return convert(C, a1)
-end
+end
\ No newline at end of file
diff --git a/src/Lookups/lookup_traits.jl b/src/Lookups/lookup_traits.jl
index 1325072a5..b33e1fbed 100644
--- a/src/Lookups/lookup_traits.jl
+++ b/src/Lookups/lookup_traits.jl
@@ -234,6 +234,10 @@ val(span::Regular) = span.step
 
 Base.step(span::Regular) = span.step
 Base.:(==)(l1::Regular, l2::Regular) = val(l1) == val(l2)
+Base.promote_rule(::Type{<:Regular{T1}}, ::Type{<:Regular{T2}}) where {T1,T2}= 
+    Regular{promote_type(T1, T2)}
+Base.convert(::Type{<:Regular{T1}}, span::Regular{T2}) where {T1,T2} = 
+    Regular(convert(T1, val(span)))
 
 """
     Irregular <: Span
@@ -256,6 +260,13 @@ bounds(span::Irregular) = span.bounds
 val(span::Irregular) = span.bounds
 
 Base.:(==)(l1::Irregular, l2::Irregular) = val(l1) == val(l2)
+function Base.promote_rule(
+    ::Type{<:Irregular{<:Tuple{T1,T2}}}, ::Type{<:Irregular{<:Tuple{T3,T4}}}
+)  where {T1,T2,T3,T4}
+    Irregular{Tuple{promote_type(T1, T3), promote_type(T2, T4)}}
+end
+Base.convert(::Type{Irregular{Tuple{T1,T2}}}, s::Irregular{Tuple{<:Any,<:Any}}) where {T1,T2} = 
+    Irregular(convert(Tuple{T1,T2}, val(s)))
 
 """
     Explicit(bounds::AbstractMatrix)
@@ -272,6 +283,10 @@ Explicit() = Explicit(AutoBounds())
 
 val(span::Explicit) = span.val
 Base.:(==)(l1::Explicit, l2::Explicit) = val(l1) == val(l2)
+Base.promote_rule(::Type{<:Explicit{<:B1}}, ::Type{<:Explicit{<:B2}}) where {B1,B2} = 
+    Explicit{promote_type(B1, B2)}
+Base.convert(::Type{<:Explicit{<:B1}}, ::Explicit{<:B2}) where {B1,B2} = 
+    Explicit{promote_type(B1, B2)}
 
 Adapt.adapt_structure(to, s::Explicit) = Explicit(Adapt.adapt_structure(to, val(s)))
 
diff --git a/src/Lookups/metadata.jl b/src/Lookups/metadata.jl
index 0e3250de3..5664d9a6b 100644
--- a/src/Lookups/metadata.jl
+++ b/src/Lookups/metadata.jl
@@ -1,6 +1,6 @@
 
 """
-    AbstractMetadata{X,T}
+    AbstractMetadata{X,K,V,T}
 
 Abstract supertype for all metadata wrappers.
 
@@ -11,11 +11,15 @@ or simply saving data back to the same file type with identical metadata.
 Using a wrapper instead of `Dict` or `NamedTuple` also lets us pass metadata 
 objects to [`set`](@ref) without ambiguity about where to put them.
 """
-abstract type AbstractMetadata{X,T} end
+abstract type AbstractMetadata{X,K,V,T} <: AbstractDict{K,V} end
 
-const _MetadataContents = Union{AbstractDict,NamedTuple}
+const MetadataContents = Union{AbstractDict,NamedTuple}
+const DefaultDict = Dict{Symbol,Any}
 const AllMetadata = Union{AbstractMetadata,AbstractDict}
 
+valtype(::AbstractMetadata{<:Any,<:Any,<:Any,T}) where T = T
+valtype(::Type{<:AbstractMetadata{<:Any,<:Any,<:Any,T}})where T  = T
+
 Base.get(m::AbstractMetadata, args...) = get(val(m), args...)
 Base.getindex(m::AbstractMetadata, key) = getindex(val(m), key)
 Base.setindex!(m::AbstractMetadata, x, key) = setindex!(val(m), x, key)
@@ -38,20 +42,24 @@ Base.:(==)(m1::AbstractMetadata, m2::AbstractMetadata) = m1 isa typeof(m2) && va
 General [`Metadata`](@ref) object. The `X` type parameter
 categorises the metadata for method dispatch, if required. 
 """
-struct Metadata{X,T<:_MetadataContents} <: AbstractMetadata{X,T}
+struct Metadata{X,T<:MetadataContents,K,V} <: AbstractMetadata{X,T,K,V}
     val::T
 end
-Metadata(val::T) where {T<:_MetadataContents} = Metadata{Nothing,T}(val)
-Metadata{X}(val::T) where {X,T<:_MetadataContents} = Metadata{X,T}(val)
+Metadata{X,T}(val::T) where {X,T<:NamedTuple} =
+    Metadata{X,T,Symbol,Any}(val)
+Metadata{X,T}(val::T) where {X,T<:AbstractDict{K,V}} where {K,V} =
+    Metadata{X,T,K,V}(val)
+Metadata(val::T) where {T<:MetadataContents} = Metadata{Nothing,T}(val)
+Metadata{X}(val::T) where {X,T<:MetadataContents} = Metadata{X,T}(val)
 
 # NamedTuple/Dict constructor
-# We have to combine these because the no-arg method is overwritten by empty kw.
-function (::Type{M})(ps...; kw...) where M <: Metadata
-    if length(ps) > 0 && length(kw) > 0
-        throw(ArgumentError("Metadata can be constructed with args of Pair to make a Dict, or kw for a NamedTuple. But not both."))
-    end
-    length(kw) > 0 ? M((; kw...)) : M(Dict(ps...))
+(::Type{M})(p1::Pair, ps::Pair...) where M <: Metadata = M(Dict(p1, ps...))
+function (::Type{M})(; kw...) where M <: Metadata
+    M((; kw...))
 end
+Metadata() = Metadata(DefaultDict())
+Metadata{X}() where X = Metadata{X}(DefaultDict())
+Metadata{X,T}() where {X,T} = Metadata{X,T}(T())
 
 ConstructionBase.constructorof(::Type{<:Metadata{X}}) where {X} = Metadata{X}
 
@@ -74,14 +82,28 @@ Indicates an object has no metadata. But unlike using `nothing`,
 returning the fallback argument. `keys` returns `()` while `haskey`
 always returns `false`.
 """
-struct NoMetadata <: AbstractMetadata{Nothing,NamedTuple{(),Tuple{}}} end
+struct NoMetadata <: AbstractMetadata{Nothing,Dict{Symbol,Any},Symbol,Any} end
 
 val(m::NoMetadata) = NamedTuple()
 
 Base.keys(::NoMetadata) = ()
-Base.haskey(::NoMetadata, args...) = false
 Base.get(::NoMetadata, key, fallback) = fallback
 Base.length(::NoMetadata) = 0
+Base.convert(::Type{NoMetadata}, s::Union{NamedTuple,AbstractMetadata,AbstractDict}) =
+    NoMetadata()
+
+Base.convert(::Type{Metadata}, ::NoMetadata) = Metadata()
+Base.convert(::Type{Metadata}, m::MetadataContents) = Metadata(m)
+Base.convert(::Type{Metadata{X}}, m::MetadataContents) where X = Metadata{X}(m)
+Base.convert(::Type{Metadata{X,T}}, m::AbstractDict) where {X,T<:AbstractDict} =
+    Metadata{X,T}(T(m))
+Base.convert(::Type{Metadata{X,T}}, m::NamedTuple) where {X,T<:AbstractDict} = 
+    Metadata{X,T}(T(metadatadict(m)))
+Base.convert(::Type{Metadata{X,T}}, m::NamedTuple) where {X,T<:NamedTuple} = 
+    Metadata{X,T}(T(m))
+Base.convert(::Type{Metadata{X,T}}, m::AbstractDict) where {X,T<:NamedTuple} = 
+    Metadata{X,T}(T(pairs(metadatadict(m))))
+
 
 function Base.show(io::IO, mime::MIME"text/plain", metadata::Metadata{N}) where N
     print(io, "Metadata")
@@ -96,12 +118,13 @@ end
 
 # Metadata utils
 
-function metadatadict(dict)
-    symboldict = Dict{Symbol,Any}()
-    for (k, v) in dict
+metadatadict(dict) = metadatadict(DefaultDict, dict)
+function metadatadict(::Type{T}, dict) where T
+    symboldict = T()
+    for (k, v) in pairs(dict)
         symboldict[Symbol(k)] = v
     end
-    symboldict
+    return symboldict
 end
 
 metadata(x) = NoMetadata()
@@ -110,4 +133,4 @@ units(x) = units(metadata(x))
 units(m::NoMetadata) = nothing
 units(m::Nothing) = nothing
 units(m::Metadata) = get(m, :units, nothing)
-units(m::AbstractDict) = get(m, :units, nothing)
+units(m::AbstractDict) = get(m, :units, nothing)
\ No newline at end of file
diff --git a/src/array/array.jl b/src/array/array.jl
index d3e054c28..cb11084a9 100644
--- a/src/array/array.jl
+++ b/src/array/array.jl
@@ -38,6 +38,7 @@ Base.checkbounds(::Type{Bool}, A::AbstractBasicDimArray, d1::IDim, dims::IDim...
 Base.checkbounds(A::AbstractBasicDimArray, d1::IDim, dims::IDim...) =
     Base.checkbounds(A, dims2indices(A, (d1, dims...))...)
 
+
 """
     AbstractDimArray <: AbstractBasicArray
 
@@ -464,7 +465,7 @@ function DimArray(A::AbstractDimArray;
 )
     DimArray(data, dims; refdims, name, metadata)
 end
-DimArray{T}(A::AbstractDimArray; kw...) where T = DimArray(convert.(T, A))
+DimArray{T}(A::AbstractDimArray; kw...) where T = DimArray(convert.(T, A); kw...)
 DimArray{T}(A::AbstractDimArray{T}; kw...) where T = DimArray(A; kw...)
 # We collect other kinds of AbstractBasicDimArray 
 # to avoid complicated nesting of dims
@@ -485,7 +486,7 @@ function DimArray(f::Function, dim::Dimension; name=Symbol(nameof(f), "(", name(
      DimArray(f.(val(dim)), (dim,); name)
 end
 
-DimArray(itr::Base.Generator; kwargs...) = rebuild(collect(itr); kwargs...)
+DimArray(itr::Base.Generator; kw...) = rebuild(collect(itr); kw...)
 
 const DimVector = DimArray{T,1} where T
 const DimMatrix = DimArray{T,2} where T
@@ -501,6 +502,31 @@ DimMatrix(A::AbstractMatrix, args...; kw...) = DimArray(A, args...; kw...)
 Base.convert(::Type{DimArray}, A::AbstractDimArray) = DimArray(A)
 Base.convert(::Type{DimArray{T}}, A::AbstractDimArray) where {T} = DimArray{T}(A)
 
+function Base.convert(
+    ::Type{<:DimArray{T,N,DT,RT,AT,NaT,MeT}}, a::DimArray{S,N}
+) where {T,N,S,DT,RT,AT,NaT,MeT}
+    rebuild(a; 
+        data=convert(AT, parent(a)), 
+        dims=convert(DT, dims(a)), 
+        name=convert(NaT, name(a)),
+        refdims=RT <: Tuple{} ? () : convert(RT, refdims(a)),
+        metadata=convert(MeT, metadata(a)),
+    )
+end
+
+# Promote element types 
+function Base.promote_rule(
+    a::Type{<:DimArray{T,N,DT,RT,AT,NaT,MeT}}, b::Type{<:DimArray{S,N,DS,RS,AS,NaS,MeS}}
+) where {T,S,N,DT,DS,RT,RS,AT,AS,NaT,NaS,MeT,MeS}
+    A = promote_type(AT, AS)
+    TS = eltype(A) 
+    D = promote_type(DT, DS) 
+    R = RT <: Tuple{} || RS <: Tuple{} ? Tuple{} : promote_type(RT, RS) 
+    Na = promote_type(NaT, NaS)
+    M = promote_type(MeT, MeS)
+    return DimArray{TS,N,D,R,A,Na,M}
+end
+
 checkdims(A::AbstractArray{<:Any,N}, dims::Tuple) where N = checkdims(N, dims)
 checkdims(::Type{<:AbstractArray{<:Any,N}}, dims::Tuple) where N = checkdims(N, dims)
 checkdims(n::Integer, dims::Tuple) = length(dims) == n || _dimlengtherror(n, length(dims))
diff --git a/src/array/broadcast.jl b/src/array/broadcast.jl
index 57f4966d0..b136656fa 100644
--- a/src/array/broadcast.jl
+++ b/src/array/broadcast.jl
@@ -77,7 +77,7 @@ function Broadcast.copy(bc::Broadcasted{DimensionalStyle{S}}) where S
     # unwrap AbstractDimArray data
     data = data isa AbstractDimArray ? parent(data) : data
     dims = format(Dimensions.promotedims(bdims...; skip_length_one=true), data)
-    return rebuild(A; data, dims, refdims=refdims(A), name=Symbol(""))
+    return rebuild(A; data, dims, refdims=refdims(A), name=_noname(name(A)))
 end
 
 function Base.copyto!(dest::AbstractArray, bc::Broadcasted{DimensionalStyle{S}}) where S
@@ -96,7 +96,7 @@ end
 
 function Base.similar(bc::Broadcast.Broadcasted{DimensionalStyle{S}}, ::Type{T}) where {S,T}
     A = _firstdimarray(bc)
-    rebuildsliced(A, similar(_unwrap_broadcasted(bc), T, axes(bc)...), axes(bc), Symbol(""))
+    rebuildsliced(A, similar(_unwrap_broadcasted(bc), T, axes(bc)...), axes(bc), _noname(name(A)))
 end
 
 
diff --git a/src/name.jl b/src/name.jl
index b47fed9eb..2b025b5c2 100644
--- a/src/name.jl
+++ b/src/name.jl
@@ -39,3 +39,18 @@ Base.Symbol(::Name{X}) where X = X
 Base.string(::Name{X}) where X = string(X)
 
 name(x::Name) = x
+
+
+Base.convert(::Type{NoName}, s::Symbol) = NoName()
+Base.convert(::Type{Symbol}, ::NoName) = Symbol("")
+# TODO should we check that X and s match?
+Base.convert(::Type{Name{X}}, s::Symbol) where X = Name{X}()
+Base.convert(::Type{Name}, s::Symbol) = Name{s}()
+Base.convert(::Type{Symbol}, x::Name{X}) where X = X
+
+Base.promote_rule(::Type{NoName}, ::Type{Symbol}) = NoName
+Base.promote_rule(::Type{NoName}, ::Type{<:Name}) = NoName
+Base.promote_rule(::Type{Symbol}, ::Type{NoName}) = NoName
+Base.promote_rule(::Type{<:Name}, ::Type{NoName}) = NoName
+Base.promote_rule(::Type{<:Name}, ::Type{Symbol}) = Symbol
+Base.promote_rule(::Type{Symbol}, ::Type{<:Name}) = Symbol
\ No newline at end of file
diff --git a/src/stack/stack.jl b/src/stack/stack.jl
index 597297627..5bc55ae93 100644
--- a/src/stack/stack.jl
+++ b/src/stack/stack.jl
@@ -429,7 +429,7 @@ function DimStack(A::AbstractDimArray;
     layersfrom=nothing, metadata=metadata(A), refdims=refdims(A), kw...
 )
     layers = if isnothing(layersfrom)
-        keys = name(A) in (NoName(), Symbol(""), Name(Symbol(""))) ? (:layer1,) : (name(A),)
+        keys = (_cleankey(name(A)),)
         NamedTuple{keys}((A,))
     else
         keys = Tuple(_layerkeysfromdim(A, layersfrom))
diff --git a/test/array.jl b/test/array.jl
index dc5aea74c..82c04c87f 100644
--- a/test/array.jl
+++ b/test/array.jl
@@ -1,5 +1,7 @@
-using DimensionalData, Test , Unitful, SparseArrays, Dates, Random
-using DimensionalData: layerdims, checkdims
+using DimensionalData, Test , Unitful, SparseArrays, Dates, Random, Statistics
+using DimensionalData: layerdims, checkdims, Name, NoName
+using DimensionalData.Lookups
+using DimensionalData.Dimensions
 using LinearAlgebra
 
 using DimensionalData.Lookups, DimensionalData.Dimensions
@@ -602,3 +604,59 @@ end
     @test Base.dataids(a) == Base.dataids(parent(a))
     @test Base.mightalias(a, parent(a))
 end
+
+#@testset "promotion" begin
+    a = rand(X(1:10))
+    b = rand(Int, X(1:10))
+    @test promote_type(typeof(a), typeof(b)) == typeof(a)
+
+    M = fill(UInt16(32000), 2)
+
+    x1 = X(1:2)
+    x2 = X(1.0:2.0)
+    T = promote_type(typeof(x1), typeof(x2))
+    @test convert(T, x2) isa T
+    @test convert(T, x2) isa T
+    @test val(convert(T, x2)) === 1.0:1.0:2.0
+    f1 = format(x1)
+    f2 = format(x2)
+
+    P = promote_type(typeof(f1), typeof(f2))
+    @test 
+    typeof(convert(P, f1))
+     typeof(f2)
+    @test convert(P, f2) isa typeof(f2)
+
+    @test x2 isa promote_type(typeof(format(x1)), typeof(format(x2)))
+
+    D = DimArray(M, x1)
+    D2 = DimArray(M, x1; name=:testname)
+    D3 = DimArray(M, x1; metadata=Metadata(:test => "test"))
+    D4 = DimArray(M, x2; metadata=Metadata(:test => "test"))
+    @test mean([D, D]) == 
+        mean([D2, D2]) == 
+        mean([D3, D3]) == 
+        mean([D4, D4]) == 
+        mean([M, M])
+    @test mean([D, D]) == mean([D, D2]) == mean([D2, D])
+
+    @test typeof(convert(typeof(D), D2)) == typeof(D)
+    @test typeof(convert(typeof(D), D3)) == typeof(D)
+    D isa promote_type(typeof(D), typeof(D3))
+    # @test 
+    P = promote_type(typeof(D3), typeof(D))
+    typeof(convert(P, D4)) <: P
+    typeof(D4)
+     <: P
+    @test typeof(convert(typeof(D2), D)) == typeof(D2)
+    @test typeof(convert(typeof(D3), D)) == typeof(D3)
+    @test 
+    typeof(convert(typeof(D4), D))
+     == 
+    promote_type(typeof(D4), typeof(D))
+    typeof(convert(typeof(D4), D))
+    typeof(D4)
+
+    @test promote_type(typeof(D), typeof(D2)) ==
+    convert(typeof(D), D2)
+end
\ No newline at end of file